MLKit's on-device Label Detection is very poor when compared to TensorFlow Label detection. MLKit on-device model is not able to predict the images accurately .
When I debugged the both apps, I found that MLKit uses preview ImageFormat as NV21 and TensorFlow is using YUV_420_888 Image format.
And I even tried using tflite model from TensorFlow app as a custom model in the MLKit android app and I see the predictions results are not satisfactory (the results are same as ML Kits on device
Label Detection)
You can see the prediction results of MLKit and TensorFlow apps on water bottle and Laptop input Images.
MLKit's on-device Label Detection is very poor when compared to TensorFlow Label detection. MLKit on-device model is not able to predict the images accurately .
When I debugged the both apps, I found that MLKit uses preview ImageFormat as NV21 and TensorFlow is using YUV_420_888 Image format.
ML kit android app https://github.com/firebase/quickstart-android
TensorFlow android app https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android
And I even tried using tflite model from TensorFlow app as a custom model in the MLKit android app and I see the predictions results are not satisfactory (the results are same as ML Kits on device Label Detection)
You can see the prediction results of MLKit and TensorFlow apps on water bottle and Laptop input Images.
