From 52888d5ae1604a4bd802b6746d052d83bdedcb32 Mon Sep 17 00:00:00 2001 From: toshan-luktuke Date: Fri, 26 Aug 2022 21:20:50 +0530 Subject: [PATCH] Change location of files --- blockDocs/Blocks/Blur.html | 16 + blockDocs/search.js | 46 --- {Blocks => docs/Blocks}/Blur.py | 6 + {Blocks => docs/Blocks}/Camera.py | 6 + {Blocks => docs/Blocks}/ColorFilter.py | 6 + {Blocks => docs/Blocks}/ContourDetector.py | 6 + {Blocks => docs/Blocks}/Cropper.py | 6 + {Blocks => docs/Blocks}/Dilation.py | 6 + {Blocks => docs/Blocks}/EdgeDetector.py | 6 + {Blocks => docs/Blocks}/Erosion.py | 6 + {Blocks => docs/Blocks}/FaceDetector.py | 6 + {Blocks => docs/Blocks}/IMU.py | 8 +- {Blocks => docs/Blocks}/ImageRead.py | 6 + {Blocks => docs/Blocks}/MotorDriver.py | 6 + {Blocks => docs/Blocks}/ObjectDetector.py | 6 + {Blocks => docs/Blocks}/Odometer.py | 6 + {Blocks => docs/Blocks}/PID.py | 6 + {Blocks => docs/Blocks}/ROSCamera.py | 6 + {Blocks => docs/Blocks}/Screen.py | 6 + {Blocks => docs/Blocks}/Teleoperator.py | 6 + {Blocks => docs/Blocks}/Threshold.py | 6 + {Blocks => docs/Blocks}/VideoStreamer.py | 6 + {Blocks => docs/Blocks}/__init__.py | 0 {Blocks => docs/Blocks}/module.html.jinja2 | 2 +- {Blocks => docs/Blocks}/utils/__init__.py | 0 .../Blocks}/utils/models/__init__.py | 0 .../haarcascade_frontalface_default.xml | 0 .../utils/models/yolov3/yolov3-tiny.cfg | 0 .../utils/models/yolov3/yolov3-tiny.weights | Bin .../Blocks}/utils/models/yolov3/yolov3.txt | 0 docs/_pages/documentation.md | 3 + {blockDocs => docs/blockDocs}/Blocks.html | 90 ++-- docs/blockDocs/Blocks/Blur.html | 390 ++++++++++++++++++ .../blockDocs}/Blocks/Camera.html | 102 +++-- .../blockDocs}/Blocks/ColorFilter.html | 98 +++-- .../blockDocs}/Blocks/ContourDetector.html | 150 ++++--- .../blockDocs}/Blocks/Cropper.html | 94 +++-- .../blockDocs}/Blocks/Dilation.html | 102 +++-- .../blockDocs}/Blocks/EdgeDetector.html | 98 +++-- .../blockDocs}/Blocks/Erosion.html | 102 +++-- .../blockDocs}/Blocks/FaceDetector.html | 148 ++++--- {blockDocs => docs/blockDocs}/Blocks/IMU.html | 96 +++-- .../blockDocs}/Blocks/ImageRead.html | 72 ++-- .../blockDocs}/Blocks/MotorDriver.html | 128 +++--- .../blockDocs}/Blocks/Odometer.html | 78 ++-- {blockDocs => docs/blockDocs}/Blocks/PID.html | 152 ++++--- .../blockDocs}/Blocks/ROSCamera.html | 86 ++-- .../blockDocs}/Blocks/Screen.html | 78 ++-- .../blockDocs}/Blocks/Teleoperator.html | 130 +++--- .../blockDocs}/Blocks/Threshold.html | 102 +++-- .../blockDocs}/Blocks/VideoStreamer.html | 90 ++-- .../blockDocs}/Blocks/utils.html | 0 .../blockDocs}/Blocks/utils/models.html | 0 docs/blockDocs/assets/blur-usage.png | Bin 0 -> 80689 bytes docs/blockDocs/assets/bulr-usage.png | Bin 0 -> 18897 bytes docs/blockDocs/assets/lenna-blur.png | Bin 0 -> 71425 bytes docs/blockDocs/assets/lenna.png | Bin 0 -> 102441 bytes {blockDocs => docs/blockDocs}/index.html | 0 docs/blockDocs/search.js | 46 +++ .../blocks/basic/code/code-widget.tsx | 2 +- 60 files changed, 1733 insertions(+), 890 deletions(-) delete mode 100644 blockDocs/search.js rename {Blocks => docs/Blocks}/Blur.py (94%) rename {Blocks => docs/Blocks}/Camera.py (92%) rename {Blocks => docs/Blocks}/ColorFilter.py (93%) rename {Blocks => docs/Blocks}/ContourDetector.py (94%) rename {Blocks => docs/Blocks}/Cropper.py (92%) rename {Blocks => docs/Blocks}/Dilation.py (93%) rename {Blocks => docs/Blocks}/EdgeDetector.py (90%) rename {Blocks => docs/Blocks}/Erosion.py (92%) rename {Blocks => docs/Blocks}/FaceDetector.py (90%) rename {Blocks => docs/Blocks}/IMU.py (90%) rename {Blocks => docs/Blocks}/ImageRead.py (89%) rename {Blocks => docs/Blocks}/MotorDriver.py (93%) rename {Blocks => docs/Blocks}/ObjectDetector.py (96%) rename {Blocks => docs/Blocks}/Odometer.py (92%) rename {Blocks => docs/Blocks}/PID.py (91%) rename {Blocks => docs/Blocks}/ROSCamera.py (93%) rename {Blocks => docs/Blocks}/Screen.py (88%) rename {Blocks => docs/Blocks}/Teleoperator.py (88%) rename {Blocks => docs/Blocks}/Threshold.py (91%) rename {Blocks => docs/Blocks}/VideoStreamer.py (91%) rename {Blocks => docs/Blocks}/__init__.py (100%) rename {Blocks => docs/Blocks}/module.html.jinja2 (99%) rename {Blocks => docs/Blocks}/utils/__init__.py (100%) rename {Blocks => docs/Blocks}/utils/models/__init__.py (100%) rename {Blocks => docs/Blocks}/utils/models/haar_cascade/haarcascade_frontalface_default.xml (100%) rename {Blocks => docs/Blocks}/utils/models/yolov3/yolov3-tiny.cfg (100%) rename {Blocks => docs/Blocks}/utils/models/yolov3/yolov3-tiny.weights (100%) rename {Blocks => docs/Blocks}/utils/models/yolov3/yolov3.txt (100%) rename {blockDocs => docs/blockDocs}/Blocks.html (89%) create mode 100644 docs/blockDocs/Blocks/Blur.html rename {blockDocs => docs/blockDocs}/Blocks/Camera.html (94%) rename {blockDocs => docs/blockDocs}/Blocks/ColorFilter.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/ContourDetector.html (94%) rename {blockDocs => docs/blockDocs}/Blocks/Cropper.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/Dilation.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/EdgeDetector.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/Erosion.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/FaceDetector.html (94%) rename {blockDocs => docs/blockDocs}/Blocks/IMU.html (96%) rename {blockDocs => docs/blockDocs}/Blocks/ImageRead.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/MotorDriver.html (94%) rename {blockDocs => docs/blockDocs}/Blocks/Odometer.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/PID.html (94%) rename {blockDocs => docs/blockDocs}/Blocks/ROSCamera.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/Screen.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/Teleoperator.html (94%) rename {blockDocs => docs/blockDocs}/Blocks/Threshold.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/VideoStreamer.html (95%) rename {blockDocs => docs/blockDocs}/Blocks/utils.html (100%) rename {blockDocs => docs/blockDocs}/Blocks/utils/models.html (100%) create mode 100644 docs/blockDocs/assets/blur-usage.png create mode 100644 docs/blockDocs/assets/bulr-usage.png create mode 100644 docs/blockDocs/assets/lenna-blur.png create mode 100644 docs/blockDocs/assets/lenna.png rename {blockDocs => docs/blockDocs}/index.html (100%) create mode 100644 docs/blockDocs/search.js diff --git a/blockDocs/Blocks/Blur.html b/blockDocs/Blocks/Blur.html index 55d399f7..826a3c56 100644 --- a/blockDocs/Blocks/Blur.html +++ b/blockDocs/Blocks/Blur.html @@ -168,6 +168,22 @@

Block Description

Outputs the blurred image through the share_image() function

+ +
+

Example Usage

+ +

Output

+ + + + + + + + + +
NormalAfter Median Blur
+
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\n\n

Visual Circuit

\n\n

\"Contributors\"\n\"Forks\"\n\"Stargazers\"\n\"Issues\"\n\"License\"

\n\n

Visual Circuit is an open source tool to develop robotic applications. It aims to make developing applications for ROS and Gazebo simple and user friendly by its intuitive block-based interface. Users have the ablity to drag and drop blocks to develop their logic. Users are also able to build completely custom blocks as well as edit code in the existing blocks, this makes Visual Circuit a robust and powerful tool to develop even complicated applications.

\n\n

For more information visit our site VisualCircuit

\n\n

Setup

\n\n

Front-end

\n\n

For more specific instructions check the frontend readme

\n\n
    \n
  1. Clone the repository https://github.com/JdeRobot/VisualCircuit.git
    2. \n
  2. Change directory to frontend
    3. \n
  3. Run npm install
    4. \n
  4. Run npm start
    5. \n
  5. Open http://localhost:3000/ in browser.
    6. \n
\n\n

Back-end

\n\n

For more specific instructions check the backend readme

\n\n
    \n
  1. Clone the repository https://github.com/JdeRobot/VisualCircuit.git
    2. \n
  2. Change directory to backend
    3. \n
  3. Create a Python3 virtual environment using venv. \nFor eg. python -m venv .venv
    4. \n
  4. After activating the virtual environment, install the dependencies by running\npip install -r requirements.txt
    5. \n
  5. Add .env file to the backend folder. And add the variables as defined in .env.template
    6. \n
  6. Create the static files to serve during execution by python manage.py collectstatic
    7. \n
  7. Start the server by running python manage.py runserver 8000
    8. \n
\n\n\n\n

Contributing

\n\n

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. For more info on how to design a block, refer to this link

\n\n

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag \"enhancement\".\nDon't forget to give the project a star! Thanks again!

\n\n
    \n
  1. Fork the Project
    2. \n
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
    3. \n
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
    4. \n
  4. Push to the Branch (git push origin feature/AmazingFeature)
    5. \n
  5. Open a Pull Request
    6. \n
\n\n

\n

\n"}, "Blocks.Blur": {"fullname": "Blocks.Blur", "modulename": "Blocks.Blur", "type": "module", "doc": "

\n"}, "Blocks.Blur.main": {"fullname": "Blocks.Blur.main", "modulename": "Blocks.Blur", "qualname": "main", "type": "function", "doc": "

Blurs an Object

\n\n

The object to be blurred is read through the inputs.\nWe have multiple available blurs including Gaussian, Averaging and Median Blur. \nWe can change these blurs by changing the name given in the parameter block

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.

\n\n

Outputs the blurred image through the share_image() function

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Camera": {"fullname": "Blocks.Camera", "modulename": "Blocks.Camera", "type": "module", "doc": "

\n"}, "Blocks.Camera.main": {"fullname": "Blocks.Camera.main", "modulename": "Blocks.Camera", "qualname": "main", "type": "function", "doc": "

Opens your Camera using OpenCV

\n\n

The Camera block opens your webcam using OpenCV and begins capturing the video feed.\nThis video feed is then propagated forward through the share_image() function

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ColorFilter": {"fullname": "Blocks.ColorFilter", "modulename": "Blocks.ColorFilter", "type": "module", "doc": "

\n"}, "Blocks.ColorFilter.main": {"fullname": "Blocks.ColorFilter.main", "modulename": "Blocks.ColorFilter", "qualname": "main", "type": "function", "doc": "

Filters Colour according to given parameters

\n\n

The image to be filtered is read through the inputs.\nWe can give a Filter between any HSV range by changing the range of the parameters LowerRGB and UpperRGB.

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire .

\n\n

Here the image is tranformed from BGR to HSV and then the filter is applied through the cv2.inRange()\nfunction. Finally the filtered image is overlayed on the orignal by the means of the\ncv2.bitwise_and() function. This filtered image is then shared through the share_image() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ContourDetector": {"fullname": "Blocks.ContourDetector", "modulename": "Blocks.ContourDetector", "type": "module", "doc": "

\n"}, "Blocks.ContourDetector.main": {"fullname": "Blocks.ContourDetector.main", "modulename": "Blocks.ContourDetector", "qualname": "main", "type": "function", "doc": "

Detects Contours in an Image

\n\n

The image in which contours are to be detected is read through the inputs.\nFirst the image is converted from BGR to Grayscale, the thresholding values are 60, 255.\nThe function used is cv2.threshold().\nOnce it is thersholded, the contours are detected in the image using cv2.findContours()

\n\n

The program then detects the biggest contour present in the image and finds the co-ordinates of its center\nusing the cv2.moments() function.

\n\n

This co-ords of the center alongwith the contour characteristics are part of the output array.\nTHis array is shared through share_array()

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.

\n\n

Further reading

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Cropper": {"fullname": "Blocks.Cropper", "modulename": "Blocks.Cropper", "type": "module", "doc": "

\n"}, "Blocks.Cropper.main": {"fullname": "Blocks.Cropper.main", "modulename": "Blocks.Cropper", "qualname": "main", "type": "function", "doc": "

Crops an Image

\n\n

The image which is to be cropped is read through the inputs using the inputs.read_image() function.\nThe parameters ask for x, y, w, h

\n\n
x: x co-ordinate of where the crop should start\n\ny: y co-ordinate of where the crop should start\n\nw: width of the crop\n\nh: height of the crop\n\n
\n\n

Image is cropped by simple list slicing.

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.\nOutput is shared via share_image()

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Dilation": {"fullname": "Blocks.Dilation", "modulename": "Blocks.Dilation", "type": "module", "doc": "

\n"}, "Blocks.Dilation.main": {"fullname": "Blocks.Dilation.main", "modulename": "Blocks.Dilation", "qualname": "main", "type": "function", "doc": "

Dilates an Image

\n\n

You can specify the kernel dimensions and number of iterations in the parameters.

\n\n

We first convert the colour of the image from BGR to GRAY then we apply dilation on it \nusing the cv2.dilate() function.

\n\n

Finaly we convert from GRAY back to BGR and output the image through the share_image() function.

\n\n

Further reading

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.EdgeDetector": {"fullname": "Blocks.EdgeDetector", "modulename": "Blocks.EdgeDetector", "type": "module", "doc": "

\n"}, "Blocks.EdgeDetector.main": {"fullname": "Blocks.EdgeDetector.main", "modulename": "Blocks.EdgeDetector", "qualname": "main", "type": "function", "doc": "

Detects Edges in an Image

\n\n

It takes in two parameters Lower and Upper. These parameters are used as the limits in Canny Edge \nDetection. First we convert the input BGR image to GRAY. Next we apply Canny Edge Detection via the \ncv2.Canny() function. The resulting image is then converted back to BGR.

\n\n

This image is then shared to the wire via the share_image() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Erosion": {"fullname": "Blocks.Erosion", "modulename": "Blocks.Erosion", "type": "module", "doc": "

\n"}, "Blocks.Erosion.main": {"fullname": "Blocks.Erosion.main", "modulename": "Blocks.Erosion", "qualname": "main", "type": "function", "doc": "

Erodes an Image

\n\n

You can specify the kernel dimensions and number of iterations in the parameters.

\n\n

We first convert the colour of the image from BGR to GRAY then we apply erosion on it \nusing the cv2.erode() function.

\n\n

Finaly we convert from GRAY back to BGR and output the image through the share_image() function.

\n\n

Further reading

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.FaceDetector": {"fullname": "Blocks.FaceDetector", "modulename": "Blocks.FaceDetector", "type": "module", "doc": "

\n"}, "Blocks.FaceDetector.main": {"fullname": "Blocks.FaceDetector.main", "modulename": "Blocks.FaceDetector", "qualname": "main", "type": "function", "doc": "

Detects Faces in the Image

\n\n

This block applies a Harr Cascade based model on the input image. \nIt takes as an input the parameter BoxOrImage. This parameter has two possible values:\nBoxOrImage: image / box

\n\n

If image is given: The output is the image passed in with a bounding box around the area where \na face is detected. Image is shared through the share_image() function.

\n\n

Else if box is given, the output is the co-ordinates of the bounding box in the form of an array. It \nis chared through the share_array() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.IMU": {"fullname": "Blocks.IMU", "modulename": "Blocks.IMU", "type": "module", "doc": "

\n"}, "Blocks.IMU.callback": {"fullname": "Blocks.IMU.callback", "modulename": "Blocks.IMU", "qualname": "callback", "type": "function", "doc": "

The callback function is required by the Subscriber to the ROSTopic. This callback function reads the orientation list from the IMU\nIt then converts the quaternion angles to euler ones. This gives us the roll, pitch and yaw of the body.\nWe convert these radian values to degrees to get the orientation of the body.

\n\n

Aside from these values the IMU also gives us the angular velocity of the body.

\n\n

All of these values are stored in the global data variable of the block.

\n", "signature": "(msg)", "funcdef": "def"}, "Blocks.IMU.main": {"fullname": "Blocks.IMU.main", "modulename": "Blocks.IMU", "qualname": "main", "type": "function", "doc": "

Reads IMU sensor data

\n\n

This is a specialized block used to read IMU sensor data.

\n\n

It reads the ROSTopic name from the ROSTopic parameter. Default is mavros/imu/data.

\n\n

This data is sent to the callback function which converts the orientation list obtained into roll, pitch and yaw for the\nrobot that the IMU is present on. Alongwith orientation, it also gives the angular velocity of the robot.\nThis data is shared in the form of an array using the share_array() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ImageRead": {"fullname": "Blocks.ImageRead", "modulename": "Blocks.ImageRead", "type": "module", "doc": "

\n"}, "Blocks.ImageRead.main": {"fullname": "Blocks.ImageRead.main", "modulename": "Blocks.ImageRead", "qualname": "main", "type": "function", "doc": "

Reads an Image from a Specified Path

\n\n

This box reads an image from a given file path. The path to be specified is written in the parameter\nImagePath.

\n\n

It is read through the cv2.imread() function and shared through the share_image() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.MotorDriver": {"fullname": "Blocks.MotorDriver", "modulename": "Blocks.MotorDriver", "type": "module", "doc": "

\n"}, "Blocks.MotorDriver.callback": {"fullname": "Blocks.MotorDriver.callback", "modulename": "Blocks.MotorDriver", "qualname": "callback", "type": "function", "doc": "

\n", "signature": "(inp)", "funcdef": "def"}, "Blocks.MotorDriver.main": {"fullname": "Blocks.MotorDriver.main", "modulename": "Blocks.MotorDriver", "qualname": "main", "type": "function", "doc": "

Publishes Twist Command to drive Motors

\n\n

It publishes to the ROSTopic name from the ROSTopic parameter. Default is /robot/cmd_vel.

\n\n

It reads an array as an input by the read_array() function.

\n\n

This is assumed to be of the format [ linear_velocity, angular_velocity ].

\n\n

This data is then converted into a Twist() message with the linear.x = linear_velocity and angular.z = angular_velocity

\n\n

The data is then published continuously

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Odometer": {"fullname": "Blocks.Odometer", "modulename": "Blocks.Odometer", "type": "module", "doc": "

\n"}, "Blocks.Odometer.callback": {"fullname": "Blocks.Odometer.callback", "modulename": "Blocks.Odometer", "qualname": "callback", "type": "function", "doc": "

\n", "signature": "(msg)", "funcdef": "def"}, "Blocks.Odometer.main": {"fullname": "Blocks.Odometer.main", "modulename": "Blocks.Odometer", "qualname": "main", "type": "function", "doc": "

Reads Data from An Odometer

\n\n

It reads the ROSTopic name from the ROSTopic parameter.\nIt then initializes a Subscriber to subscribe to that ROSTopic, once the data is obtained through the callback\nfunction, it is formatted into an array with the format: [ x, y, yaw ]

\n\n

This data is then shared to the wire using the share_array() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.PID": {"fullname": "Blocks.PID", "modulename": "Blocks.PID", "type": "module", "doc": "

\n"}, "Blocks.PID.main": {"fullname": "Blocks.PID.main", "modulename": "Blocks.PID", "qualname": "main", "type": "function", "doc": "

Applies PID for a Given Error Value

\n\n

The error is read as an input from the inputs wire.

\n\n

The Kp, Ki, and Kd parameters are read from the parameters of the same name.\nOnce there it applies the PID technique to the error variable in order to minimize it.

\n\n

The resulting values are shared through the share_array() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ROSCamera": {"fullname": "Blocks.ROSCamera", "modulename": "Blocks.ROSCamera", "type": "module", "doc": "

\n"}, "Blocks.ROSCamera.callback": {"fullname": "Blocks.ROSCamera.callback", "modulename": "Blocks.ROSCamera", "qualname": "callback", "type": "function", "doc": "

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Gets Image from a ROSCamera

\n\n

The camera topic is read from the ROSTopic parameter, by default it is /robot/camera

\n\n

The image message is converted to OpenCV compatible format via the imgmsg_to_cv2() function.

\n\n

This is then shared ahead using the share_image() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Screen": {"fullname": "Blocks.Screen", "modulename": "Blocks.Screen", "type": "module", "doc": "

\n"}, "Blocks.Screen.main": {"fullname": "Blocks.Screen.main", "modulename": "Blocks.Screen", "qualname": "main", "type": "function", "doc": "

Displays the given Image

\n\n

Takes an image as an input and displays it on the user's screen.\nThe cv2.imshow() function is used in order to display the image.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Teleoperator": {"fullname": "Blocks.Teleoperator", "modulename": "Blocks.Teleoperator", "type": "module", "doc": "

\n"}, "Blocks.Teleoperator.main": {"fullname": "Blocks.Teleoperator.main", "modulename": "Blocks.Teleoperator", "qualname": "main", "type": "function", "doc": "

Used to Imitate the Movements of the Operator

\n\n

It takes in an array as input, depending on the array variables, it will output another array\ncontaining the velocity it deems appropriate.\nThe linear_velocity can be given via the Linear parameter.

\n\n

The output data is a list of the format: [ linear_velocity, angular_velocity ]

\n\n

This is then shared to the output wire using the share_array() function.

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Threshold": {"fullname": "Blocks.Threshold", "modulename": "Blocks.Threshold", "type": "module", "doc": "

\n"}, "Blocks.Threshold.main": {"fullname": "Blocks.Threshold.main", "modulename": "Blocks.Threshold", "qualname": "main", "type": "function", "doc": "

Thresholds an Image

\n\n

THis block reads the parameters LowerThreshold and UpperThreshold.

\n\n

Based on these values it converts the input image form BGR into GRAY and applies the cv2.threshold() function on it.

\n\n

The image is then converted back into BGR and shared to the output wire using the\nshare_image() function.

\n\n

Further reading

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.VideoStreamer": {"fullname": "Blocks.VideoStreamer", "modulename": "Blocks.VideoStreamer", "type": "module", "doc": "

\n"}, "Blocks.VideoStreamer.main": {"fullname": "Blocks.VideoStreamer.main", "modulename": "Blocks.VideoStreamer", "qualname": "main", "type": "function", "doc": "

Streams Video from File

\n\n

The filepath of your video is given in the PathToFile parameter.\nNote: that this file path is relative to the modules folder of the final built application.

\n\n

Capturing begins using the cv2.VideoCapture() function. \nThe video is then read frame by frame and each frame is shared to the output wire using the\nshare_image() function.

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"df": 0, "r": {"docs": {}, "df": 0, "n": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "l": {"docs": {"Blocks.Dilation.main": {"tf": 1}, "Blocks.Erosion.main": {"tf": 1}}, "df": 2}}}}}, "p": {"docs": {"Blocks.PID.main": {"tf": 1}}, "df": 1}, "i": {"docs": {"Blocks.PID.main": {"tf": 1}}, "df": 1}, "d": {"docs": {"Blocks.PID.main": {"tf": 1}}, "df": 1}}, "q": {"docs": {}, "df": 0, "u": {"docs": {}, "df": 0, "a": {"docs": {}, "df": 0, "t": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "r": {"docs": {}, "df": 0, "n": {"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "o": {"docs": {}, "df": 0, "n": {"docs": {"Blocks.IMU.callback": {"tf": 1}}, "df": 1}}}}}}}}}}, "z": {"docs": {"Blocks.MotorDriver.main": {"tf": 1}}, "df": 1}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; - - // mirrored in build-search-index.js (part 1) - // Also split on html tags. this is a cheap heuristic, but good enough. - elasticlunr.tokenizer.setSeperator(/[\s\-.;&_'"=,()]+|<[^>]*>/); - - let searchIndex; - if (docs._isPrebuiltIndex) { - console.info("using precompiled search index"); - searchIndex = elasticlunr.Index.load(docs); - } else { - console.time("building search index"); - // mirrored in build-search-index.js (part 2) - searchIndex = elasticlunr(function () { - this.pipeline.remove(elasticlunr.stemmer); - this.pipeline.remove(elasticlunr.stopWordFilter); - this.addField("qualname"); - this.addField("fullname"); - this.addField("annotation"); - this.addField("default_value"); - this.addField("signature"); - this.addField("bases"); - this.addField("doc"); - this.setRef("fullname"); - }); - for (let doc of docs) { - searchIndex.addDoc(doc); - } - console.timeEnd("building search index"); - } - - return (term) => searchIndex.search(term, { - fields: { - qualname: {boost: 4}, - fullname: {boost: 2}, - annotation: {boost: 2}, - default_value: {boost: 2}, - signature: {boost: 2}, - bases: {boost: 2}, - doc: {boost: 1}, - }, - expand: true - }); -})(); \ No newline at end of file diff --git a/Blocks/Blur.py b/docs/Blocks/Blur.py similarity index 94% rename from Blocks/Blur.py rename to docs/Blocks/Blur.py index 43070b9c..14c577b7 100644 --- a/Blocks/Blur.py +++ b/docs/Blocks/Blur.py @@ -12,6 +12,12 @@ def main(inputs, outputs, parameters, synchronise): It is enabled by default but can be disabled by passing in 0 through the enable wire. Outputs the blurred image through the `share_image()` function + + **Inputs**: BGR Image + + **Outputs**: BGR Image + + **Parameters**: BlurType """ # Blur Type blur_type : str = parameters.read_string("BlurType") diff --git a/Blocks/Camera.py b/docs/Blocks/Camera.py similarity index 92% rename from Blocks/Camera.py rename to docs/Blocks/Camera.py index 0e0c713b..e4237f2f 100644 --- a/Blocks/Camera.py +++ b/docs/Blocks/Camera.py @@ -9,6 +9,12 @@ def main(inputs, outputs, parameters, synchronise): `while` loop is the part of the program that is executed continuously. It is enabled by default but can be disabled by passing in 0 through the enable wire. + + **Inputs**: None + + **Outputs**: BGR Image + + **Parameters**: None ''' cap = cv2.VideoCapture(0) auto_enable = False diff --git a/Blocks/ColorFilter.py b/docs/Blocks/ColorFilter.py similarity index 93% rename from Blocks/ColorFilter.py rename to docs/Blocks/ColorFilter.py index 05a2846e..8ce81f92 100644 --- a/Blocks/ColorFilter.py +++ b/docs/Blocks/ColorFilter.py @@ -13,6 +13,12 @@ def main(inputs, outputs, parameters, synchronise): Here the image is tranformed from `BGR` to `HSV` and then the filter is applied through the `cv2.inRange()` function. Finally the filtered image is overlayed on the orignal by the means of the `cv2.bitwise_and()` function. This filtered image is then shared through the `share_image()` function. + + **Inputs**: BGR Image + + **Outputs**: BGR Image + + **Parameters**: LowerHSV, UpperHSV ''' lower_rgb = np.array([int(x.strip()) for x in parameters.read_string('LowerRGB').split(',')]) upper_rgb = np.array([int(x.strip()) for x in parameters.read_string('UpperRGB').split(',')]) diff --git a/Blocks/ContourDetector.py b/docs/Blocks/ContourDetector.py similarity index 94% rename from Blocks/ContourDetector.py rename to docs/Blocks/ContourDetector.py index f8fb1d14..27f446ff 100644 --- a/Blocks/ContourDetector.py +++ b/docs/Blocks/ContourDetector.py @@ -19,6 +19,12 @@ def main(inputs, outputs, parameters, synchronise): It is enabled by default but can be disabled by passing in 0 through the enable wire. [Further reading](https://docs.opencv.org/4.x/d4/d73/tutorial_py_contours_begin.html) + + **Inputs**: BGR Image + + **Outputs**: Array [x, y, width, height, angle of rotation], BGR Image + + **Parameters**: None ''' auto_enable = False try: diff --git a/Blocks/Cropper.py b/docs/Blocks/Cropper.py similarity index 92% rename from Blocks/Cropper.py rename to docs/Blocks/Cropper.py index 00eed4b7..dc73ed5e 100644 --- a/Blocks/Cropper.py +++ b/docs/Blocks/Cropper.py @@ -16,6 +16,12 @@ def main(inputs, outputs, parameters, synchronise): `while` loop is the part of the program that is executed continuously. It is enabled by default but can be disabled by passing in 0 through the enable wire. Output is shared via `share_image()` + + **Inputs**: BGR Image + + **Outputs**: Resized BGR Image + + **Parameters**: x, y, width, height ''' x, y, w, h = np.array([int(x.strip()) for x in parameters.read_string("xywh").split(",")]) diff --git a/Blocks/Dilation.py b/docs/Blocks/Dilation.py similarity index 93% rename from Blocks/Dilation.py rename to docs/Blocks/Dilation.py index 1522d5e1..59057951 100644 --- a/Blocks/Dilation.py +++ b/docs/Blocks/Dilation.py @@ -11,6 +11,12 @@ def main(inputs, outputs, parameters, synchronise): Finaly we convert from `GRAY` back to `BGR` and output the image through the `share_image()` function. [Further reading](https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html) + + **Inputs**: BGR Image + + **Outputs**: BGR Image + + **Parameters**: Kernel, Iterations ''' kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) kernel = np.ones(kernel, np.uint8) diff --git a/Blocks/EdgeDetector.py b/docs/Blocks/EdgeDetector.py similarity index 90% rename from Blocks/EdgeDetector.py rename to docs/Blocks/EdgeDetector.py index f20744dc..1844d03f 100644 --- a/Blocks/EdgeDetector.py +++ b/docs/Blocks/EdgeDetector.py @@ -9,6 +9,12 @@ def main(inputs, outputs, parameters, synchronise): `cv2.Canny()` function. The resulting image is then converted back to `BGR`. This image is then shared to the wire via the `share_image()` function. + + **Inputs**: BGR Image + + **Outputs**: BGR Image + + **Parameters**: Lower, Upper (Threshold values) ''' lower = int(parameters.read_string("Lower")) upper = int(parameters.read_string("Upper")) diff --git a/Blocks/Erosion.py b/docs/Blocks/Erosion.py similarity index 92% rename from Blocks/Erosion.py rename to docs/Blocks/Erosion.py index 97e19d88..3d6196b7 100644 --- a/Blocks/Erosion.py +++ b/docs/Blocks/Erosion.py @@ -11,6 +11,12 @@ def main(inputs, outputs, parameters, synchronise): Finaly we convert from `GRAY` back to `BGR` and output the image through the `share_image()` function. [Further reading]([Further reading](https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html)) + + **Inputs**: BGR Image + + **Outputs**: BGR Image + + **Parameters**: Kernel, Iterations ''' kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) kernel = np.ones(kernel, np.uint8) diff --git a/Blocks/FaceDetector.py b/docs/Blocks/FaceDetector.py similarity index 90% rename from Blocks/FaceDetector.py rename to docs/Blocks/FaceDetector.py index 2fac7fab..9e1242b6 100644 --- a/Blocks/FaceDetector.py +++ b/docs/Blocks/FaceDetector.py @@ -11,6 +11,12 @@ def main(inputs, outputs, parameters, synchronise): a face is detected. Image is shared through the `share_image()` function.\n Else if `box` is given, the output is the co-ordinates of the bounding box in the form of an array. It is chared through the `share_array()` function. + + **Inputs**: BGR Image + + **Outputs**: BGR Image with Bounding Boxes + + **Parameters**: BoxOrImage ('box' for Bounding Boxes, 'image' for Image with Detections) ''' choice = parameters.read_string("BoxOrImage") diff --git a/Blocks/IMU.py b/docs/Blocks/IMU.py similarity index 90% rename from Blocks/IMU.py rename to docs/Blocks/IMU.py index 3bd36e3c..de9ffd43 100644 --- a/Blocks/IMU.py +++ b/docs/Blocks/IMU.py @@ -13,7 +13,7 @@ def callback(msg): We convert these radian values to degrees to get the orientation of the body. Aside from these values the IMU also gives us the angular velocity of the body.\n - All of these values are stored in the global data variable of the block. + All of these values are stored in the global `data` variable of the block. ''' global data # Get the orientation list from the IMU sensor @@ -40,6 +40,12 @@ def main(inputs, outputs, parameters, synchronise): This data is sent to the callback function which converts the orientation list obtained into roll, pitch and yaw for the robot that the IMU is present on. Alongwith orientation, it also gives the angular velocity of the robot. This data is shared in the form of an array using the `share_array()` function. + + **Inputs**: None + + **Outputs**: Array [Roll, Pitch , Yaw, Angular Velocity in X, Angular Velocity in Y, Angular Velocity in Z] + + **Parameters**: ROSTopic ''' global data auto_enable = False diff --git a/Blocks/ImageRead.py b/docs/Blocks/ImageRead.py similarity index 89% rename from Blocks/ImageRead.py rename to docs/Blocks/ImageRead.py index 9573bb36..a7878219 100644 --- a/Blocks/ImageRead.py +++ b/docs/Blocks/ImageRead.py @@ -7,6 +7,12 @@ def main(inputs, outputs, parameters, synchronise): This box reads an image from a given file path. The path to be specified is written in the parameter `ImagePath`.\n It is read through the `cv2.imread()` function and shared through the `share_image()` function. + + **Inputs**: None + + **Outputs**: BGR Image + + **Parameters**: ImagePath ''' path = parameters.read_string("ImagePath") image = cv2.imread(path) diff --git a/Blocks/MotorDriver.py b/docs/Blocks/MotorDriver.py similarity index 93% rename from Blocks/MotorDriver.py rename to docs/Blocks/MotorDriver.py index 4ec766e8..0b2890e2 100644 --- a/Blocks/MotorDriver.py +++ b/docs/Blocks/MotorDriver.py @@ -18,6 +18,12 @@ def main(inputs, outputs, parameters, synchronise): This data is then converted into a Twist() message with the `linear.x = linear_velocity` and `angular.z = angular_velocity` The data is then published continuously + + **Inputs**: `cmd_vel` (Linear Velocity, Angular Velocity) + + **Outputs**: None + + **Parameters**: ROSTopic ''' rospy.init_node("motordriverVC", anonymous=True) diff --git a/Blocks/ObjectDetector.py b/docs/Blocks/ObjectDetector.py similarity index 96% rename from Blocks/ObjectDetector.py rename to docs/Blocks/ObjectDetector.py index cd8f70eb..38cccbc7 100644 --- a/Blocks/ObjectDetector.py +++ b/docs/Blocks/ObjectDetector.py @@ -54,6 +54,12 @@ def main(inputs, outputs, parameters, synchronise): tag to it, a bounding box is also drawn over it. This image is then shared to the output wire using the `share_image()` function. + + **Inputs**: BGR Image + + **Outputs**: BGR Image with Bounding Boxes + + **Parameters**: None ''' auto_enable = True try: diff --git a/Blocks/Odometer.py b/docs/Blocks/Odometer.py similarity index 92% rename from Blocks/Odometer.py rename to docs/Blocks/Odometer.py index 8dd3622b..df6fb181 100644 --- a/Blocks/Odometer.py +++ b/docs/Blocks/Odometer.py @@ -17,6 +17,12 @@ def main(inputs, outputs, parameters, synchronise): It then initializes a Subscriber to subscribe to that ROSTopic, once the data is obtained through the callback function, it is formatted into an array with the format: `[ x, y, yaw ]`\n This data is then shared to the wire using the `share_array()` function. + + **Inputs**: None + + **Outputs**: Array [X, Y, Yaw] + + **Parameters**: ROSTopic ''' rospy.init_node("odometerVC", anonymous=True) rostopic_name = parameters.read_string("ROSTopic") diff --git a/Blocks/PID.py b/docs/Blocks/PID.py similarity index 91% rename from Blocks/PID.py rename to docs/Blocks/PID.py index 50190ee6..10b2a80c 100644 --- a/Blocks/PID.py +++ b/docs/Blocks/PID.py @@ -10,6 +10,12 @@ def main(inputs, outputs, parameters, synchronise): Once there it applies the PID technique to the error variable in order to minimize it. The resulting values are shared through the `share_array()` function. + + **Inputs**: Error + + **Outputs**: `cmd_vel` (Linear Velocity, Angular Velocity) + + **Parameters**: Kp, Ki, Kd ''' auto_enable = True try: diff --git a/Blocks/ROSCamera.py b/docs/Blocks/ROSCamera.py similarity index 93% rename from Blocks/ROSCamera.py rename to docs/Blocks/ROSCamera.py index 2475e07b..666dc7f0 100644 --- a/Blocks/ROSCamera.py +++ b/docs/Blocks/ROSCamera.py @@ -18,6 +18,12 @@ def main(inputs, outputs, parameters, synchronise): The image message is converted to OpenCV compatible format via the `imgmsg_to_cv2()` function. This is then shared ahead using the `share_image()` function. + + **Inputs**: None + + **Outputs**: BGR Image + + **Parameters**: ROSTopic ''' auto_enable = False try: diff --git a/Blocks/Screen.py b/docs/Blocks/Screen.py similarity index 88% rename from Blocks/Screen.py rename to docs/Blocks/Screen.py index f434e1a9..19183b88 100644 --- a/Blocks/Screen.py +++ b/docs/Blocks/Screen.py @@ -6,6 +6,12 @@ def main(inputs, outputs, parameters, synchronise): Takes an image as an input and displays it on the user's screen. The `cv2.imshow()` function is used in order to display the image. + + **Inputs**: BGR Image + + **Outputs**: None + + **Parameters**: None ''' auto_enable = False try: diff --git a/Blocks/Teleoperator.py b/docs/Blocks/Teleoperator.py similarity index 88% rename from Blocks/Teleoperator.py rename to docs/Blocks/Teleoperator.py index 8dc4dd80..11dcdaeb 100644 --- a/Blocks/Teleoperator.py +++ b/docs/Blocks/Teleoperator.py @@ -9,6 +9,12 @@ def main(inputs, outputs, parameters, synchronise): The output data is a list of the format: `[ linear_velocity, angular_velocity ]`\n This is then shared to the output wire using the `share_array()` function. + + **Inputs**: Bounding Box (x, y, width, height) + + **Outputs**: `cmd_vel` (linear velocity, angular velocity) + + **Parameters**: Linear(Linear Velocity) ''' auto_enable = True try: diff --git a/Blocks/Threshold.py b/docs/Blocks/Threshold.py similarity index 91% rename from Blocks/Threshold.py rename to docs/Blocks/Threshold.py index 72dc27ed..e7029b5e 100644 --- a/Blocks/Threshold.py +++ b/docs/Blocks/Threshold.py @@ -11,6 +11,12 @@ def main(inputs, outputs, parameters, synchronise): `share_image()` function. [Further reading](https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html) + + **Inputs**: BGR Image + + **Outputs**: BGR Image + + **Parameters**: LowerThreshold, UpperThreshold ''' lower = parameters.read_number("LowerThreshold") upper = parameters.read_number("UpperThreshold") diff --git a/Blocks/VideoStreamer.py b/docs/Blocks/VideoStreamer.py similarity index 91% rename from Blocks/VideoStreamer.py rename to docs/Blocks/VideoStreamer.py index 969274fa..e5da5f31 100644 --- a/Blocks/VideoStreamer.py +++ b/docs/Blocks/VideoStreamer.py @@ -10,6 +10,12 @@ def main(inputs, outputs, parameters, synchronise): Capturing begins using the `cv2.VideoCapture()` function. The video is then read frame by frame and each frame is shared to the output wire using the `share_image()` function. + + **Inputs**: None + + **Outputs**: BGR Image + + **Parameters**: PathToFile ''' filepath = parameters.read_string("PathToFile") auto_enable = False diff --git a/Blocks/__init__.py b/docs/Blocks/__init__.py similarity index 100% rename from Blocks/__init__.py rename to docs/Blocks/__init__.py diff --git a/Blocks/module.html.jinja2 b/docs/Blocks/module.html.jinja2 similarity index 99% rename from Blocks/module.html.jinja2 rename to docs/Blocks/module.html.jinja2 index 7651c0d5..365f0f98 100644 --- a/Blocks/module.html.jinja2 +++ b/docs/Blocks/module.html.jinja2 @@ -25,7 +25,7 @@ } %} -{% set parent = 'docCode' %} +{% set parent = 'Blocks' %} {% block body %} {% set currentblock = module.modulename.split(".")[-1].replace("%20", "") %} diff --git a/Blocks/utils/__init__.py b/docs/Blocks/utils/__init__.py similarity index 100% rename from Blocks/utils/__init__.py rename to docs/Blocks/utils/__init__.py diff --git a/Blocks/utils/models/__init__.py b/docs/Blocks/utils/models/__init__.py similarity index 100% rename from Blocks/utils/models/__init__.py rename to docs/Blocks/utils/models/__init__.py diff --git a/Blocks/utils/models/haar_cascade/haarcascade_frontalface_default.xml b/docs/Blocks/utils/models/haar_cascade/haarcascade_frontalface_default.xml similarity index 100% rename from Blocks/utils/models/haar_cascade/haarcascade_frontalface_default.xml rename to docs/Blocks/utils/models/haar_cascade/haarcascade_frontalface_default.xml diff --git a/Blocks/utils/models/yolov3/yolov3-tiny.cfg b/docs/Blocks/utils/models/yolov3/yolov3-tiny.cfg similarity index 100% rename from Blocks/utils/models/yolov3/yolov3-tiny.cfg rename to docs/Blocks/utils/models/yolov3/yolov3-tiny.cfg diff --git a/Blocks/utils/models/yolov3/yolov3-tiny.weights b/docs/Blocks/utils/models/yolov3/yolov3-tiny.weights similarity index 100% rename from Blocks/utils/models/yolov3/yolov3-tiny.weights rename to docs/Blocks/utils/models/yolov3/yolov3-tiny.weights diff --git a/Blocks/utils/models/yolov3/yolov3.txt b/docs/Blocks/utils/models/yolov3/yolov3.txt similarity index 100% rename from Blocks/utils/models/yolov3/yolov3.txt rename to docs/Blocks/utils/models/yolov3/yolov3.txt diff --git a/docs/_pages/documentation.md b/docs/_pages/documentation.md index d6ec1ad2..27ff9e77 100644 --- a/docs/_pages/documentation.md +++ b/docs/_pages/documentation.md @@ -13,6 +13,9 @@ sidebar: ## Project +### New Documentation +To access the new documentation, visit this link. [Visual Circuit 3.x Block Documentation](/blockDocs/index.html) + ### Definition Version: 1.0. diff --git a/blockDocs/Blocks.html b/docs/blockDocs/Blocks.html similarity index 89% rename from blockDocs/Blocks.html rename to docs/blockDocs/Blocks.html index 5271d91e..3c48ebd4 100644 --- a/blockDocs/Blocks.html +++ b/docs/blockDocs/Blocks.html @@ -25,10 +25,12 @@

Contents

@@ -71,71 +73,59 @@

Submodules

Blocks

-
+

Jekyll Local Installation

-

+

Prerequisites

-

Visual Circuit

+

Installing Ruby on Ubuntu

-

Contributors -Forks -Stargazers -Issues -License

+

First of all, we need to install all the dependencies typing:

-

Visual Circuit is an open source tool to develop robotic applications. It aims to make developing applications for ROS and Gazebo simple and user friendly by its intuitive block-based interface. Users have the ablity to drag and drop blocks to develop their logic. Users are also able to build completely custom blocks as well as edit code in the existing blocks, this makes Visual Circuit a robust and powerful tool to develop even complicated applications.

+
sudo apt-get install ruby-full build-essential zlib1g-dev
+
-

For more information visit our site VisualCircuit

+

After that, we need to set up a gem installation directory for your user account. The following commands will add environment variables to your ~/.bashrc file to configure the gem installation path. Run them now:

-

Setup

+
echo '# Install Ruby Gems to ~/gems' >> ~/.bashrc
+echo 'export GEM_HOME="$HOME/gems"' >> ~/.bashrc
+echo 'export PATH="$HOME/gems/bin:$PATH"' >> ~/.bashrc
+source ~/.bashrc
+
-

Front-end

+

Finally, we install Jekyll:

-

For more specific instructions check the frontend readme

+
gem install jekyll bundler
+
-
    -
  1. Clone the repository https://github.com/JdeRobot/VisualCircuit.git
    2. -
  2. Change directory to frontend
    3. -
  3. Run npm install
    4. -
  4. Run npm start
    5. -
  5. Open http://localhost:3000/ in browser.
    6. -
+

Notice that we don't use the root user :-)

-

Back-end

+

Installing Ruby and Jekyll on Mac OS X

-

For more specific instructions check the backend readme

+

Follow the Jekyll page installation guide.

-
    -
  1. Clone the repository https://github.com/JdeRobot/VisualCircuit.git
    2. -
  2. Change directory to backend
    3. -
  3. Create a Python3 virtual environment using venv. -For eg. python -m venv .venv
    4. -
  4. After activating the virtual environment, install the dependencies by running -pip install -r requirements.txt
    5. -
  5. Add .env file to the backend folder. And add the variables as defined in .env.template
    6. -
  6. Create the static files to serve during execution by python manage.py collectstatic
    7. -
  7. Start the server by running python manage.py runserver 8000
    8. -
+

Running Jekyll Serve

- +

By default, the Jekyll server is launched with the following command (which is the one indicated on your website).

-

Contributing

+
bundle exec jekyll serve
+
-

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. For more info on how to design a block, refer to this link

+

If in the process of building the server there is a dependency problem, for example, there is a missing library to install, it is necessary to delete the Gemfile.lock file so that it is rebuilt with the installed dependency. This list of dependencies is found in the Gemfile file (in Python it would be equivalent to the requirements.txt file) and the version of each of the installed gems (packages) is specified. Having a list of dependencies is important for future updates as well as knowing the libraries needed to run the server. Once the Gemfile.lock file is deleted, the command shown above is launched again and the dependency errors should end.

-

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". -Don't forget to give the project a star! Thanks again!

+

Notes for exercise cards.

-
    -
  1. Fork the Project
    2. -
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
    3. -
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
    4. -
  4. Push to the Branch (git push origin feature/AmazingFeature)
    5. -
  5. Open a Pull Request
    6. -
+
    +
  • Teaser Images size: multiple of 600x400px
    • +
+ +

FAQ

+ +
    +
  • Error building Jekyll server:
    • +
-

-

+
jekyll build --incremental --verbose
+
diff --git a/docs/blockDocs/Blocks/Blur.html b/docs/blockDocs/Blocks/Blur.html new file mode 100644 index 00000000..7978bd08 --- /dev/null +++ b/docs/blockDocs/Blocks/Blur.html @@ -0,0 +1,390 @@ + + + + + + + Blocks.Blur API documentation + + + + + + + + + + + + +
+
+

+Blocks.Blur

+ + + + + + + 
 1import cv2
+ 2import numpy as np
+ 3
+ 4def main(inputs, outputs, parameters, synchronise):
+ 5    """
+ 6    ## Blurs an Object\n
+ 7    The object to be blurred is read through the inputs.
+ 8    We have multiple available blurs including Gaussian, Averaging and Median Blur. 
+ 9    We can change these blurs by changing the name given in the parameter block
+10
+11    `while` loop is the part of the program that is executed continuously.
+12    It is enabled by default but can be disabled by passing in 0 through the enable wire.
+13
+14    Outputs the blurred image through the `share_image()` function
+15
+16    **Inputs**: BGR Image
+17
+18    **Outputs**: BGR Image
+19
+20    **Parameters**: BlurType
+21    """
+22    # Blur Type
+23    blur_type : str = parameters.read_string("BlurType") 
+24    """Type of blur, reads from a parameter"""
+25    # Kernel Size
+26    kernel = tuple([int(x.strip()) for x in parameters.read_string("Kernel").split(',')])
+27    auto_enable = False
+28    try:
+29        enable = inputs.read_number("Enable")
+30    except Exception:
+31        auto_enable = True
+32
+33    while(auto_enable or inputs.read_number('Enable')):
+34        frame = inputs.read_image("Img")
+35        if frame is None:
+36            continue
+37
+38        if blur_type == 'Gaussian':
+39            blurred_img = cv2.GaussianBlur(frame, kernel, 0)
+40                        
+41        elif blur_type == 'Averaging':
+42            blurred_img = cv2.blur(frame, kernel)
+43                        
+44        elif blur_type == 'Median':
+45            blurred_img = cv2.medianBlur(frame, kernel[0])
+46
+47        outputs.share_image('Out', blurred_img)
+48        synchronise()
+
+ + +
+
+ +
+ + def + main(inputs, outputs, parameters, synchronise) + + + +
+ + 
 5def main(inputs, outputs, parameters, synchronise):
+ 6    """
+ 7    ## Blurs an Object\n
+ 8    The object to be blurred is read through the inputs.
+ 9    We have multiple available blurs including Gaussian, Averaging and Median Blur. 
+10    We can change these blurs by changing the name given in the parameter block
+11
+12    `while` loop is the part of the program that is executed continuously.
+13    It is enabled by default but can be disabled by passing in 0 through the enable wire.
+14
+15    Outputs the blurred image through the `share_image()` function
+16
+17    **Inputs**: BGR Image
+18
+19    **Outputs**: BGR Image
+20
+21    **Parameters**: BlurType
+22    """
+23    # Blur Type
+24    blur_type : str = parameters.read_string("BlurType") 
+25    """Type of blur, reads from a parameter"""
+26    # Kernel Size
+27    kernel = tuple([int(x.strip()) for x in parameters.read_string("Kernel").split(',')])
+28    auto_enable = False
+29    try:
+30        enable = inputs.read_number("Enable")
+31    except Exception:
+32        auto_enable = True
+33
+34    while(auto_enable or inputs.read_number('Enable')):
+35        frame = inputs.read_image("Img")
+36        if frame is None:
+37            continue
+38
+39        if blur_type == 'Gaussian':
+40            blurred_img = cv2.GaussianBlur(frame, kernel, 0)
+41                        
+42        elif blur_type == 'Averaging':
+43            blurred_img = cv2.blur(frame, kernel)
+44                        
+45        elif blur_type == 'Median':
+46            blurred_img = cv2.medianBlur(frame, kernel[0])
+47
+48        outputs.share_image('Out', blurred_img)
+49        synchronise()
+
+ + +

Block Description

+

Blurs an Object

+ +

The object to be blurred is read through the inputs. +We have multiple available blurs including Gaussian, Averaging and Median Blur. +We can change these blurs by changing the name given in the parameter block

+ +

while loop is the part of the program that is executed continuously. +It is enabled by default but can be disabled by passing in 0 through the enable wire.

+ +

Outputs the blurred image through the share_image() function

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image

+ +

Parameters: BlurType

+
+ +
+

Example Usage

+ +

Output

+ + + + + + + + + +
NormalAfter Median Blur
+
+ + + +
+
+ + + + \ No newline at end of file diff --git a/blockDocs/Blocks/Camera.html b/docs/blockDocs/Blocks/Camera.html similarity index 94% rename from blockDocs/Blocks/Camera.html rename to docs/blockDocs/Blocks/Camera.html index 282aec34..b3644ced 100644 --- a/blockDocs/Blocks/Camera.html +++ b/docs/blockDocs/Blocks/Camera.html @@ -68,27 +68,33 @@

9 10 `while` loop is the part of the program that is executed continuously. 11 It is enabled by default but can be disabled by passing in 0 through the enable wire. -12 ''' -13 cap = cv2.VideoCapture(0) -14 auto_enable = False -15 try: -16 enable = inputs.read_number('Enable') -17 except Exception: -18 auto_enable = True -19 try: -20 while cap.isOpened() and (auto_enable or inputs.read_number('Enable')): -21 ret, frame = cap.read() -22 if not ret: -23 continue -24 -25 outputs.share_image("Img", frame) -26 synchronise() -27 except Exception as e: -28 print('Error:', e) -29 pass -30 finally: -31 print("Exiting") -32 cap.release() +12 +13 **Inputs**: None +14 +15 **Outputs**: BGR Image +16 +17 **Parameters**: None +18 ''' +19 cap = cv2.VideoCapture(0) +20 auto_enable = False +21 try: +22 enable = inputs.read_number('Enable') +23 except Exception: +24 auto_enable = True +25 try: +26 while cap.isOpened() and (auto_enable or inputs.read_number('Enable')): +27 ret, frame = cap.read() +28 if not ret: +29 continue +30 +31 outputs.share_image("Img", frame) +32 synchronise() +33 except Exception as e: +34 print('Error:', e) +35 pass +36 finally: +37 print("Exiting") +38 cap.release()

@@ -112,27 +118,33 @@

10 11 `while` loop is the part of the program that is executed continuously. 12 It is enabled by default but can be disabled by passing in 0 through the enable wire. -13 ''' -14 cap = cv2.VideoCapture(0) -15 auto_enable = False -16 try: -17 enable = inputs.read_number('Enable') -18 except Exception: -19 auto_enable = True -20 try: -21 while cap.isOpened() and (auto_enable or inputs.read_number('Enable')): -22 ret, frame = cap.read() -23 if not ret: -24 continue -25 -26 outputs.share_image("Img", frame) -27 synchronise() -28 except Exception as e: -29 print('Error:', e) -30 pass -31 finally: -32 print("Exiting") -33 cap.release() +13 +14 **Inputs**: None +15 +16 **Outputs**: BGR Image +17 +18 **Parameters**: None +19 ''' +20 cap = cv2.VideoCapture(0) +21 auto_enable = False +22 try: +23 enable = inputs.read_number('Enable') +24 except Exception: +25 auto_enable = True +26 try: +27 while cap.isOpened() and (auto_enable or inputs.read_number('Enable')): +28 ret, frame = cap.read() +29 if not ret: +30 continue +31 +32 outputs.share_image("Img", frame) +33 synchronise() +34 except Exception as e: +35 print('Error:', e) +36 pass +37 finally: +38 print("Exiting") +39 cap.release() @@ -144,6 +156,12 @@

Block Description

while loop is the part of the program that is executed continuously. It is enabled by default but can be disabled by passing in 0 through the enable wire.

+ +

Inputs: None

+ +

Outputs: BGR Image

+ +

Parameters: None

diff --git a/blockDocs/Blocks/ColorFilter.html b/docs/blockDocs/Blocks/ColorFilter.html similarity index 95% rename from blockDocs/Blocks/ColorFilter.html rename to docs/blockDocs/Blocks/ColorFilter.html index 81b59fe4..49c2ca67 100644 --- a/blockDocs/Blocks/ColorFilter.html +++ b/docs/blockDocs/Blocks/ColorFilter.html @@ -72,27 +72,33 @@

13 Here the image is tranformed from `BGR` to `HSV` and then the filter is applied through the `cv2.inRange()` 14 function. Finally the filtered image is overlayed on the orignal by the means of the 15 `cv2.bitwise_and()` function. This filtered image is then shared through the `share_image()` function. -16 ''' -17 lower_rgb = np.array([int(x.strip()) for x in parameters.read_string('LowerRGB').split(',')]) -18 upper_rgb = np.array([int(x.strip()) for x in parameters.read_string('UpperRGB').split(',')]) -19 -20 auto_enable = False -21 try: -22 enable = inputs.read_number('Enable') -23 except Exception: -24 auto_enable = True +16 +17 **Inputs**: BGR Image +18 +19 **Outputs**: BGR Image +20 +21 **Parameters**: LowerHSV, UpperHSV +22 ''' +23 lower_rgb = np.array([int(x.strip()) for x in parameters.read_string('LowerRGB').split(',')]) +24 upper_rgb = np.array([int(x.strip()) for x in parameters.read_string('UpperRGB').split(',')]) 25 -26 while (auto_enable or inputs.read_number('Enable')): -27 frame = inputs.read_image('Img') -28 if frame is None: -29 continue -30 -31 hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) -32 mask = cv2.inRange(hsv, lower_rgb, upper_rgb) -33 filtered = cv2.bitwise_and(frame, frame, mask= mask) -34 -35 outputs.share_image('Out', filtered) -36 synchronise() +26 auto_enable = False +27 try: +28 enable = inputs.read_number('Enable') +29 except Exception: +30 auto_enable = True +31 +32 while (auto_enable or inputs.read_number('Enable')): +33 frame = inputs.read_image('Img') +34 if frame is None: +35 continue +36 +37 hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) +38 mask = cv2.inRange(hsv, lower_rgb, upper_rgb) +39 filtered = cv2.bitwise_and(frame, frame, mask= mask) +40 +41 outputs.share_image('Out', filtered) +42 synchronise() @@ -120,27 +126,33 @@

14 Here the image is tranformed from `BGR` to `HSV` and then the filter is applied through the `cv2.inRange()` 15 function. Finally the filtered image is overlayed on the orignal by the means of the 16 `cv2.bitwise_and()` function. This filtered image is then shared through the `share_image()` function. -17 ''' -18 lower_rgb = np.array([int(x.strip()) for x in parameters.read_string('LowerRGB').split(',')]) -19 upper_rgb = np.array([int(x.strip()) for x in parameters.read_string('UpperRGB').split(',')]) -20 -21 auto_enable = False -22 try: -23 enable = inputs.read_number('Enable') -24 except Exception: -25 auto_enable = True +17 +18 **Inputs**: BGR Image +19 +20 **Outputs**: BGR Image +21 +22 **Parameters**: LowerHSV, UpperHSV +23 ''' +24 lower_rgb = np.array([int(x.strip()) for x in parameters.read_string('LowerRGB').split(',')]) +25 upper_rgb = np.array([int(x.strip()) for x in parameters.read_string('UpperRGB').split(',')]) 26 -27 while (auto_enable or inputs.read_number('Enable')): -28 frame = inputs.read_image('Img') -29 if frame is None: -30 continue -31 -32 hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) -33 mask = cv2.inRange(hsv, lower_rgb, upper_rgb) -34 filtered = cv2.bitwise_and(frame, frame, mask= mask) -35 -36 outputs.share_image('Out', filtered) -37 synchronise() +27 auto_enable = False +28 try: +29 enable = inputs.read_number('Enable') +30 except Exception: +31 auto_enable = True +32 +33 while (auto_enable or inputs.read_number('Enable')): +34 frame = inputs.read_image('Img') +35 if frame is None: +36 continue +37 +38 hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) +39 mask = cv2.inRange(hsv, lower_rgb, upper_rgb) +40 filtered = cv2.bitwise_and(frame, frame, mask= mask) +41 +42 outputs.share_image('Out', filtered) +43 synchronise() @@ -156,6 +168,12 @@

Block Description

Here the image is tranformed from BGR to HSV and then the filter is applied through the cv2.inRange() function. Finally the filtered image is overlayed on the orignal by the means of the cv2.bitwise_and() function. This filtered image is then shared through the share_image() function.

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image

+ +

Parameters: LowerHSV, UpperHSV

diff --git a/blockDocs/Blocks/ContourDetector.html b/docs/blockDocs/Blocks/ContourDetector.html similarity index 94% rename from blockDocs/Blocks/ContourDetector.html rename to docs/blockDocs/Blocks/ContourDetector.html index f785a6b3..ffabcfdd 100644 --- a/blockDocs/Blocks/ContourDetector.html +++ b/docs/blockDocs/Blocks/ContourDetector.html @@ -78,40 +78,46 @@

19 It is enabled by default but can be disabled by passing in 0 through the enable wire. 20 21 [Further reading](https://docs.opencv.org/4.x/d4/d73/tutorial_py_contours_begin.html) -22 ''' -23 auto_enable = False -24 try: -25 enable = inputs.read_number("Enable") -26 except Exception: -27 auto_enable = True -28 -29 while(auto_enable or inputs.read_number('Enable')): -30 img = inputs.read_image("Img") -31 if img is None: -32 continue -33 -34 img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) -35 ret, thresh = cv2.threshold(img_gray, 60, 255, cv2.THRESH_BINARY) -36 contours, hierarchy = cv2.findContours(thresh, 1, 2) -37 -38 # Find the biggest contour (if detected) -39 if len(contours) > 0: -40 cont = max(contours, key=cv2.contourArea) -41 rect = cv2.minAreaRect(cont) # Get the minimum area bounding rectangle for the contour -42 # ( center (x,y), (width, height), angle of rotation ) +22 +23 **Inputs**: BGR Image +24 +25 **Outputs**: Array [x, y, width, height, angle of rotation], BGR Image +26 +27 **Parameters**: None +28 ''' +29 auto_enable = False +30 try: +31 enable = inputs.read_number("Enable") +32 except Exception: +33 auto_enable = True +34 +35 while(auto_enable or inputs.read_number('Enable')): +36 img = inputs.read_image("Img") +37 if img is None: +38 continue +39 +40 img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) +41 ret, thresh = cv2.threshold(img_gray, 60, 255, cv2.THRESH_BINARY) +42 contours, hierarchy = cv2.findContours(thresh, 1, 2) 43 -44 # Get the moments of the image -45 M = cv2.moments(cont) -46 if M['m00'] != 0: -47 # Get the coords of the center of the moments -48 cx = int(M['m10']/M['m00']) -49 cy = int(M['m01']/M['m00']) -50 -51 data = [cx, cy, rect[1][0], rect[1][1], rect[2]] -52 # Send the data to the wire in the form of an array -53 outputs.share_array('Out', data) -54 -55 synchronise() +44 # Find the biggest contour (if detected) +45 if len(contours) > 0: +46 cont = max(contours, key=cv2.contourArea) +47 rect = cv2.minAreaRect(cont) # Get the minimum area bounding rectangle for the contour +48 # ( center (x,y), (width, height), angle of rotation ) +49 +50 # Get the moments of the image +51 M = cv2.moments(cont) +52 if M['m00'] != 0: +53 # Get the coords of the center of the moments +54 cx = int(M['m10']/M['m00']) +55 cy = int(M['m01']/M['m00']) +56 +57 data = [cx, cy, rect[1][0], rect[1][1], rect[2]] +58 # Send the data to the wire in the form of an array +59 outputs.share_array('Out', data) +60 +61 synchronise() @@ -145,40 +151,46 @@

20 It is enabled by default but can be disabled by passing in 0 through the enable wire. 21 22 [Further reading](https://docs.opencv.org/4.x/d4/d73/tutorial_py_contours_begin.html) -23 ''' -24 auto_enable = False -25 try: -26 enable = inputs.read_number("Enable") -27 except Exception: -28 auto_enable = True -29 -30 while(auto_enable or inputs.read_number('Enable')): -31 img = inputs.read_image("Img") -32 if img is None: -33 continue -34 -35 img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) -36 ret, thresh = cv2.threshold(img_gray, 60, 255, cv2.THRESH_BINARY) -37 contours, hierarchy = cv2.findContours(thresh, 1, 2) -38 -39 # Find the biggest contour (if detected) -40 if len(contours) > 0: -41 cont = max(contours, key=cv2.contourArea) -42 rect = cv2.minAreaRect(cont) # Get the minimum area bounding rectangle for the contour -43 # ( center (x,y), (width, height), angle of rotation ) +23 +24 **Inputs**: BGR Image +25 +26 **Outputs**: Array [x, y, width, height, angle of rotation], BGR Image +27 +28 **Parameters**: None +29 ''' +30 auto_enable = False +31 try: +32 enable = inputs.read_number("Enable") +33 except Exception: +34 auto_enable = True +35 +36 while(auto_enable or inputs.read_number('Enable')): +37 img = inputs.read_image("Img") +38 if img is None: +39 continue +40 +41 img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) +42 ret, thresh = cv2.threshold(img_gray, 60, 255, cv2.THRESH_BINARY) +43 contours, hierarchy = cv2.findContours(thresh, 1, 2) 44 -45 # Get the moments of the image -46 M = cv2.moments(cont) -47 if M['m00'] != 0: -48 # Get the coords of the center of the moments -49 cx = int(M['m10']/M['m00']) -50 cy = int(M['m01']/M['m00']) -51 -52 data = [cx, cy, rect[1][0], rect[1][1], rect[2]] -53 # Send the data to the wire in the form of an array -54 outputs.share_array('Out', data) -55 -56 synchronise() +45 # Find the biggest contour (if detected) +46 if len(contours) > 0: +47 cont = max(contours, key=cv2.contourArea) +48 rect = cv2.minAreaRect(cont) # Get the minimum area bounding rectangle for the contour +49 # ( center (x,y), (width, height), angle of rotation ) +50 +51 # Get the moments of the image +52 M = cv2.moments(cont) +53 if M['m00'] != 0: +54 # Get the coords of the center of the moments +55 cx = int(M['m10']/M['m00']) +56 cy = int(M['m01']/M['m00']) +57 +58 data = [cx, cy, rect[1][0], rect[1][1], rect[2]] +59 # Send the data to the wire in the form of an array +60 outputs.share_array('Out', data) +61 +62 synchronise() @@ -200,6 +212,12 @@

Block Description

It is enabled by default but can be disabled by passing in 0 through the enable wire.

Further reading

+ +

Inputs: BGR Image

+ +

Outputs: Array [x, y, width, height, angle of rotation], BGR Image

+ +

Parameters: None

diff --git a/blockDocs/Blocks/Cropper.html b/docs/blockDocs/Blocks/Cropper.html similarity index 95% rename from blockDocs/Blocks/Cropper.html rename to docs/blockDocs/Blocks/Cropper.html index 14542092..dea8061d 100644 --- a/blockDocs/Blocks/Cropper.html +++ b/docs/blockDocs/Blocks/Cropper.html @@ -75,25 +75,31 @@

16 `while` loop is the part of the program that is executed continuously. 17 It is enabled by default but can be disabled by passing in 0 through the enable wire. 18 Output is shared via `share_image()` -19 ''' -20 x, y, w, h = np.array([int(x.strip()) for x in parameters.read_string("xywh").split(",")]) -21 -22 auto_enable = False -23 try: -24 enable = inputs.read_number("Enable") -25 except Exception: -26 auto_enable = True -27 -28 while(auto_enable or inputs.read_number('Enable')): -29 frame = inputs.read_image("Img") -30 if frame is None: -31 continue -32 -33 -34 cropped_img = frame[y:y+h, x:x+w, :] -35 outputs.share_image('Out', cropped_img) -36 -37 synchronise() +19 +20 **Inputs**: BGR Image +21 +22 **Outputs**: Resized BGR Image +23 +24 **Parameters**: x, y, width, height +25 ''' +26 x, y, w, h = np.array([int(x.strip()) for x in parameters.read_string("xywh").split(",")]) +27 +28 auto_enable = False +29 try: +30 enable = inputs.read_number("Enable") +31 except Exception: +32 auto_enable = True +33 +34 while(auto_enable or inputs.read_number('Enable')): +35 frame = inputs.read_image("Img") +36 if frame is None: +37 continue +38 +39 +40 cropped_img = frame[y:y+h, x:x+w, :] +41 outputs.share_image('Out', cropped_img) +42 +43 synchronise() @@ -124,25 +130,31 @@

17 `while` loop is the part of the program that is executed continuously. 18 It is enabled by default but can be disabled by passing in 0 through the enable wire. 19 Output is shared via `share_image()` -20 ''' -21 x, y, w, h = np.array([int(x.strip()) for x in parameters.read_string("xywh").split(",")]) -22 -23 auto_enable = False -24 try: -25 enable = inputs.read_number("Enable") -26 except Exception: -27 auto_enable = True -28 -29 while(auto_enable or inputs.read_number('Enable')): -30 frame = inputs.read_image("Img") -31 if frame is None: -32 continue -33 -34 -35 cropped_img = frame[y:y+h, x:x+w, :] -36 outputs.share_image('Out', cropped_img) -37 -38 synchronise() +20 +21 **Inputs**: BGR Image +22 +23 **Outputs**: Resized BGR Image +24 +25 **Parameters**: x, y, width, height +26 ''' +27 x, y, w, h = np.array([int(x.strip()) for x in parameters.read_string("xywh").split(",")]) +28 +29 auto_enable = False +30 try: +31 enable = inputs.read_number("Enable") +32 except Exception: +33 auto_enable = True +34 +35 while(auto_enable or inputs.read_number('Enable')): +36 frame = inputs.read_image("Img") +37 if frame is None: +38 continue +39 +40 +41 cropped_img = frame[y:y+h, x:x+w, :] +42 outputs.share_image('Out', cropped_img) +43 +44 synchronise() @@ -167,6 +179,12 @@

Block Description

while loop is the part of the program that is executed continuously. It is enabled by default but can be disabled by passing in 0 through the enable wire. Output is shared via share_image()

+ +

Inputs: BGR Image

+ +

Outputs: Resized BGR Image

+ +

Parameters: x, y, width, height

diff --git a/blockDocs/Blocks/Dilation.html b/docs/blockDocs/Blocks/Dilation.html similarity index 95% rename from blockDocs/Blocks/Dilation.html rename to docs/blockDocs/Blocks/Dilation.html index 1950a8a0..d62cf383 100644 --- a/blockDocs/Blocks/Dilation.html +++ b/docs/blockDocs/Blocks/Dilation.html @@ -70,28 +70,34 @@

11 Finaly we convert from `GRAY` back to `BGR` and output the image through the `share_image()` function. 12 13 [Further reading](https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html) -14 ''' -15 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) -16 kernel = np.ones(kernel, np.uint8) -17 iters = int(parameters.read_string("Iterations")) -18 auto_enable = False -19 try: -20 enable = inputs.read_number("Enable") -21 except Exception: -22 auto_enable = True -23 -24 while(auto_enable or inputs.read_number('Enable')): -25 frame = inputs.read_image("Img") -26 if frame is None: -27 continue -28 -29 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -30 dilated = cv2.dilate(frame, kernel, iterations = iters) -31 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) -32 -33 outputs.share_image('Out', dilated) +14 +15 **Inputs**: BGR Image +16 +17 **Outputs**: BGR Image +18 +19 **Parameters**: Kernel, Iterations +20 ''' +21 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) +22 kernel = np.ones(kernel, np.uint8) +23 iters = int(parameters.read_string("Iterations")) +24 auto_enable = False +25 try: +26 enable = inputs.read_number("Enable") +27 except Exception: +28 auto_enable = True +29 +30 while(auto_enable or inputs.read_number('Enable')): +31 frame = inputs.read_image("Img") +32 if frame is None: +33 continue 34 -35 synchronise() +35 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +36 dilated = cv2.dilate(frame, kernel, iterations = iters) +37 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) +38 +39 outputs.share_image('Out', dilated) +40 +41 synchronise() @@ -117,28 +123,34 @@

12 Finaly we convert from `GRAY` back to `BGR` and output the image through the `share_image()` function. 13 14 [Further reading](https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html) -15 ''' -16 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) -17 kernel = np.ones(kernel, np.uint8) -18 iters = int(parameters.read_string("Iterations")) -19 auto_enable = False -20 try: -21 enable = inputs.read_number("Enable") -22 except Exception: -23 auto_enable = True -24 -25 while(auto_enable or inputs.read_number('Enable')): -26 frame = inputs.read_image("Img") -27 if frame is None: -28 continue -29 -30 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -31 dilated = cv2.dilate(frame, kernel, iterations = iters) -32 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) -33 -34 outputs.share_image('Out', dilated) +15 +16 **Inputs**: BGR Image +17 +18 **Outputs**: BGR Image +19 +20 **Parameters**: Kernel, Iterations +21 ''' +22 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) +23 kernel = np.ones(kernel, np.uint8) +24 iters = int(parameters.read_string("Iterations")) +25 auto_enable = False +26 try: +27 enable = inputs.read_number("Enable") +28 except Exception: +29 auto_enable = True +30 +31 while(auto_enable or inputs.read_number('Enable')): +32 frame = inputs.read_image("Img") +33 if frame is None: +34 continue 35 -36 synchronise() +36 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +37 dilated = cv2.dilate(frame, kernel, iterations = iters) +38 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) +39 +40 outputs.share_image('Out', dilated) +41 +42 synchronise() @@ -153,6 +165,12 @@

Block Description

Finaly we convert from GRAY back to BGR and output the image through the share_image() function.

Further reading

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image

+ +

Parameters: Kernel, Iterations

diff --git a/blockDocs/Blocks/EdgeDetector.html b/docs/blockDocs/Blocks/EdgeDetector.html similarity index 95% rename from blockDocs/Blocks/EdgeDetector.html rename to docs/blockDocs/Blocks/EdgeDetector.html index b395725d..22a3d00d 100644 --- a/blockDocs/Blocks/EdgeDetector.html +++ b/docs/blockDocs/Blocks/EdgeDetector.html @@ -68,28 +68,34 @@

9 `cv2.Canny()` function. The resulting image is then converted back to `BGR`. 10 11 This image is then shared to the wire via the `share_image()` function. -12 ''' -13 lower = int(parameters.read_string("Lower")) -14 upper = int(parameters.read_string("Upper")) -15 -16 auto_enable = False -17 try: -18 enable = inputs.read_number("Enable") -19 except Exception: -20 auto_enable = True +12 +13 **Inputs**: BGR Image +14 +15 **Outputs**: BGR Image +16 +17 **Parameters**: Lower, Upper (Threshold values) +18 ''' +19 lower = int(parameters.read_string("Lower")) +20 upper = int(parameters.read_string("Upper")) 21 -22 while(auto_enable or inputs.read_number('Enable')): -23 frame = inputs.read_image("Img") -24 if frame is None: -25 continue -26 -27 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -28 edge_img = cv2.Canny(frame, lower, upper) -29 edge_img = cv2.cvtColor(edge_img, cv2.COLOR_GRAY2BGR) -30 -31 outputs.share_image('Out', edge_img) +22 auto_enable = False +23 try: +24 enable = inputs.read_number("Enable") +25 except Exception: +26 auto_enable = True +27 +28 while(auto_enable or inputs.read_number('Enable')): +29 frame = inputs.read_image("Img") +30 if frame is None: +31 continue 32 -33 synchronise() +33 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +34 edge_img = cv2.Canny(frame, lower, upper) +35 edge_img = cv2.cvtColor(edge_img, cv2.COLOR_GRAY2BGR) +36 +37 outputs.share_image('Out', edge_img) +38 +39 synchronise() @@ -113,28 +119,34 @@

10 `cv2.Canny()` function. The resulting image is then converted back to `BGR`. 11 12 This image is then shared to the wire via the `share_image()` function. -13 ''' -14 lower = int(parameters.read_string("Lower")) -15 upper = int(parameters.read_string("Upper")) -16 -17 auto_enable = False -18 try: -19 enable = inputs.read_number("Enable") -20 except Exception: -21 auto_enable = True +13 +14 **Inputs**: BGR Image +15 +16 **Outputs**: BGR Image +17 +18 **Parameters**: Lower, Upper (Threshold values) +19 ''' +20 lower = int(parameters.read_string("Lower")) +21 upper = int(parameters.read_string("Upper")) 22 -23 while(auto_enable or inputs.read_number('Enable')): -24 frame = inputs.read_image("Img") -25 if frame is None: -26 continue -27 -28 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -29 edge_img = cv2.Canny(frame, lower, upper) -30 edge_img = cv2.cvtColor(edge_img, cv2.COLOR_GRAY2BGR) -31 -32 outputs.share_image('Out', edge_img) +23 auto_enable = False +24 try: +25 enable = inputs.read_number("Enable") +26 except Exception: +27 auto_enable = True +28 +29 while(auto_enable or inputs.read_number('Enable')): +30 frame = inputs.read_image("Img") +31 if frame is None: +32 continue 33 -34 synchronise() +34 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +35 edge_img = cv2.Canny(frame, lower, upper) +36 edge_img = cv2.cvtColor(edge_img, cv2.COLOR_GRAY2BGR) +37 +38 outputs.share_image('Out', edge_img) +39 +40 synchronise() @@ -146,6 +158,12 @@

Block Description

cv2.Canny() function. The resulting image is then converted back to BGR.

This image is then shared to the wire via the share_image() function.

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image

+ +

Parameters: Lower, Upper (Threshold values)

diff --git a/blockDocs/Blocks/Erosion.html b/docs/blockDocs/Blocks/Erosion.html similarity index 95% rename from blockDocs/Blocks/Erosion.html rename to docs/blockDocs/Blocks/Erosion.html index 57b97d19..45e27ba5 100644 --- a/blockDocs/Blocks/Erosion.html +++ b/docs/blockDocs/Blocks/Erosion.html @@ -70,28 +70,34 @@

11 Finaly we convert from `GRAY` back to `BGR` and output the image through the `share_image()` function. 12 13 [Further reading]([Further reading](https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html)) -14 ''' -15 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) -16 kernel = np.ones(kernel, np.uint8) -17 iters = int(parameters.read_string("Iterations")) -18 auto_enable = False -19 try: -20 enable = inputs.read_number("Enable") -21 except Exception: -22 auto_enable = True -23 -24 while(auto_enable or inputs.read_number('Enable')): -25 frame = inputs.read_image("Img") -26 if frame is None: -27 continue -28 -29 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -30 dilated = cv2.erode(frame, kernel, iterations = iters) -31 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) -32 -33 outputs.share_image('Out', dilated) +14 +15 **Inputs**: BGR Image +16 +17 **Outputs**: BGR Image +18 +19 **Parameters**: Kernel, Iterations +20 ''' +21 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) +22 kernel = np.ones(kernel, np.uint8) +23 iters = int(parameters.read_string("Iterations")) +24 auto_enable = False +25 try: +26 enable = inputs.read_number("Enable") +27 except Exception: +28 auto_enable = True +29 +30 while(auto_enable or inputs.read_number('Enable')): +31 frame = inputs.read_image("Img") +32 if frame is None: +33 continue 34 -35 synchronise() +35 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +36 dilated = cv2.erode(frame, kernel, iterations = iters) +37 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) +38 +39 outputs.share_image('Out', dilated) +40 +41 synchronise() @@ -117,28 +123,34 @@

12 Finaly we convert from `GRAY` back to `BGR` and output the image through the `share_image()` function. 13 14 [Further reading]([Further reading](https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html)) -15 ''' -16 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) -17 kernel = np.ones(kernel, np.uint8) -18 iters = int(parameters.read_string("Iterations")) -19 auto_enable = False -20 try: -21 enable = inputs.read_number("Enable") -22 except Exception: -23 auto_enable = True -24 -25 while(auto_enable or inputs.read_number('Enable')): -26 frame = inputs.read_image("Img") -27 if frame is None: -28 continue -29 -30 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -31 dilated = cv2.erode(frame, kernel, iterations = iters) -32 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) -33 -34 outputs.share_image('Out', dilated) +15 +16 **Inputs**: BGR Image +17 +18 **Outputs**: BGR Image +19 +20 **Parameters**: Kernel, Iterations +21 ''' +22 kernel = np.array([int(x.strip()) for x in parameters.read_string("Kernel").split(",")]) +23 kernel = np.ones(kernel, np.uint8) +24 iters = int(parameters.read_string("Iterations")) +25 auto_enable = False +26 try: +27 enable = inputs.read_number("Enable") +28 except Exception: +29 auto_enable = True +30 +31 while(auto_enable or inputs.read_number('Enable')): +32 frame = inputs.read_image("Img") +33 if frame is None: +34 continue 35 -36 synchronise() +36 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +37 dilated = cv2.erode(frame, kernel, iterations = iters) +38 dilated = cv2.cvtColor(dilated, cv2.COLOR_GRAY2BGR) +39 +40 outputs.share_image('Out', dilated) +41 +42 synchronise() @@ -153,6 +165,12 @@

Block Description

Finaly we convert from GRAY back to BGR and output the image through the share_image() function.

Further reading

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image

+ +

Parameters: Kernel, Iterations

diff --git a/blockDocs/Blocks/FaceDetector.html b/docs/blockDocs/Blocks/FaceDetector.html similarity index 94% rename from blockDocs/Blocks/FaceDetector.html rename to docs/blockDocs/Blocks/FaceDetector.html index a69ebbb0..98001f47 100644 --- a/blockDocs/Blocks/FaceDetector.html +++ b/docs/blockDocs/Blocks/FaceDetector.html @@ -70,40 +70,46 @@

11 a face is detected. Image is shared through the `share_image()` function.\n 12 Else if `box` is given, the output is the co-ordinates of the bounding box in the form of an array. It 13 is chared through the `share_array()` function. -14 ''' -15 choice = parameters.read_string("BoxOrImage") -16 -17 auto_enable = False -18 try: -19 enable = inputs.read_number("Enable") -20 except Exception: -21 auto_enable = True -22 -23 classifier = cv2.CascadeClassifier('utils/models/haar_cascade/haarcascade_frontalface_default.xml') -24 -25 while(auto_enable or inputs.read_number('Enable')): -26 img = inputs.read_image("Img") -27 if img is None: -28 continue -29 bboxes = classifier.detectMultiScale(img) -30 -31 if choice == 'image': -32 for box in bboxes: -33 x, y, x1, y1 = box -34 x1, y1 = x+x1, y+y1 -35 cv2.rectangle(img, (x, y), (x1, y1), (0,255,0), 2) -36 outputs.share_image('Out', img) -37 else: -38 to_write = [320, 240, 0, 0] -39 for box in bboxes: -40 to_write = [box[0], box[1], box[2], box[3]] -41 break -42 outputs.share_array("Out", to_write) -43 -44 synchronise() -45 -46 -47 +14 +15 **Inputs**: BGR Image +16 +17 **Outputs**: BGR Image with Bounding Boxes +18 +19 **Parameters**: BoxOrImage ('box' for Bounding Boxes, 'image' for Image with Detections) +20 ''' +21 choice = parameters.read_string("BoxOrImage") +22 +23 auto_enable = False +24 try: +25 enable = inputs.read_number("Enable") +26 except Exception: +27 auto_enable = True +28 +29 classifier = cv2.CascadeClassifier('utils/models/haar_cascade/haarcascade_frontalface_default.xml') +30 +31 while(auto_enable or inputs.read_number('Enable')): +32 img = inputs.read_image("Img") +33 if img is None: +34 continue +35 bboxes = classifier.detectMultiScale(img) +36 +37 if choice == 'image': +38 for box in bboxes: +39 x, y, x1, y1 = box +40 x1, y1 = x+x1, y+y1 +41 cv2.rectangle(img, (x, y), (x1, y1), (0,255,0), 2) +42 outputs.share_image('Out', img) +43 else: +44 to_write = [320, 240, 0, 0] +45 for box in bboxes: +46 to_write = [box[0], box[1], box[2], box[3]] +47 break +48 outputs.share_array("Out", to_write) +49 +50 synchronise() +51 +52 +53 @@ -129,37 +135,43 @@

12 a face is detected. Image is shared through the `share_image()` function.\n 13 Else if `box` is given, the output is the co-ordinates of the bounding box in the form of an array. It 14 is chared through the `share_array()` function. -15 ''' -16 choice = parameters.read_string("BoxOrImage") -17 -18 auto_enable = False -19 try: -20 enable = inputs.read_number("Enable") -21 except Exception: -22 auto_enable = True -23 -24 classifier = cv2.CascadeClassifier('utils/models/haar_cascade/haarcascade_frontalface_default.xml') -25 -26 while(auto_enable or inputs.read_number('Enable')): -27 img = inputs.read_image("Img") -28 if img is None: -29 continue -30 bboxes = classifier.detectMultiScale(img) -31 -32 if choice == 'image': -33 for box in bboxes: -34 x, y, x1, y1 = box -35 x1, y1 = x+x1, y+y1 -36 cv2.rectangle(img, (x, y), (x1, y1), (0,255,0), 2) -37 outputs.share_image('Out', img) -38 else: -39 to_write = [320, 240, 0, 0] -40 for box in bboxes: -41 to_write = [box[0], box[1], box[2], box[3]] -42 break -43 outputs.share_array("Out", to_write) -44 -45 synchronise() +15 +16 **Inputs**: BGR Image +17 +18 **Outputs**: BGR Image with Bounding Boxes +19 +20 **Parameters**: BoxOrImage ('box' for Bounding Boxes, 'image' for Image with Detections) +21 ''' +22 choice = parameters.read_string("BoxOrImage") +23 +24 auto_enable = False +25 try: +26 enable = inputs.read_number("Enable") +27 except Exception: +28 auto_enable = True +29 +30 classifier = cv2.CascadeClassifier('utils/models/haar_cascade/haarcascade_frontalface_default.xml') +31 +32 while(auto_enable or inputs.read_number('Enable')): +33 img = inputs.read_image("Img") +34 if img is None: +35 continue +36 bboxes = classifier.detectMultiScale(img) +37 +38 if choice == 'image': +39 for box in bboxes: +40 x, y, x1, y1 = box +41 x1, y1 = x+x1, y+y1 +42 cv2.rectangle(img, (x, y), (x1, y1), (0,255,0), 2) +43 outputs.share_image('Out', img) +44 else: +45 to_write = [320, 240, 0, 0] +46 for box in bboxes: +47 to_write = [box[0], box[1], box[2], box[3]] +48 break +49 outputs.share_array("Out", to_write) +50 +51 synchronise() @@ -175,6 +187,12 @@

Block Description

Else if box is given, the output is the co-ordinates of the bounding box in the form of an array. It is chared through the share_array() function.

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image with Bounding Boxes

+ +

Parameters: BoxOrImage ('box' for Bounding Boxes, 'image' for Image with Detections)

diff --git a/blockDocs/Blocks/IMU.html b/docs/blockDocs/Blocks/IMU.html similarity index 96% rename from blockDocs/Blocks/IMU.html rename to docs/blockDocs/Blocks/IMU.html index f9c5c635..b29c90be 100644 --- a/blockDocs/Blocks/IMU.html +++ b/docs/blockDocs/Blocks/IMU.html @@ -75,7 +75,7 @@

13 We convert these radian values to degrees to get the orientation of the body. 14 15 Aside from these values the IMU also gives us the angular velocity of the body.\n -16 All of these values are stored in the global data variable of the block. +16 All of these values are stored in the global `data` variable of the block. 17 ''' 18 global data 19 # Get the orientation list from the IMU sensor @@ -102,24 +102,30 @@

40 This data is sent to the callback function which converts the orientation list obtained into roll, pitch and yaw for the 41 robot that the IMU is present on. Alongwith orientation, it also gives the angular velocity of the robot. 42 This data is shared in the form of an array using the `share_array()` function. -43 ''' -44 global data -45 auto_enable = False -46 try: -47 enable = inputs.read_number('Enable') -48 except Exception: -49 auto_enable = True -50 -51 rospy.init_node('imu_vc') -52 rostopic_name = parameters.read_string("ROSTopic") -53 rospy.Subscriber(rostopic_name, Imu, callback) -54 -55 while ((auto_enable or inputs.read_number('Enable')) and not rospy.is_shutdown()): -56 if not data: -57 continue -58 -59 outputs.share_array("Out", data) -60 synchronise() +43 +44 **Inputs**: None +45 +46 **Outputs**: Array [Roll, Pitch , Yaw, Angular Velocity in X, Angular Velocity in Y, Angular Velocity in Z] +47 +48 **Parameters**: ROSTopic +49 ''' +50 global data +51 auto_enable = False +52 try: +53 enable = inputs.read_number('Enable') +54 except Exception: +55 auto_enable = True +56 +57 rospy.init_node('imu_vc') +58 rostopic_name = parameters.read_string("ROSTopic") +59 rospy.Subscriber(rostopic_name, Imu, callback) +60 +61 while ((auto_enable or inputs.read_number('Enable')) and not rospy.is_shutdown()): +62 if not data: +63 continue +64 +65 outputs.share_array("Out", data) +66 synchronise() @@ -142,7 +148,7 @@

14 We convert these radian values to degrees to get the orientation of the body. 15 16 Aside from these values the IMU also gives us the angular velocity of the body.\n -17 All of these values are stored in the global data variable of the block. +17 All of these values are stored in the global `data` variable of the block. 18 ''' 19 global data 20 # Get the orientation list from the IMU sensor @@ -168,7 +174,7 @@

Aside from these values the IMU also gives us the angular velocity of the body.

-

All of these values are stored in the global data variable of the block.

+

All of these values are stored in the global data variable of the block.

@@ -194,24 +200,30 @@

41 This data is sent to the callback function which converts the orientation list obtained into roll, pitch and yaw for the 42 robot that the IMU is present on. Alongwith orientation, it also gives the angular velocity of the robot. 43 This data is shared in the form of an array using the `share_array()` function. -44 ''' -45 global data -46 auto_enable = False -47 try: -48 enable = inputs.read_number('Enable') -49 except Exception: -50 auto_enable = True -51 -52 rospy.init_node('imu_vc') -53 rostopic_name = parameters.read_string("ROSTopic") -54 rospy.Subscriber(rostopic_name, Imu, callback) -55 -56 while ((auto_enable or inputs.read_number('Enable')) and not rospy.is_shutdown()): -57 if not data: -58 continue -59 -60 outputs.share_array("Out", data) -61 synchronise() +44 +45 **Inputs**: None +46 +47 **Outputs**: Array [Roll, Pitch , Yaw, Angular Velocity in X, Angular Velocity in Y, Angular Velocity in Z] +48 +49 **Parameters**: ROSTopic +50 ''' +51 global data +52 auto_enable = False +53 try: +54 enable = inputs.read_number('Enable') +55 except Exception: +56 auto_enable = True +57 +58 rospy.init_node('imu_vc') +59 rostopic_name = parameters.read_string("ROSTopic") +60 rospy.Subscriber(rostopic_name, Imu, callback) +61 +62 while ((auto_enable or inputs.read_number('Enable')) and not rospy.is_shutdown()): +63 if not data: +64 continue +65 +66 outputs.share_array("Out", data) +67 synchronise() @@ -225,6 +237,12 @@

Block Description

This data is sent to the callback function which converts the orientation list obtained into roll, pitch and yaw for the robot that the IMU is present on. Alongwith orientation, it also gives the angular velocity of the robot. This data is shared in the form of an array using the share_array() function.

+ +

Inputs: None

+ +

Outputs: Array [Roll, Pitch , Yaw, Angular Velocity in X, Angular Velocity in Y, Angular Velocity in Z]

+ +

Parameters: ROSTopic

diff --git a/blockDocs/Blocks/ImageRead.html b/docs/blockDocs/Blocks/ImageRead.html similarity index 95% rename from blockDocs/Blocks/ImageRead.html rename to docs/blockDocs/Blocks/ImageRead.html index 9b186724..99b47c66 100644 --- a/blockDocs/Blocks/ImageRead.html +++ b/docs/blockDocs/Blocks/ImageRead.html @@ -66,21 +66,27 @@

7 This box reads an image from a given file path. The path to be specified is written in the parameter 8 `ImagePath`.\n 9 It is read through the `cv2.imread()` function and shared through the `share_image()` function. -10 ''' -11 path = parameters.read_string("ImagePath") -12 image = cv2.imread(path) -13 auto_enable = False -14 try: -15 enable = inputs.read_number("Enable") -16 except Exception: -17 auto_enable = True -18 -19 while(auto_enable or inputs.read_number('Enable')): -20 outputs.share_image('Out', image) -21 synchronise() -22 -23 -24 +10 +11 **Inputs**: None +12 +13 **Outputs**: BGR Image +14 +15 **Parameters**: ImagePath +16 ''' +17 path = parameters.read_string("ImagePath") +18 image = cv2.imread(path) +19 auto_enable = False +20 try: +21 enable = inputs.read_number("Enable") +22 except Exception: +23 auto_enable = True +24 +25 while(auto_enable or inputs.read_number('Enable')): +26 outputs.share_image('Out', image) +27 synchronise() +28 +29 +30 @@ -102,18 +108,24 @@

8 This box reads an image from a given file path. The path to be specified is written in the parameter 9 `ImagePath`.\n 10 It is read through the `cv2.imread()` function and shared through the `share_image()` function. -11 ''' -12 path = parameters.read_string("ImagePath") -13 image = cv2.imread(path) -14 auto_enable = False -15 try: -16 enable = inputs.read_number("Enable") -17 except Exception: -18 auto_enable = True -19 -20 while(auto_enable or inputs.read_number('Enable')): -21 outputs.share_image('Out', image) -22 synchronise() +11 +12 **Inputs**: None +13 +14 **Outputs**: BGR Image +15 +16 **Parameters**: ImagePath +17 ''' +18 path = parameters.read_string("ImagePath") +19 image = cv2.imread(path) +20 auto_enable = False +21 try: +22 enable = inputs.read_number("Enable") +23 except Exception: +24 auto_enable = True +25 +26 while(auto_enable or inputs.read_number('Enable')): +27 outputs.share_image('Out', image) +28 synchronise() @@ -124,6 +136,12 @@

Block Description

ImagePath.

It is read through the cv2.imread() function and shared through the share_image() function.

+ +

Inputs: None

+ +

Outputs: BGR Image

+ +

Parameters: ImagePath

diff --git a/blockDocs/Blocks/MotorDriver.html b/docs/blockDocs/Blocks/MotorDriver.html similarity index 94% rename from blockDocs/Blocks/MotorDriver.html rename to docs/blockDocs/Blocks/MotorDriver.html index f18fbf47..edceedeb 100644 --- a/blockDocs/Blocks/MotorDriver.html +++ b/docs/blockDocs/Blocks/MotorDriver.html @@ -80,36 +80,42 @@

18 This data is then converted into a Twist() message with the `linear.x = linear_velocity` and `angular.z = angular_velocity` 19 20 The data is then published continuously -21 ''' -22 rospy.init_node("motordriverVC", anonymous=True) +21 +22 **Inputs**: `cmd_vel` (Linear Velocity, Angular Velocity) 23 -24 rostopic_name = parameters.read_string("ROSTopic") -25 # Create a Publisher that publishes to the given ROSTopic -26 publisher = rospy.Publisher(rostopic_name, Twist, queue_size=10) -27 -28 auto_enable = True -29 try: -30 enable = inputs.read_number("Enable") -31 except Exception: -32 auto_enable = True -33 -34 # Create a Twist message -35 data = Twist() -36 -37 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): -38 msg = inputs.read_array("Inp") -39 -40 if msg is None: -41 continue +24 **Outputs**: None +25 +26 **Parameters**: ROSTopic +27 ''' +28 rospy.init_node("motordriverVC", anonymous=True) +29 +30 rostopic_name = parameters.read_string("ROSTopic") +31 # Create a Publisher that publishes to the given ROSTopic +32 publisher = rospy.Publisher(rostopic_name, Twist, queue_size=10) +33 +34 auto_enable = True +35 try: +36 enable = inputs.read_number("Enable") +37 except Exception: +38 auto_enable = True +39 +40 # Create a Twist message +41 data = Twist() 42 -43 linear_velocity = float(msg[0]) -44 angular_velocity = float(msg[1]) +43 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): +44 msg = inputs.read_array("Inp") 45 -46 data.linear.x = linear_velocity -47 data.angular.z = angular_velocity -48 publisher.publish(data) -49 -50 synchronise() +46 if msg is None: +47 continue +48 +49 linear_velocity = float(msg[0]) +50 angular_velocity = float(msg[1]) +51 +52 data.linear.x = linear_velocity +53 data.angular.z = angular_velocity +54 publisher.publish(data) +55 +56 synchronise() @@ -153,36 +159,42 @@

19 This data is then converted into a Twist() message with the `linear.x = linear_velocity` and `angular.z = angular_velocity` 20 21 The data is then published continuously -22 ''' -23 rospy.init_node("motordriverVC", anonymous=True) +22 +23 **Inputs**: `cmd_vel` (Linear Velocity, Angular Velocity) 24 -25 rostopic_name = parameters.read_string("ROSTopic") -26 # Create a Publisher that publishes to the given ROSTopic -27 publisher = rospy.Publisher(rostopic_name, Twist, queue_size=10) -28 -29 auto_enable = True -30 try: -31 enable = inputs.read_number("Enable") -32 except Exception: -33 auto_enable = True -34 -35 # Create a Twist message -36 data = Twist() -37 -38 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): -39 msg = inputs.read_array("Inp") -40 -41 if msg is None: -42 continue +25 **Outputs**: None +26 +27 **Parameters**: ROSTopic +28 ''' +29 rospy.init_node("motordriverVC", anonymous=True) +30 +31 rostopic_name = parameters.read_string("ROSTopic") +32 # Create a Publisher that publishes to the given ROSTopic +33 publisher = rospy.Publisher(rostopic_name, Twist, queue_size=10) +34 +35 auto_enable = True +36 try: +37 enable = inputs.read_number("Enable") +38 except Exception: +39 auto_enable = True +40 +41 # Create a Twist message +42 data = Twist() 43 -44 linear_velocity = float(msg[0]) -45 angular_velocity = float(msg[1]) +44 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): +45 msg = inputs.read_array("Inp") 46 -47 data.linear.x = linear_velocity -48 data.angular.z = angular_velocity -49 publisher.publish(data) -50 -51 synchronise() +47 if msg is None: +48 continue +49 +50 linear_velocity = float(msg[0]) +51 angular_velocity = float(msg[1]) +52 +53 data.linear.x = linear_velocity +54 data.angular.z = angular_velocity +55 publisher.publish(data) +56 +57 synchronise() @@ -197,7 +209,13 @@

Block Description

This data is then converted into a Twist() message with the linear.x = linear_velocity and angular.z = angular_velocity

-

The data is then published continuously

+

The data is then published continuously

+ +

Inputs: cmd_vel (Linear Velocity, Angular Velocity)

+ +

Outputs: None

+ +

Parameters: ROSTopic

diff --git a/blockDocs/Blocks/Odometer.html b/docs/blockDocs/Blocks/Odometer.html similarity index 95% rename from blockDocs/Blocks/Odometer.html rename to docs/blockDocs/Blocks/Odometer.html index 8548d447..41c8416e 100644 --- a/blockDocs/Blocks/Odometer.html +++ b/docs/blockDocs/Blocks/Odometer.html @@ -79,23 +79,29 @@

17 It then initializes a Subscriber to subscribe to that ROSTopic, once the data is obtained through the callback 18 function, it is formatted into an array with the format: `[ x, y, yaw ]`\n 19 This data is then shared to the wire using the `share_array()` function. -20 ''' -21 rospy.init_node("odometerVC", anonymous=True) -22 rostopic_name = parameters.read_string("ROSTopic") -23 odometer_subscriber = rospy.Subscriber(rostopic_name, Pose, callback) +20 +21 **Inputs**: None +22 +23 **Outputs**: Array [X, Y, Yaw] 24 -25 auto_enable = False -26 try: -27 enable = inputs.read_number("Enable") -28 except Exception: -29 auto_enable = True +25 **Parameters**: ROSTopic +26 ''' +27 rospy.init_node("odometerVC", anonymous=True) +28 rostopic_name = parameters.read_string("ROSTopic") +29 odometer_subscriber = rospy.Subscriber(rostopic_name, Pose, callback) 30 -31 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): -32 data = [x, y, yaw] -33 -34 outputs.share_array("Out", data) -35 -36 synchronise() +31 auto_enable = False +32 try: +33 enable = inputs.read_number("Enable") +34 except Exception: +35 auto_enable = True +36 +37 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): +38 data = [x, y, yaw] +39 +40 outputs.share_array("Out", data) +41 +42 synchronise() @@ -140,23 +146,29 @@

18 It then initializes a Subscriber to subscribe to that ROSTopic, once the data is obtained through the callback 19 function, it is formatted into an array with the format: `[ x, y, yaw ]`\n 20 This data is then shared to the wire using the `share_array()` function. -21 ''' -22 rospy.init_node("odometerVC", anonymous=True) -23 rostopic_name = parameters.read_string("ROSTopic") -24 odometer_subscriber = rospy.Subscriber(rostopic_name, Pose, callback) +21 +22 **Inputs**: None +23 +24 **Outputs**: Array [X, Y, Yaw] 25 -26 auto_enable = False -27 try: -28 enable = inputs.read_number("Enable") -29 except Exception: -30 auto_enable = True +26 **Parameters**: ROSTopic +27 ''' +28 rospy.init_node("odometerVC", anonymous=True) +29 rostopic_name = parameters.read_string("ROSTopic") +30 odometer_subscriber = rospy.Subscriber(rostopic_name, Pose, callback) 31 -32 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): -33 data = [x, y, yaw] -34 -35 outputs.share_array("Out", data) -36 -37 synchronise() +32 auto_enable = False +33 try: +34 enable = inputs.read_number("Enable") +35 except Exception: +36 auto_enable = True +37 +38 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): +39 data = [x, y, yaw] +40 +41 outputs.share_array("Out", data) +42 +43 synchronise() @@ -168,6 +180,12 @@

Block Description

function, it is formatted into an array with the format: [ x, y, yaw ]

This data is then shared to the wire using the share_array() function.

+ +

Inputs: None

+ +

Outputs: Array [X, Y, Yaw]

+ +

Parameters: ROSTopic

diff --git a/blockDocs/Blocks/PID.html b/docs/blockDocs/Blocks/PID.html similarity index 94% rename from blockDocs/Blocks/PID.html rename to docs/blockDocs/Blocks/PID.html index 210f6cd0..35e91e9b 100644 --- a/blockDocs/Blocks/PID.html +++ b/docs/blockDocs/Blocks/PID.html @@ -69,40 +69,46 @@

10 Once there it applies the PID technique to the error variable in order to minimize it. 11 12 The resulting values are shared through the `share_array()` function. -13 ''' -14 auto_enable = True -15 try: -16 enable = inputs.read_number("Enable") -17 except Exception: -18 auto_enable = True -19 -20 kp = parameters.read_number("Kp") -21 ki = parameters.read_number("Ki") -22 kd = parameters.read_number("Kd") -23 -24 previousError, I = 0, 0 -25 # Problem this should be inside the while loop -26 msg = inputs.read_number("Inp") -27 -28 while(auto_enable or inputs.read_number('Enable')): -29 if msg is None: -30 continue -31 -32 error = float(msg) -33 sleep(0.01) -34 -35 P = error -36 I = I + error -37 D = error - previousError -38 PIDvalue = (kp*P) + (ki*I) + (kd*D) -39 previousError = error +13 +14 **Inputs**: Error +15 +16 **Outputs**: `cmd_vel` (Linear Velocity, Angular Velocity) +17 +18 **Parameters**: Kp, Ki, Kd +19 ''' +20 auto_enable = True +21 try: +22 enable = inputs.read_number("Enable") +23 except Exception: +24 auto_enable = True +25 +26 kp = parameters.read_number("Kp") +27 ki = parameters.read_number("Ki") +28 kd = parameters.read_number("Kd") +29 +30 previousError, I = 0, 0 +31 # Problem this should be inside the while loop +32 msg = inputs.read_number("Inp") +33 +34 while(auto_enable or inputs.read_number('Enable')): +35 if msg is None: +36 continue +37 +38 error = float(msg) +39 sleep(0.01) 40 -41 linear_velocity = 5.0 -42 angular_velocity = -PIDvalue -43 -44 data = [linear_velocity, angular_velocity] -45 outputs.share_array("Out", data) -46 synchronise() +41 P = error +42 I = I + error +43 D = error - previousError +44 PIDvalue = (kp*P) + (ki*I) + (kd*D) +45 previousError = error +46 +47 linear_velocity = 5.0 +48 angular_velocity = -PIDvalue +49 +50 data = [linear_velocity, angular_velocity] +51 outputs.share_array("Out", data) +52 synchronise() @@ -126,40 +132,46 @@

11 Once there it applies the PID technique to the error variable in order to minimize it. 12 13 The resulting values are shared through the `share_array()` function. -14 ''' -15 auto_enable = True -16 try: -17 enable = inputs.read_number("Enable") -18 except Exception: -19 auto_enable = True -20 -21 kp = parameters.read_number("Kp") -22 ki = parameters.read_number("Ki") -23 kd = parameters.read_number("Kd") -24 -25 previousError, I = 0, 0 -26 # Problem this should be inside the while loop -27 msg = inputs.read_number("Inp") -28 -29 while(auto_enable or inputs.read_number('Enable')): -30 if msg is None: -31 continue -32 -33 error = float(msg) -34 sleep(0.01) -35 -36 P = error -37 I = I + error -38 D = error - previousError -39 PIDvalue = (kp*P) + (ki*I) + (kd*D) -40 previousError = error +14 +15 **Inputs**: Error +16 +17 **Outputs**: `cmd_vel` (Linear Velocity, Angular Velocity) +18 +19 **Parameters**: Kp, Ki, Kd +20 ''' +21 auto_enable = True +22 try: +23 enable = inputs.read_number("Enable") +24 except Exception: +25 auto_enable = True +26 +27 kp = parameters.read_number("Kp") +28 ki = parameters.read_number("Ki") +29 kd = parameters.read_number("Kd") +30 +31 previousError, I = 0, 0 +32 # Problem this should be inside the while loop +33 msg = inputs.read_number("Inp") +34 +35 while(auto_enable or inputs.read_number('Enable')): +36 if msg is None: +37 continue +38 +39 error = float(msg) +40 sleep(0.01) 41 -42 linear_velocity = 5.0 -43 angular_velocity = -PIDvalue -44 -45 data = [linear_velocity, angular_velocity] -46 outputs.share_array("Out", data) -47 synchronise() +42 P = error +43 I = I + error +44 D = error - previousError +45 PIDvalue = (kp*P) + (ki*I) + (kd*D) +46 previousError = error +47 +48 linear_velocity = 5.0 +49 angular_velocity = -PIDvalue +50 +51 data = [linear_velocity, angular_velocity] +52 outputs.share_array("Out", data) +53 synchronise() @@ -171,7 +183,13 @@

Block Description

The Kp, Ki, and Kd parameters are read from the parameters of the same name. Once there it applies the PID technique to the error variable in order to minimize it.

-

The resulting values are shared through the share_array() function.

+

The resulting values are shared through the share_array() function.

+ +

Inputs: Error

+ +

Outputs: cmd_vel (Linear Velocity, Angular Velocity)

+ +

Parameters: Kp, Ki, Kd

diff --git a/blockDocs/Blocks/ROSCamera.html b/docs/blockDocs/Blocks/ROSCamera.html similarity index 95% rename from blockDocs/Blocks/ROSCamera.html rename to docs/blockDocs/Blocks/ROSCamera.html index af92fcef..3b89bf6d 100644 --- a/blockDocs/Blocks/ROSCamera.html +++ b/docs/blockDocs/Blocks/ROSCamera.html @@ -80,23 +80,29 @@

18 The image message is converted to OpenCV compatible format via the `imgmsg_to_cv2()` function. 19 20 This is then shared ahead using the `share_image()` function. -21 ''' -22 auto_enable = False -23 try: -24 enable = inputs.read_number("Enable") -25 except Exception: -26 auto_enable = True -27 -28 rospy.init_node("camera_ros", anonymous=True) -29 subscriber_name = parameters.read_string("ROSTopic") -30 camera_subscriber = rospy.Subscriber(subscriber_name, Image, callback) -31 -32 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): -33 if img is None: -34 continue -35 -36 outputs.share_image("Out", img) -37 synchronise() +21 +22 **Inputs**: None +23 +24 **Outputs**: BGR Image +25 +26 **Parameters**: ROSTopic +27 ''' +28 auto_enable = False +29 try: +30 enable = inputs.read_number("Enable") +31 except Exception: +32 auto_enable = True +33 +34 rospy.init_node("camera_ros", anonymous=True) +35 subscriber_name = parameters.read_string("ROSTopic") +36 camera_subscriber = rospy.Subscriber(subscriber_name, Image, callback) +37 +38 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): +39 if img is None: +40 continue +41 +42 outputs.share_image("Out", img) +43 synchronise() @@ -140,23 +146,29 @@

19 The image message is converted to OpenCV compatible format via the `imgmsg_to_cv2()` function. 20 21 This is then shared ahead using the `share_image()` function. -22 ''' -23 auto_enable = False -24 try: -25 enable = inputs.read_number("Enable") -26 except Exception: -27 auto_enable = True -28 -29 rospy.init_node("camera_ros", anonymous=True) -30 subscriber_name = parameters.read_string("ROSTopic") -31 camera_subscriber = rospy.Subscriber(subscriber_name, Image, callback) -32 -33 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): -34 if img is None: -35 continue -36 -37 outputs.share_image("Out", img) -38 synchronise() +22 +23 **Inputs**: None +24 +25 **Outputs**: BGR Image +26 +27 **Parameters**: ROSTopic +28 ''' +29 auto_enable = False +30 try: +31 enable = inputs.read_number("Enable") +32 except Exception: +33 auto_enable = True +34 +35 rospy.init_node("camera_ros", anonymous=True) +36 subscriber_name = parameters.read_string("ROSTopic") +37 camera_subscriber = rospy.Subscriber(subscriber_name, Image, callback) +38 +39 while(auto_enable or inputs.read_number('Enable') and not rospy.is_shutdown()): +40 if img is None: +41 continue +42 +43 outputs.share_image("Out", img) +44 synchronise() @@ -168,6 +180,12 @@

Block Description

The image message is converted to OpenCV compatible format via the imgmsg_to_cv2() function.

This is then shared ahead using the share_image() function.

+ +

Inputs: None

+ +

Outputs: BGR Image

+ +

Parameters: ROSTopic

diff --git a/blockDocs/Blocks/Screen.html b/docs/blockDocs/Blocks/Screen.html similarity index 95% rename from blockDocs/Blocks/Screen.html rename to docs/blockDocs/Blocks/Screen.html index 4c954559..69e4946d 100644 --- a/blockDocs/Blocks/Screen.html +++ b/docs/blockDocs/Blocks/Screen.html @@ -65,21 +65,27 @@

6 7 Takes an image as an input and displays it on the user's screen. 8 The `cv2.imshow()` function is used in order to display the image. - 9 ''' -10 auto_enable = False -11 try: -12 enable = inputs.read_number('Enable') -13 except Exception: -14 auto_enable = True -15 while (auto_enable or inputs.read_number('Enable')): -16 img = inputs.read_image("Img") -17 if img is None: -18 continue -19 -20 cv2.imshow("frame", img) -21 cv2.waitKey(10) -22 -23 synchronise() + 9 +10 **Inputs**: BGR Image +11 +12 **Outputs**: None +13 +14 **Parameters**: None +15 ''' +16 auto_enable = False +17 try: +18 enable = inputs.read_number('Enable') +19 except Exception: +20 auto_enable = True +21 while (auto_enable or inputs.read_number('Enable')): +22 img = inputs.read_image("Img") +23 if img is None: +24 continue +25 +26 cv2.imshow("frame", img) +27 cv2.waitKey(10) +28 +29 synchronise() @@ -101,21 +107,27 @@

7 8 Takes an image as an input and displays it on the user's screen. 9 The `cv2.imshow()` function is used in order to display the image. -10 ''' -11 auto_enable = False -12 try: -13 enable = inputs.read_number('Enable') -14 except Exception: -15 auto_enable = True -16 while (auto_enable or inputs.read_number('Enable')): -17 img = inputs.read_image("Img") -18 if img is None: -19 continue -20 -21 cv2.imshow("frame", img) -22 cv2.waitKey(10) -23 -24 synchronise() +10 +11 **Inputs**: BGR Image +12 +13 **Outputs**: None +14 +15 **Parameters**: None +16 ''' +17 auto_enable = False +18 try: +19 enable = inputs.read_number('Enable') +20 except Exception: +21 auto_enable = True +22 while (auto_enable or inputs.read_number('Enable')): +23 img = inputs.read_image("Img") +24 if img is None: +25 continue +26 +27 cv2.imshow("frame", img) +28 cv2.waitKey(10) +29 +30 synchronise() @@ -124,6 +136,12 @@

Block Description

Takes an image as an input and displays it on the user's screen. The cv2.imshow() function is used in order to display the image.

+ +

Inputs: BGR Image

+ +

Outputs: None

+ +

Parameters: None

diff --git a/blockDocs/Blocks/Teleoperator.html b/docs/blockDocs/Blocks/Teleoperator.html similarity index 94% rename from blockDocs/Blocks/Teleoperator.html rename to docs/blockDocs/Blocks/Teleoperator.html index c09db452..c483935d 100644 --- a/blockDocs/Blocks/Teleoperator.html +++ b/docs/blockDocs/Blocks/Teleoperator.html @@ -68,34 +68,40 @@

9 10 The output data is a list of the format: `[ linear_velocity, angular_velocity ]`\n 11 This is then shared to the output wire using the `share_array()` function. -12 ''' -13 auto_enable = True -14 try: -15 enable = inputs.read_number("Enable") -16 except Exception: -17 auto_enable = True -18 -19 linear_velocity = parameters.read_number("Linear") -20 -21 while(auto_enable or inputs.read_number('Enable')): -22 msg = inputs.read_array("Inp") -23 -24 # (x, y, width, height) -25 x, y = float(msg[0]), float(msg[1]) -26 x1, y1 = x+float(msg[2]), y+float(msg[3]) -27 -28 # Teleoperator Control Logic -29 cx = (x+x1)/2.0 -30 -31 if cx < 320: -32 angular_velocity = -0.5 -33 else: -34 angular_velocity = 0.5 -35 -36 data = [linear_velocity, angular_velocity] -37 outputs.share_array("Out", data) -38 -39 synchronise() +12 +13 **Inputs**: Bounding Box (x, y, width, height) +14 +15 **Outputs**: `cmd_vel` (linear velocity, angular velocity) +16 +17 **Parameters**: Linear(Linear Velocity) +18 ''' +19 auto_enable = True +20 try: +21 enable = inputs.read_number("Enable") +22 except Exception: +23 auto_enable = True +24 +25 linear_velocity = parameters.read_number("Linear") +26 +27 while(auto_enable or inputs.read_number('Enable')): +28 msg = inputs.read_array("Inp") +29 +30 # (x, y, width, height) +31 x, y = float(msg[0]), float(msg[1]) +32 x1, y1 = x+float(msg[2]), y+float(msg[3]) +33 +34 # Teleoperator Control Logic +35 cx = (x+x1)/2.0 +36 +37 if cx < 320: +38 angular_velocity = -0.5 +39 else: +40 angular_velocity = 0.5 +41 +42 data = [linear_velocity, angular_velocity] +43 outputs.share_array("Out", data) +44 +45 synchronise() @@ -120,34 +126,40 @@

10 11 The output data is a list of the format: `[ linear_velocity, angular_velocity ]`\n 12 This is then shared to the output wire using the `share_array()` function. -13 ''' -14 auto_enable = True -15 try: -16 enable = inputs.read_number("Enable") -17 except Exception: -18 auto_enable = True -19 -20 linear_velocity = parameters.read_number("Linear") -21 -22 while(auto_enable or inputs.read_number('Enable')): -23 msg = inputs.read_array("Inp") -24 -25 # (x, y, width, height) -26 x, y = float(msg[0]), float(msg[1]) -27 x1, y1 = x+float(msg[2]), y+float(msg[3]) -28 -29 # Teleoperator Control Logic -30 cx = (x+x1)/2.0 -31 -32 if cx < 320: -33 angular_velocity = -0.5 -34 else: -35 angular_velocity = 0.5 -36 -37 data = [linear_velocity, angular_velocity] -38 outputs.share_array("Out", data) -39 -40 synchronise() +13 +14 **Inputs**: Bounding Box (x, y, width, height) +15 +16 **Outputs**: `cmd_vel` (linear velocity, angular velocity) +17 +18 **Parameters**: Linear(Linear Velocity) +19 ''' +20 auto_enable = True +21 try: +22 enable = inputs.read_number("Enable") +23 except Exception: +24 auto_enable = True +25 +26 linear_velocity = parameters.read_number("Linear") +27 +28 while(auto_enable or inputs.read_number('Enable')): +29 msg = inputs.read_array("Inp") +30 +31 # (x, y, width, height) +32 x, y = float(msg[0]), float(msg[1]) +33 x1, y1 = x+float(msg[2]), y+float(msg[3]) +34 +35 # Teleoperator Control Logic +36 cx = (x+x1)/2.0 +37 +38 if cx < 320: +39 angular_velocity = -0.5 +40 else: +41 angular_velocity = 0.5 +42 +43 data = [linear_velocity, angular_velocity] +44 outputs.share_array("Out", data) +45 +46 synchronise() @@ -161,6 +173,12 @@

Block Description

The output data is a list of the format: [ linear_velocity, angular_velocity ]

This is then shared to the output wire using the share_array() function.

+ +

Inputs: Bounding Box (x, y, width, height)

+ +

Outputs: cmd_vel (linear velocity, angular velocity)

+ +

Parameters: Linear(Linear Velocity)

diff --git a/blockDocs/Blocks/Threshold.html b/docs/blockDocs/Blocks/Threshold.html similarity index 95% rename from blockDocs/Blocks/Threshold.html rename to docs/blockDocs/Blocks/Threshold.html index cffa5061..b019978a 100644 --- a/blockDocs/Blocks/Threshold.html +++ b/docs/blockDocs/Blocks/Threshold.html @@ -70,28 +70,34 @@

11 `share_image()` function. 12 13 [Further reading](https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html) -14 ''' -15 lower = parameters.read_number("LowerThreshold") -16 upper = parameters.read_number("UpperThreshold") -17 -18 auto_enable = False -19 try: -20 enable = inputs.read_number("Enable") -21 except Exception: -22 auto_enable = True -23 -24 while(auto_enable or inputs.read_number('Enable')): -25 frame = inputs.read_image("Img") -26 if frame is None: -27 continue -28 -29 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -30 (T, thresh) = cv2.threshold(frame, lower, upper, cv2.THRESH_BINARY) -31 output = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR) -32 -33 outputs.share_image('Out', output) +14 +15 **Inputs**: BGR Image +16 +17 **Outputs**: BGR Image +18 +19 **Parameters**: LowerThreshold, UpperThreshold +20 ''' +21 lower = parameters.read_number("LowerThreshold") +22 upper = parameters.read_number("UpperThreshold") +23 +24 auto_enable = False +25 try: +26 enable = inputs.read_number("Enable") +27 except Exception: +28 auto_enable = True +29 +30 while(auto_enable or inputs.read_number('Enable')): +31 frame = inputs.read_image("Img") +32 if frame is None: +33 continue 34 -35 synchronise() +35 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +36 (T, thresh) = cv2.threshold(frame, lower, upper, cv2.THRESH_BINARY) +37 output = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR) +38 +39 outputs.share_image('Out', output) +40 +41 synchronise() @@ -117,28 +123,34 @@

12 `share_image()` function. 13 14 [Further reading](https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html) -15 ''' -16 lower = parameters.read_number("LowerThreshold") -17 upper = parameters.read_number("UpperThreshold") -18 -19 auto_enable = False -20 try: -21 enable = inputs.read_number("Enable") -22 except Exception: -23 auto_enable = True -24 -25 while(auto_enable or inputs.read_number('Enable')): -26 frame = inputs.read_image("Img") -27 if frame is None: -28 continue -29 -30 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -31 (T, thresh) = cv2.threshold(frame, lower, upper, cv2.THRESH_BINARY) -32 output = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR) -33 -34 outputs.share_image('Out', output) +15 +16 **Inputs**: BGR Image +17 +18 **Outputs**: BGR Image +19 +20 **Parameters**: LowerThreshold, UpperThreshold +21 ''' +22 lower = parameters.read_number("LowerThreshold") +23 upper = parameters.read_number("UpperThreshold") +24 +25 auto_enable = False +26 try: +27 enable = inputs.read_number("Enable") +28 except Exception: +29 auto_enable = True +30 +31 while(auto_enable or inputs.read_number('Enable')): +32 frame = inputs.read_image("Img") +33 if frame is None: +34 continue 35 -36 synchronise() +36 frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +37 (T, thresh) = cv2.threshold(frame, lower, upper, cv2.THRESH_BINARY) +38 output = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR) +39 +40 outputs.share_image('Out', output) +41 +42 synchronise() @@ -153,6 +165,12 @@

Block Description

share_image() function.

Further reading

+ +

Inputs: BGR Image

+ +

Outputs: BGR Image

+ +

Parameters: LowerThreshold, UpperThreshold

diff --git a/blockDocs/Blocks/VideoStreamer.html b/docs/blockDocs/Blocks/VideoStreamer.html similarity index 95% rename from blockDocs/Blocks/VideoStreamer.html rename to docs/blockDocs/Blocks/VideoStreamer.html index ff48bf25..49d7791c 100644 --- a/blockDocs/Blocks/VideoStreamer.html +++ b/docs/blockDocs/Blocks/VideoStreamer.html @@ -69,24 +69,30 @@

10 Capturing begins using the `cv2.VideoCapture()` function. 11 The video is then read frame by frame and each frame is shared to the output wire using the 12 `share_image()` function. -13 ''' -14 filepath = parameters.read_string("PathToFile") -15 auto_enable = False -16 try: -17 enable = inputs.read_number("Enable") -18 except Exception: -19 auto_enable = True -20 -21 cap = cv2.VideoCapture(filepath) -22 -23 while(auto_enable or inputs.read_number('Enable') and cap.isOpened()): -24 ret, frame = cap.read() -25 if ret: -26 outputs.share_image('Out', frame) -27 else: -28 cap.set(cv2.CAP_PROP_POS_FRAMES, 0) -29 -30 synchronise() +13 +14 **Inputs**: None +15 +16 **Outputs**: BGR Image +17 +18 **Parameters**: PathToFile +19 ''' +20 filepath = parameters.read_string("PathToFile") +21 auto_enable = False +22 try: +23 enable = inputs.read_number("Enable") +24 except Exception: +25 auto_enable = True +26 +27 cap = cv2.VideoCapture(filepath) +28 +29 while(auto_enable or inputs.read_number('Enable') and cap.isOpened()): +30 ret, frame = cap.read() +31 if ret: +32 outputs.share_image('Out', frame) +33 else: +34 cap.set(cv2.CAP_PROP_POS_FRAMES, 0) +35 +36 synchronise() @@ -111,24 +117,30 @@

11 Capturing begins using the `cv2.VideoCapture()` function. 12 The video is then read frame by frame and each frame is shared to the output wire using the 13 `share_image()` function. -14 ''' -15 filepath = parameters.read_string("PathToFile") -16 auto_enable = False -17 try: -18 enable = inputs.read_number("Enable") -19 except Exception: -20 auto_enable = True -21 -22 cap = cv2.VideoCapture(filepath) -23 -24 while(auto_enable or inputs.read_number('Enable') and cap.isOpened()): -25 ret, frame = cap.read() -26 if ret: -27 outputs.share_image('Out', frame) -28 else: -29 cap.set(cv2.CAP_PROP_POS_FRAMES, 0) -30 -31 synchronise() +14 +15 **Inputs**: None +16 +17 **Outputs**: BGR Image +18 +19 **Parameters**: PathToFile +20 ''' +21 filepath = parameters.read_string("PathToFile") +22 auto_enable = False +23 try: +24 enable = inputs.read_number("Enable") +25 except Exception: +26 auto_enable = True +27 +28 cap = cv2.VideoCapture(filepath) +29 +30 while(auto_enable or inputs.read_number('Enable') and cap.isOpened()): +31 ret, frame = cap.read() +32 if ret: +33 outputs.share_image('Out', frame) +34 else: +35 cap.set(cv2.CAP_PROP_POS_FRAMES, 0) +36 +37 synchronise() @@ -141,6 +153,12 @@

Block Description

Capturing begins using the cv2.VideoCapture() function. The video is then read frame by frame and each frame is shared to the output wire using the share_image() function.

