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Arresttb Model latest

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This commit is contained in:
Ramandeep
2021-09-21 00:44:52 +05:30
parent 35fbea548a
commit 4db4918e39
5 changed files with 27 additions and 8 deletions
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app/src/main/assets/model.tflite
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26
app/src/main/java/in/sminnovations/arrest_tb/TensorFlowImageClassifier.java
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@@ -28,9 +28,14 @@ public class TensorFlowImageClassifier implements Classifier {
private static final int PIXEL_SIZE = 3;
private static final float THRESHOLD = 0.1f;
private static final int IMAGE_MEAN = 128;
private static final float IMAGE_STD = 128.0f;
private Interpreter interpreter;
private int inputSize;
private List<String> labelList;
private boolean quant;
private TensorFlowImageClassifier() {
@@ -52,9 +57,13 @@ public class TensorFlowImageClassifier implements Classifier {
@Override
public List<Recognition> recognizeImage(Bitmap bitmap) {
ByteBuffer byteBuffer = convertBitmapToByteBuffer(bitmap);
/* ByteBuffer byteBuffer = convertBitmapToByteBuffer(bitmap);
byte[][] result = new byte[1][labelList.size()];
interpreter.run(byteBuffer, result);
return getSortedResult(result);
return getSortedResult(result);*/
float [][] result = new float[1][labelList.size()];
interpreter.run(byteBuffer, result);
return getSortedResultFloat(result);
}
@Override
@@ -84,7 +93,8 @@ public class TensorFlowImageClassifier implements Classifier {
}
private ByteBuffer convertBitmapToByteBuffer(Bitmap bitmap) {
ByteBuffer byteBuffer = ByteBuffer.allocateDirect(BATCH_SIZE * inputSize * inputSize * PIXEL_SIZE);
ByteBuffer byteBuffer = ByteBuffer.allocateDirect(4 * BATCH_SIZE * inputSize * inputSize * PIXEL_SIZE);
byteBuffer.order(ByteOrder.nativeOrder());
int[] intValues = new int[inputSize * inputSize];
bitmap.getPixels(intValues, 0, bitmap.getWidth(), 0, 0, bitmap.getWidth(), bitmap.getHeight());
@@ -92,16 +102,18 @@ public class TensorFlowImageClassifier implements Classifier {
for (int i = 0; i < inputSize; ++i) {
for (int j = 0; j < inputSize; ++j) {
final int val = intValues[pixel++];
byteBuffer.put((byte) ((val >> 16) & 0xFF));
byteBuffer.put((byte) ((val >> 8) & 0xFF));
byteBuffer.put((byte) (val & 0xFF));
byteBuffer.putFloat((((val >> 16) & 0xFF)-IMAGE_MEAN)/IMAGE_STD);
byteBuffer.putFloat((((val >> 8) & 0xFF)-IMAGE_MEAN)/IMAGE_STD);
byteBuffer.putFloat((((val) & 0xFF)-IMAGE_MEAN)/IMAGE_STD);
}
}
return byteBuffer;
}
@SuppressLint("DefaultLocale")
private List<Recognition> getSortedResult(byte[][] labelProbArray) {
private List<Recognition> getSortedResultFloat(float[][] labelProbArray) {
PriorityQueue<Recognition> pq =
new PriorityQueue<>(
@@ -114,7 +126,7 @@ public class TensorFlowImageClassifier implements Classifier {
});
for (int i = 0; i < labelList.size(); ++i) {
float confidence = (labelProbArray[0][i] & 0xff) / 255.0f;
float confidence = labelProbArray[0][i];
if (confidence > THRESHOLD) {
pq.add(new Recognition("" + i,
labelList.size() > i ? labelList.get(i) : "unknown",