Dear ST Community,
I’m currently working with an ALIENTEK STM32MP257 development board and ran into an issue when deploying a model converted via the ST Edge AI online tool.
The original model is a plant disease recognition model from the ST model zoo (in .tflite format). I used the ST Edge AI webpage to convert it to an .nb model for deployment on my STM32MP257 board. However, when I test the converted .nb model, the inference output is unexpected: it only predicts two classes — “Background_without_leaves” and “Corn__Northern_Leaf_Blight” — both with relatively high confidence. This happens regardless of the input image.
In contrast, when I run inference directly using the original .tflite file on the same test images, the results are correct and show proper class diversity.
I double-checked my test code and also consulted AI assistance, which suggested that the converted .nb model might be problematic.
I’ve attached a compressed file containing my inference code and the model files for reference. Could someone kindly help verify the converted .nb model, or possibly provide a correctly converted .nb file for this plant disease recognition model? Any guidance would be greatly appreciated.
Thank you very much for your time!
Best regards,
[WangWei]