+ +

Inputs: None

+ +

Outputs: BGR Image

+ +

Parameters: PathToFile

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t.EventEmitter,this._idfCache={},this.on("add","remove","update",function(){this._idfCache={}}.bind(this))},t.Index.prototype.on=function(){var e=Array.prototype.slice.call(arguments);return this.eventEmitter.addListener.apply(this.eventEmitter,e)},t.Index.prototype.off=function(e,t){return this.eventEmitter.removeListener(e,t)},t.Index.load=function(e){e.version!==t.version&&t.utils.warn("version mismatch: current "+t.version+" importing "+e.version);var n=new this;n._fields=e.fields,n._ref=e.ref,n.documentStore=t.DocumentStore.load(e.documentStore),n.pipeline=t.Pipeline.load(e.pipeline),n.index={};for(var i in e.index)n.index[i]=t.InvertedIndex.load(e.index[i]);return n},t.Index.prototype.addField=function(e){return this._fields.push(e),this.index[e]=new t.InvertedIndex,this},t.Index.prototype.setRef=function(e){return this._ref=e,this},t.Index.prototype.saveDocument=function(e){return this.documentStore=new t.DocumentStore(e),this},t.Index.prototype.addDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.addDoc(i,e),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));this.documentStore.addFieldLength(i,n,o.length);var r={};o.forEach(function(e){e in r?r[e]+=1:r[e]=1},this);for(var s in r){var u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 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i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();oJekyll Local Installation

\n\n

Prerequisites

\n\n

Installing Ruby on Ubuntu

\n\n

First of all, we need to install all the dependencies typing:

\n\n
sudo apt-get install ruby-full build-essential zlib1g-dev\n
\n\n

After that, we need to set up a gem installation directory for your user account. The following commands will add environment variables to your ~/.bashrc file to configure the gem installation path. Run them now:

\n\n
echo '# Install Ruby Gems to ~/gems' >> ~/.bashrc\necho 'export GEM_HOME="$HOME/gems"' >> ~/.bashrc\necho 'export PATH="$HOME/gems/bin:$PATH"' >> ~/.bashrc\nsource ~/.bashrc\n
\n\n

Finally, we install Jekyll:

\n\n
gem install jekyll bundler\n
\n\n

Notice that we don't use the root user :-)

\n\n

Installing Ruby and Jekyll on Mac OS X

\n\n

Follow the Jekyll page installation guide.

\n\n

Running Jekyll Serve

\n\n

By default, the Jekyll server is launched with the following command (which is the one indicated on your website).

\n\n
bundle exec jekyll serve\n
\n\n

If in the process of building the server there is a dependency problem, for example, there is a missing library to install, it is necessary to delete the Gemfile.lock file so that it is rebuilt with the installed dependency. This list of dependencies is found in the Gemfile file (in Python it would be equivalent to the requirements.txt file) and the version of each of the installed gems (packages) is specified. Having a list of dependencies is important for future updates as well as knowing the libraries needed to run the server. Once the Gemfile.lock file is deleted, the command shown above is launched again and the dependency errors should end.

\n\n

Notes for exercise cards.

\n\n
    \n
  • Teaser Images size: multiple of 600x400px
    • \n
\n\n

FAQ

\n\n
    \n
  • Error building Jekyll server:
    • \n
\n\n
jekyll build --incremental --verbose\n
\n"}, "Blocks.Blur": {"fullname": "Blocks.Blur", "modulename": "Blocks.Blur", "type": "module", "doc": "

\n"}, "Blocks.Blur.main": {"fullname": "Blocks.Blur.main", "modulename": "Blocks.Blur", "qualname": "main", "type": "function", "doc": "

Blurs an Object

\n\n

The object to be blurred is read through the inputs.\nWe have multiple available blurs including Gaussian, Averaging and Median Blur. \nWe can change these blurs by changing the name given in the parameter block

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.

\n\n

Outputs the blurred image through the share_image() function

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image

\n\n

Parameters: BlurType

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Camera": {"fullname": "Blocks.Camera", "modulename": "Blocks.Camera", "type": "module", "doc": "

\n"}, "Blocks.Camera.main": {"fullname": "Blocks.Camera.main", "modulename": "Blocks.Camera", "qualname": "main", "type": "function", "doc": "

Opens your Camera using OpenCV

\n\n

The Camera block opens your webcam using OpenCV and begins capturing the video feed.\nThis video feed is then propagated forward through the share_image() function

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.

\n\n

Inputs: None

\n\n

Outputs: BGR Image

\n\n

Parameters: None

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ColorFilter": {"fullname": "Blocks.ColorFilter", "modulename": "Blocks.ColorFilter", "type": "module", "doc": "

\n"}, "Blocks.ColorFilter.main": {"fullname": "Blocks.ColorFilter.main", "modulename": "Blocks.ColorFilter", "qualname": "main", "type": "function", "doc": "

Filters Colour according to given parameters

\n\n

The image to be filtered is read through the inputs.\nWe can give a Filter between any HSV range by changing the range of the parameters LowerRGB and UpperRGB.

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire .

\n\n

Here the image is tranformed from BGR to HSV and then the filter is applied through the cv2.inRange()\nfunction. Finally the filtered image is overlayed on the orignal by the means of the\ncv2.bitwise_and() function. This filtered image is then shared through the share_image() function.

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image

\n\n

Parameters: LowerHSV, UpperHSV

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ContourDetector": {"fullname": "Blocks.ContourDetector", "modulename": "Blocks.ContourDetector", "type": "module", "doc": "

\n"}, "Blocks.ContourDetector.main": {"fullname": "Blocks.ContourDetector.main", "modulename": "Blocks.ContourDetector", "qualname": "main", "type": "function", "doc": "

Detects Contours in an Image

\n\n

The image in which contours are to be detected is read through the inputs.\nFirst the image is converted from BGR to Grayscale, the thresholding values are 60, 255.\nThe function used is cv2.threshold().\nOnce it is thersholded, the contours are detected in the image using cv2.findContours()

\n\n

The program then detects the biggest contour present in the image and finds the co-ordinates of its center\nusing the cv2.moments() function.

\n\n

This co-ords of the center alongwith the contour characteristics are part of the output array.\nTHis array is shared through share_array()

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.

\n\n

Further reading

\n\n

Inputs: BGR Image

\n\n

Outputs: Array [x, y, width, height, angle of rotation], BGR Image

\n\n

Parameters: None

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Cropper": {"fullname": "Blocks.Cropper", "modulename": "Blocks.Cropper", "type": "module", "doc": "

\n"}, "Blocks.Cropper.main": {"fullname": "Blocks.Cropper.main", "modulename": "Blocks.Cropper", "qualname": "main", "type": "function", "doc": "

Crops an Image

\n\n

The image which is to be cropped is read through the inputs using the inputs.read_image() function.\nThe parameters ask for x, y, w, h

\n\n
x: x co-ordinate of where the crop should start\n\ny: y co-ordinate of where the crop should start\n\nw: width of the crop\n\nh: height of the crop\n\n
\n\n

Image is cropped by simple list slicing.

\n\n

while loop is the part of the program that is executed continuously.\nIt is enabled by default but can be disabled by passing in 0 through the enable wire.\nOutput is shared via share_image()

\n\n

Inputs: BGR Image

\n\n

Outputs: Resized BGR Image

\n\n

Parameters: x, y, width, height

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Dilation": {"fullname": "Blocks.Dilation", "modulename": "Blocks.Dilation", "type": "module", "doc": "

\n"}, "Blocks.Dilation.main": {"fullname": "Blocks.Dilation.main", "modulename": "Blocks.Dilation", "qualname": "main", "type": "function", "doc": "

Dilates an Image

\n\n

You can specify the kernel dimensions and number of iterations in the parameters.

\n\n

We first convert the colour of the image from BGR to GRAY then we apply dilation on it \nusing the cv2.dilate() function.

\n\n

Finaly we convert from GRAY back to BGR and output the image through the share_image() function.

\n\n

Further reading

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image

\n\n

Parameters: Kernel, Iterations

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.EdgeDetector": {"fullname": "Blocks.EdgeDetector", "modulename": "Blocks.EdgeDetector", "type": "module", "doc": "

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Detects Edges in an Image

\n\n

It takes in two parameters Lower and Upper. These parameters are used as the limits in Canny Edge \nDetection. First we convert the input BGR image to GRAY. Next we apply Canny Edge Detection via the \ncv2.Canny() function. The resulting image is then converted back to BGR.

\n\n

This image is then shared to the wire via the share_image() function.

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image

\n\n

Parameters: Lower, Upper (Threshold values)

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Erosion": {"fullname": "Blocks.Erosion", "modulename": "Blocks.Erosion", "type": "module", "doc": "

\n"}, "Blocks.Erosion.main": {"fullname": "Blocks.Erosion.main", "modulename": "Blocks.Erosion", "qualname": "main", "type": "function", "doc": "

Erodes an Image

\n\n

You can specify the kernel dimensions and number of iterations in the parameters.

\n\n

We first convert the colour of the image from BGR to GRAY then we apply erosion on it \nusing the cv2.erode() function.

\n\n

Finaly we convert from GRAY back to BGR and output the image through the share_image() function.

\n\n

Further reading

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image

\n\n

Parameters: Kernel, Iterations

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.FaceDetector": {"fullname": "Blocks.FaceDetector", "modulename": "Blocks.FaceDetector", "type": "module", "doc": "

\n"}, "Blocks.FaceDetector.main": {"fullname": "Blocks.FaceDetector.main", "modulename": "Blocks.FaceDetector", "qualname": "main", "type": "function", "doc": "

Detects Faces in the Image

\n\n

This block applies a Harr Cascade based model on the input image. \nIt takes as an input the parameter BoxOrImage. This parameter has two possible values:\nBoxOrImage: image / box

\n\n

If image is given: The output is the image passed in with a bounding box around the area where \na face is detected. Image is shared through the share_image() function.

\n\n

Else if box is given, the output is the co-ordinates of the bounding box in the form of an array. It \nis chared through the share_array() function.

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image with Bounding Boxes

\n\n

Parameters: BoxOrImage ('box' for Bounding Boxes, 'image' for Image with Detections)

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.IMU": {"fullname": "Blocks.IMU", "modulename": "Blocks.IMU", "type": "module", "doc": "

\n"}, "Blocks.IMU.callback": {"fullname": "Blocks.IMU.callback", "modulename": "Blocks.IMU", "qualname": "callback", "type": "function", "doc": "

The callback function is required by the Subscriber to the ROSTopic. This callback function reads the orientation list from the IMU\nIt then converts the quaternion angles to euler ones. This gives us the roll, pitch and yaw of the body.\nWe convert these radian values to degrees to get the orientation of the body.

\n\n

Aside from these values the IMU also gives us the angular velocity of the body.

\n\n

All of these values are stored in the global data variable of the block.

\n", "signature": "(msg)", "funcdef": "def"}, "Blocks.IMU.main": {"fullname": "Blocks.IMU.main", "modulename": "Blocks.IMU", "qualname": "main", "type": "function", "doc": "

Reads IMU sensor data

\n\n

This is a specialized block used to read IMU sensor data.

\n\n

It reads the ROSTopic name from the ROSTopic parameter. Default is mavros/imu/data.

\n\n

This data is sent to the callback function which converts the orientation list obtained into roll, pitch and yaw for the\nrobot that the IMU is present on. Alongwith orientation, it also gives the angular velocity of the robot.\nThis data is shared in the form of an array using the share_array() function.

\n\n

Inputs: None

\n\n

Outputs: Array [Roll, Pitch , Yaw, Angular Velocity in X, Angular Velocity in Y, Angular Velocity in Z]

\n\n

Parameters: ROSTopic

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.ImageRead": {"fullname": "Blocks.ImageRead", "modulename": "Blocks.ImageRead", "type": "module", "doc": "

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Reads an Image from a Specified Path

\n\n

This box reads an image from a given file path. The path to be specified is written in the parameter\nImagePath.

\n\n

It is read through the cv2.imread() function and shared through the share_image() function.

\n\n

Inputs: None

\n\n

Outputs: BGR Image

\n\n

Parameters: ImagePath

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Publishes Twist Command to drive Motors

\n\n

It publishes to the ROSTopic name from the ROSTopic parameter. Default is /robot/cmd_vel.

\n\n

It reads an array as an input by the read_array() function.

\n\n

This is assumed to be of the format [ linear_velocity, angular_velocity ].

\n\n

This data is then converted into a Twist() message with the linear.x = linear_velocity and angular.z = angular_velocity

\n\n

The data is then published continuously

\n\n

Inputs: cmd_vel (Linear Velocity, Angular Velocity)

\n\n

Outputs: None

\n\n

Parameters: ROSTopic

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Reads Data from An Odometer

\n\n

It reads the ROSTopic name from the ROSTopic parameter.\nIt then initializes a Subscriber to subscribe to that ROSTopic, once the data is obtained through the callback\nfunction, it is formatted into an array with the format: [ x, y, yaw ]

\n\n

This data is then shared to the wire using the share_array() function.

\n\n

Inputs: None

\n\n

Outputs: Array [X, Y, Yaw]

\n\n

Parameters: ROSTopic

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Applies PID for a Given Error Value

\n\n

The error is read as an input from the inputs wire.

\n\n

The Kp, Ki, and Kd parameters are read from the parameters of the same name.\nOnce there it applies the PID technique to the error variable in order to minimize it.

\n\n

The resulting values are shared through the share_array() function.

\n\n

Inputs: Error

\n\n

Outputs: cmd_vel (Linear Velocity, Angular Velocity)

\n\n

Parameters: Kp, Ki, Kd

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Gets Image from a ROSCamera

\n\n

The camera topic is read from the ROSTopic parameter, by default it is /robot/camera

\n\n

The image message is converted to OpenCV compatible format via the imgmsg_to_cv2() function.

\n\n

This is then shared ahead using the share_image() function.

\n\n

Inputs: None

\n\n

Outputs: BGR Image

\n\n

Parameters: ROSTopic

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Screen": {"fullname": "Blocks.Screen", "modulename": "Blocks.Screen", "type": "module", "doc": "

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Displays the given Image

\n\n

Takes an image as an input and displays it on the user's screen.\nThe cv2.imshow() function is used in order to display the image.

\n\n

Inputs: BGR Image

\n\n

Outputs: None

\n\n

Parameters: None

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Used to Imitate the Movements of the Operator

\n\n

It takes in an array as input, depending on the array variables, it will output another array\ncontaining the velocity it deems appropriate.\nThe linear_velocity can be given via the Linear parameter.

\n\n

The output data is a list of the format: [ linear_velocity, angular_velocity ]

\n\n

This is then shared to the output wire using the share_array() function.

\n\n

Inputs: Bounding Box (x, y, width, height)

\n\n

Outputs: cmd_vel (linear velocity, angular velocity)

\n\n

Parameters: Linear(Linear Velocity)

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.Threshold": {"fullname": "Blocks.Threshold", "modulename": "Blocks.Threshold", "type": "module", "doc": "

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Thresholds an Image

\n\n

THis block reads the parameters LowerThreshold and UpperThreshold.

\n\n

Based on these values it converts the input image form BGR into GRAY and applies the cv2.threshold() function on it.

\n\n

The image is then converted back into BGR and shared to the output wire using the\nshare_image() function.

\n\n

Further reading

\n\n

Inputs: BGR Image

\n\n

Outputs: BGR Image

\n\n

Parameters: LowerThreshold, UpperThreshold

\n", "signature": "(inputs, outputs, parameters, synchronise)", "funcdef": "def"}, "Blocks.VideoStreamer": {"fullname": "Blocks.VideoStreamer", "modulename": "Blocks.VideoStreamer", "type": "module", "doc": "

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Streams Video from File

\n\n

The filepath of your video is given in the PathToFile parameter.\nNote: that this file path is relative to the modules folder of the final built application.

\n\n

Capturing begins using the cv2.VideoCapture() function. \nThe video is then read frame by frame and each frame is shared to the output wire using the\nshare_image() function.

\n\n

Inputs: None

\n\n

Outputs: BGR Image

\n\n

Parameters: PathToFile

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1.4142135623730951}}, "df": 2}}}}}, "p": {"docs": {"Blocks.PID.main": {"tf": 1.4142135623730951}}, "df": 1}, "i": {"docs": {"Blocks.PID.main": {"tf": 1.4142135623730951}}, "df": 1}, "d": {"docs": {"Blocks.PID.main": {"tf": 1.4142135623730951}}, "df": 1}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; + + // mirrored in build-search-index.js (part 1) + // Also split on html tags. this is a cheap heuristic, but good enough. + elasticlunr.tokenizer.setSeperator(/[\s\-.;&_'"=,()]+|<[^>]*>/); + + let searchIndex; + if (docs._isPrebuiltIndex) { + console.info("using precompiled search index"); + searchIndex = elasticlunr.Index.load(docs); + } else { + console.time("building search index"); + // mirrored in build-search-index.js (part 2) + searchIndex = elasticlunr(function () { + this.pipeline.remove(elasticlunr.stemmer); + this.pipeline.remove(elasticlunr.stopWordFilter); + this.addField("qualname"); + this.addField("fullname"); + this.addField("annotation"); + this.addField("default_value"); + this.addField("signature"); + this.addField("bases"); + this.addField("doc"); + this.setRef("fullname"); + }); + for (let doc of docs) { + searchIndex.addDoc(doc); + } + console.timeEnd("building search index"); + } + + return (term) => searchIndex.search(term, { + fields: { + qualname: {boost: 4}, + fullname: {boost: 2}, + annotation: {boost: 2}, + default_value: {boost: 2}, + signature: {boost: 2}, + bases: {boost: 2}, + doc: {boost: 1}, + }, + expand: true + }); +})(); \ No newline at end of file diff --git a/frontend/src/components/blocks/basic/code/code-widget.tsx b/frontend/src/components/blocks/basic/code/code-widget.tsx index 9382950b..340d4e86 100644 --- a/frontend/src/components/blocks/basic/code/code-widget.tsx +++ b/frontend/src/components/blocks/basic/code/code-widget.tsx @@ -201,7 +201,7 @@ export class CodeBlockWidget extends React.Component = (event) => { const element = event.target as HTMLDivElement; - this.props.node.setSize(element.clientWidth, element.clientHeight); + this.props.node.setSize(Math.max(element.clientWidth, 300), Math.max(element.clientHeight, 300)); }