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Have you reproduced the bug with TensorFlow Nightly?
No
Source
source
TensorFlow version
tf 2.16.1
Custom code
Yes
OS platform and distribution
Android
Mobile device
Some Android Devices
Python version
No response
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
I converted the YOLO11n model to TensorFlow Lite (TFLite) and used it in my Android app. However, my app crashes on some Android devices, and the following error appears in Logcat: Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR)
To create the TFLite model, I tried various conversion options in YOLO, as shown below:
# Load a model
model = YOLO("yolo11n.pt") # load an official model
# model = YOLO("path/to/best.pt") # load a custom trained model
# Export the model
# model.export(format="tflite", half = True, batch = 4)
model.export(format="tflite", half = True, int8 = True)
Despite testing different configurations, the app consistently crashes when using the model in GPU mode.
Interestingly, this issue only occurs with the YOLO11n TFLite model. When I use other TFLite models, such as YOLOv8n or YOLOv9t, everything works fine. This suggests there may be a compatibility issue or a bug in the TFLite Android library specific to the YOLO11n model.
Standalone code to reproduce the issue
I'm testing my YOLO TFLite model with the code in this repository:https://github.com/surendramaran/YOLO/tree/main/YOLOv9-Object-Detector-Android-Tflite
Relevant log output
No response
The text was updated successfully, but these errors were encountered:
Original Issue: App Crash with YOLO11n TFLite Model on Android. Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR) on GPU mode
Original Author: @emoo44566
Issue type
Bug
Have you reproduced the bug with TensorFlow Nightly?
No
Source
source
TensorFlow version
tf 2.16.1
Custom code
Yes
OS platform and distribution
Android
Mobile device
Some Android Devices
Python version
No response
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
I converted the YOLO11n model to TensorFlow Lite (TFLite) and used it in my Android app. However, my app crashes on some Android devices, and the following error appears in Logcat:
Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR)
To create the TFLite model, I tried various conversion options in YOLO, as shown below:
Despite testing different configurations, the app consistently crashes when using the model in GPU mode.
Interestingly, this issue only occurs with the YOLO11n TFLite model. When I use other TFLite models, such as YOLOv8n or YOLOv9t, everything works fine. This suggests there may be a compatibility issue or a bug in the TFLite Android library specific to the YOLO11n model.
Standalone code to reproduce the issue
Relevant log output
No response
The text was updated successfully, but these errors were encountered: