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I have trained a MobileNetV2 model on a custom dataset following the example configurations. Testing the quantized model on the dataset gives good results reaching above 90% in accuracy. However, when I deploy the model using Sense Craft AI on Grove Vision AI V2, I get a 99% probability on one of the classes all the time, except when I black out the camera it drops down to ~83%. I uploaded the same model tflite model to Edge Impulse and tested the model on few images of the dataset and it appeared to work correctly when the input was set to values 0..1 . Is it possible that the model is performing poorly on camera images because of a wrong preprocessing withing the Grove firmware?
The text was updated successfully, but these errors were encountered:
I have trained a MobileNetV2 model on a custom dataset following the example configurations. Testing the quantized model on the dataset gives good results reaching above 90% in accuracy. However, when I deploy the model using Sense Craft AI on Grove Vision AI V2, I get a 99% probability on one of the classes all the time, except when I black out the camera it drops down to ~83%. I uploaded the same model tflite model to Edge Impulse and tested the model on few images of the dataset and it appeared to work correctly when the input was set to values 0..1 . Is it possible that the model is performing poorly on camera images because of a wrong preprocessing withing the Grove firmware?
The text was updated successfully, but these errors were encountered: