Issue
This Content is from Stack Overflow. Question asked by Riyas PK
I converted a keras model in to tenserflow lite model using the code
model = tf.keras.models.load_model('liveness.model')
# Convert the model.
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
# Save the model.
with open('model.tflite', 'wb') as f:
f.write(tflite_model)
But it not working and always giving same output for all inputs. I tried with android i am adding my android code as well.
bitmap = getBitmapImageWith32();
int inputSize=32;
int OUTPUT_SIZE=2;
float[][] embeedings;
int[] intValues;
ByteBuffer imgData = ByteBuffer.allocateDirect(1 * inputSize * inputSize * 3 * 4);
imgData.order(ByteOrder.nativeOrder());
bitmap.getPixels(intValues, 0, bitmap.getWidth(), 0, 0, bitmap.getWidth(), bitmap.getHeight());
imgData.rewind();
int p = 0;
for (int i = 0; i < inputSize; ++i) {
for (int j = 0; j < inputSize; ++j) {
int pixelValue = intValues[pixel++];
imgData.putFloat((((pixelValue >> 16) & 0xFF) - IMAGE_MEAN) / IMAGE_STD);
imgData.putFloat((((pixelValue >> 8) & 0xFF) - IMAGE_MEAN) / IMAGE_STD);
imgData.putFloat(((pixelValue & 0xFF) - IMAGE_MEAN) / IMAGE_STD);
p++;
}
}
Object[] inputArray = {imgData};
Map<Integer, Object> outputMap = new HashMap<>();
embeedings = new float[1][OUTPUT_SIZE];
outputMap.put(0, embeedings);
tfLiteLiveness.runForMultipleInputsOutputs(inputArray, outputMap);
Log.e("first val", String.valueOf(embeedings[0][0]));
Log.e("second val", String.valueOf(embeedings[0][1]));
This is the model I am using
https://github.com/birdowl21/Face-Liveness-Detection-Anti-Spoofing-Web-App/blob/main/liveness.model
Solution
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