(DO NOT MERGE) Test link

.github/markdown-link-check.json

@@ -0,0 +1,13 @@
+{
+    "projectBaseUrl":"${workspaceFolder}",
+    "ignorePatterns": [
+      {
+        "pattern": "^https://monai.io"
+      }
+    ],
+    "timeout": "20s",
+    "retryOn429": true,
+    "retryCount": 3,
+    "fallbackRetryDelay": "30s",
+    "aliveStatusCodes": [200, 202, 403]
+}

.github/workflows/check-links.yml

@@ -0,0 +1,27 @@
+name: Check Markdown Links
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  markdown-link-check:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository content
+        uses: actions/checkout@v3
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v3
+        with:
+          node-version: '18'
+
+      - name: Install markdown-link-check
+        run: npm install -g markdown-link-check
+
+      - name: Check for broken links
+        run: find . -name "*.md" | xargs -I {} markdown-link-check {} --config .github/markdown-link-check.json

monai_vila2d/README.md

@@ -71,7 +71,7 @@ An interactive demo is provided in ...
 To prepare the datasets for training and evaluation, follow the instructions in [data_prepare](./data_prepare).
 
 ## Training
-To replicate our fine-tuning procedure, utilize the provided [scripts](./scripts).
+To replicate our fine-tuning procedure, utilize the provided scripts.
 
 ## Evaluation
 To evaluate a model on the above benchmarks, follow the instructions in [eval](./eval/README.md)

monai_vila2d/data_prepare/README.md

@@ -28,9 +28,9 @@ experts
 
 | Dataset   | QA/Text Pairs  | Images    | Link |
 |-----------|-----------|-----------|------|
-| PathVQA   | ~32,000   | ~4,000    | [PathVQA](https://github.com/UCSD-AI4H/PathVQA) |
-| RadVQA    | ~25,000   | ~7,000    | [RadVQA](https://github.com/abachaa/VQA-Med-2019) |
-| SLAKE     | ~45,000   | ~14,000   | [SLAKE](https://github.com/SLAKE-SLAKE/SLAKE) |
+| PathVQA   | ~32,000   | ~4,000    | [PathVQA](https://huggingface.co/datasets/flaviagiammarino/path-vqa) |
+| RadVQA    | ~25,000   | ~7,000    | [RadVQA](https://osf.io/89kps/) |
+| SLAKE     | ~45,000   | ~14,000   | [SLAKE](https://www.med-vqa.com/slake/) |
 | Medical-Diff-VQA | ~429,000  | 129,232  | [MIMIC-VQA](https://physionet.org/content/medical-diff-vqa/1.0.0) |
 | MIMIC-CXR-JPG | 270,784 | 270,784 | [MIMIC-CXR-JPG](https://physionet.org/content/mimic-cxr-jpg/2.1.0/) |
 | ChestXRay14 | 1,962 | 1,962 | [nih-chest-xray](https://cloud.google.com/healthcare-api/docs/resources/public-datasets/nih-chest#additional_labels) |

monai_vila2d/data_prepare/vqa/README.md

@@ -31,11 +31,11 @@ python slake_instruct_data_generate.py \
 Example command to run generate the instruction training data json file for PathVQA dataset:
 
 ```
-python pathvqa_instruct_data_generate.py \
-    --train_pkl /path/to/train_vqa.pkl \
-    --val_pkl /path/to/val_vqa.pkl \
-    --test_pkl /path/to/test_vqa.pkl \
-    --output_json /path/to/output/merged_pathvqa_instruct.json
+python pathvqa_instruction_gen_parquet.py --input_path /path/to/input/parquet/files --output_path /path/to/output/processed/dataset
+```
+Please make sure that the .csv files were succesfully generated from the prior command before running the next command
+```
+python pathvqa_instruction_generate.py --input_dir /path/to/output/processed/dataset --output_dir /path/to/output_directory
 ```
 
 ### MIMIC-VQA