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@@ -392,8 +392,7 @@ int main()
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size_t size{ 0 };
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-
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-
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+ // 读取engine文件
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std::ifstream file("yolov5-crowd-n.engine", std::ios::binary);
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if (file.good()) {
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@@ -433,11 +432,11 @@ int main()
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// generate input data
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-
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float data[BATCH_SIZE * 3 * IN_H * IN_W];
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// Run inference
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int num_total = 3 * (IN_H/4 * IN_W/4 + IN_H/8 * IN_W/8 + IN_H/16 * IN_W/16) * 6;
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+ // 存储推理结果
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float prob[num_total];
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printf("num_total: %d\n", num_total);
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@@ -465,36 +464,19 @@ int main()
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float height_scale = height / 640.0;
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float width_scale = width / 640.0;
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- doInference(*context, data, prob, BATCH_SIZE);
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- // 推理结果
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- // float *prob_ptr = prob;
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- // int count = 0;
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- // for (int i = 0; i < num_total / 6; i++)
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- // {
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- // {
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- // for (int j = 0; j < 6; j++)
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- // {
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- // //printf("%f ", prob_ptr[j]);
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- // count++;
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- // }
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- // //printf("\n");
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-
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- // }
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- // prob_ptr += 6;
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+ doInference(*context, data, prob, BATCH_SIZE);
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- // }
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- // printf("count: %d\n", count);
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- printf("inference done");
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+ printf("inference done");
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- // Destroy the engine
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+ // Destroy the engine
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- context->destroy();
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+ context->destroy();
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- engine->destroy();
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+ engine->destroy();
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- runtime->destroy();
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+ runtime->destroy();
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// 将输出根据grid和anchor进行计算，得到预测框的坐标和置信度
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float* result = postprocess(prob); // prob -> 604800
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@@ -526,7 +508,9 @@ int main()
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// 根据置信度 获得有效框
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vector<vector<float>> info = get_info(result, 0.25, 6);
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+ // 将推理的xywh 转换为原图中的 xyxy
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info_simplify(info, width_scale, height_scale);
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+ // 将推理结果按类别分割
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vector<vector<vector<float>>> info_split = split_info(info);
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printf("info size: %ld\n", info_split.size());
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clshuaige