package com.rockchip.gpadc.demo.yolo;
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import android.graphics.RectF;
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import android.util.Log;
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import com.rockchip.gpadc.demo.InferenceResult;
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import com.rockchip.gpadc.demo.InferenceResult.OutputBuffer;
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import com.rockchip.gpadc.demo.InferenceResult.Recognition;
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import com.rockchip.gpadc.demo.InferenceResult.DetectResultGroup;
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import java.io.IOException;
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import java.util.ArrayList;
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/**
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* Created by randall on 18-4-18.
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*/
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public class InferenceWrapper {
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private final String TAG = "rkyolo.InferenceWrapper";
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static {
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System.loadLibrary("rknn4j");
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}
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OutputBuffer mOutputs;
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ArrayList<Recognition> mRecognitions = new ArrayList<Recognition>();
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DetectResultGroup mDetectResults;
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public int OBJ_NUMB_MAX_SIZE = 64;
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// public int inf_count = 0;
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// public int post_count = 0;
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// public long inf_time = 0;
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// public long post_time = 0;
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public InferenceWrapper() {
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}
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public int initModel(int im_height, int im_width, int im_channel, String modelPath) throws Exception {
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mOutputs = new InferenceResult.OutputBuffer();
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mOutputs.mGrid0Out = new byte[255 * 80 * 80];
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mOutputs.mGrid1Out = new byte[255 * 40 * 40];
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mOutputs.mGrid2Out = new byte[255 * 20 * 20];
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if (navite_init(im_height, im_width, im_channel, modelPath) != 0) {
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throw new IOException("rknn init fail!");
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}
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return 0;
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}
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public void deinit() {
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native_deinit();
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mOutputs.mGrid0Out = null;
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mOutputs.mGrid1Out = null;
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mOutputs.mGrid2Out = null;
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mOutputs = null;
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}
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public InferenceResult.OutputBuffer run(byte[] inData) {
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// long startTime = System.currentTimeMillis();
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// long endTime;
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native_run(inData, mOutputs.mGrid0Out, mOutputs.mGrid1Out, mOutputs.mGrid2Out);
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// this.inf_count += 1;
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// endTime = System.currentTimeMillis();
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// this.inf_time += (endTime - startTime);
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// if (this.inf_count >= 100) {
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// float inf_avg = this.inf_time * 1.0f / this.inf_count;
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// Log.w(TAG, String.format("inference avg cost: %.5f ms", inf_avg));
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// this.inf_count = 0;
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// this.inf_time = 0;
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// }
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// Log.i(TAG, String.format("inference count: %d", this.inf_count));
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return mOutputs;
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}
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public ArrayList<InferenceResult.Recognition> postProcess(InferenceResult.OutputBuffer outputs) {
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ArrayList<Recognition> recognitions = new ArrayList<Recognition>();
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mDetectResults = new DetectResultGroup();
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mDetectResults.count = 0;
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mDetectResults.ids = new int[OBJ_NUMB_MAX_SIZE];
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mDetectResults.scores = new float[OBJ_NUMB_MAX_SIZE];
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mDetectResults.boxes = new float[4 * OBJ_NUMB_MAX_SIZE];
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if (null == outputs || null == outputs.mGrid0Out || null == outputs.mGrid1Out
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|| null == outputs.mGrid2Out) {
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return recognitions;
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}
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// long startTime = System.currentTimeMillis();
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// long endTime;
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int count = native_post_process(outputs.mGrid0Out, outputs.mGrid1Out, outputs.mGrid2Out,
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mDetectResults.ids, mDetectResults.scores, mDetectResults.boxes);
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if (count < 0) {
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Log.w(TAG, "post_process may fail.");
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mDetectResults.count = 0;
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} else {
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mDetectResults.count = count;
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}
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// Log.i(TAG, String.format("Detected %d objects", count));
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// this.post_count += 1;
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// Log.i(TAG, String.format("post count: %d", this.post_count));
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for (int i = 0; i < count; ++i) {
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RectF rect = new RectF();
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rect.left = mDetectResults.boxes[i*4+0];
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rect.top = mDetectResults.boxes[i*4+1];
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rect.right = mDetectResults.boxes[i*4+2];
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rect.bottom = mDetectResults.boxes[i*4+3];
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Recognition recog = new InferenceResult.Recognition(mDetectResults.ids[i],
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mDetectResults.scores[i], rect);
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recognitions.add(recog);
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}
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// endTime = System.currentTimeMillis();
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// this.post_time += (endTime - startTime);
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// if (this.post_count >= 100) {
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// float post_avg = this.post_time * 1.0f / this.post_count;
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// Log.w(TAG, String.format("post process avg cost: %.5f ms", post_avg));
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// this.post_time = 0;
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// this.post_count = 0;
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// }
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return recognitions;
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}
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private native int navite_init(int im_height, int im_width, int im_channel, String modelPath);
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private native void native_deinit();
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private native int native_run(byte[] inData, byte[] grid0Out, byte[] grid1Out, byte[] grid2Out);
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private native int native_post_process(byte[] grid0Out, byte[] grid1Out, byte[] grid2Out,
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int[] ids, float[] scores, float[] boxes);
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}
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