Comments (2)
I have also faced the same issue, I changed the putFloat
into put
and typecasted the value passed into (byte) imgData.put((byte) ((((val >> 16) & 0xFF)-IMAGE_MEAN)/IMAGE_STD));
App stopped crashing but the output model predicts is very very wrong.
from tensorflow-for-poets-2.
I used this tutorial instead: https://www.tensorflow.org/lite/models/image_classification/android
And it works no problem, just swap the tflite and txt file exported from AutoML into the assets folder again and change the ClassifierQuantizedModel to point to the custom file instead of the pregenerated ones.
from tensorflow-for-poets-2.
Related Issues (20)
- ERROR : python -m scripts.retrain -h HOT 3
- broken link to "quantized version of demo app" HOT 1
- scripts.label_image tensorflow 2.0 HOT 1
- Has no images in the category testing for retrain.py file
- Missing requirement for installing TensorFlow version. HOT 1
- Retrain from deeper within the architecture (include more layers)
- quantization instruction not working
- Need help on understanding "convertBitmapToByteBuffer" and "applyfilter"
- A lot of deprecated things and critical error in the end HOT 1
- unable to convert to .tflite
- Failed Building customized app 'E/AndroidRuntime: FATAL EXCEPTION: CameraBackground' HOT 1
- Cannot retrain data using scripts.retrain
- ERROR: tensorflow:No valid folders of images found at training_data/breadboard
- Getting Error While Converting to optimized tflite model
- Detecting other objects similar to trained model HOT 3
- Can't not build android app
- Takes too long time label_image.py
- Cant find bottleneck file in tf_file
- How to change the code to facilitate binary classification?
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