Recator draw imprecise face

src/nv_infer_server_manager.cpp

@@ -248,79 +248,82 @@ GstPadProbeReturn NvInferServerManager::pgie_pad_buffer_probe(
             NvDsUserMeta *user_meta = (NvDsUserMeta *)l_user->data;
             if (user_meta->base_meta.meta_type != NVDSINFER_TENSOR_OUTPUT_META)
                 continue;
-
+            extract_tensor_metadata(user_meta, networkInfo, batch_meta,
-            /* convert to tensor metadata */
+                                    frame_meta);
-            NvDsInferTensorMeta *meta =
-                (NvDsInferTensorMeta *)user_meta->user_meta_data;
-            for (unsigned int i = 0; i < meta->num_output_layers; i++) {
-                NvDsInferLayerInfo *info = &meta->output_layers_info[i];
-                info->buffer = meta->out_buf_ptrs_host[i];
-                if (use_device_mem && meta->out_buf_ptrs_dev[i]) {
-                    cudaMemcpy(meta->out_buf_ptrs_host[i],
-                               meta->out_buf_ptrs_dev[i],
-                               info->inferDims.numElements * 4,
-                               cudaMemcpyDeviceToHost);
-                }
-            }
-            /* Parse output tensor and fill detection results into objectList.
-             */
-            std::vector<NvDsInferLayerInfo> outputLayersInfo(
-                meta->output_layers_info,
-                meta->output_layers_info + meta->num_output_layers);
-#if NVDS_VERSION_MAJOR >= 5
-            if (nvds_lib_major_version >= 5) {
-                if (meta->network_info.width != networkInfo.width ||
-                    meta->network_info.height != networkInfo.height ||
-                    meta->network_info.channels != networkInfo.channels) {
-                    g_error("failed to check pgie network info\n");
-                }
-            }
-#endif
-
-            float *outputBuffer = (float *)outputLayersInfo[0].buffer;
-            (void)outputBuffer;
-            // NvDsInferDims dims = outputLayersInfo[0].inferDims;
-
-            for (size_t jkl = 0; jkl < outputLayersInfo.size(); jkl++) {
-                const NvDsInferLayerInfo &layer = outputLayersInfo[jkl];
-
-                unsigned int numDims = layer.inferDims.numDims;
-                unsigned int numElements = layer.inferDims.numElements;
-                (void)numElements;
-                (void)numDims;
-
-                // std::cout << "Layer " << jkl << " (" << layer.layerName <<
-                // "):\n"; std::cout << "  Num Dims: " << numDims << "\n";
-                // std::cout << "  Num Elements: " << numElements << "\n";
-                // std::cout << "  Dims: [";
-                // for (unsigned int mno = 0; mno < numDims; ++mno) {
-                //     std::cout << layer.inferDims.d[mno];
-                //     // layer.inferDims.d[0] = 100;
-                //     // layer.inferDims.d[1] = 57;
-                //     if (mno < numDims - 1)
-                //        std::cout << ", ";
-                // }
-                // std::cout << "]\n";
-            }
-            const NvDsInferLayerInfo &layer =
-                outputLayersInfo[0];  // or loop over all
-
-            uint detected_persons = 0;
-            float *data = static_cast<float *>(layer.buffer);
-            for (unsigned int jkl = 0; jkl < 100;
-                 jkl++) {  // 100 persons for each frame
-                if (data[jkl * 57 + 4] > threshold_body_detection) {
-                    detected_persons++;
-                }
-            }
-            update_frame_with_face_body_meta(detected_persons, batch_meta, meta,
-                                             data, frame_meta);
         }
     }
     // use_device_mem = 1 - use_device_mem;
     return GST_PAD_PROBE_OK;
 }
 
+void NvInferServerManager::extract_tensor_metadata(
+    NvDsUserMeta *user_meta, NvDsInferNetworkInfo networkInfo,
+    NvDsBatchMeta *batch_meta, NvDsFrameMeta *frame_meta) {
+    /* convert to tensor metadata */
+    NvDsInferTensorMeta *meta =
+        (NvDsInferTensorMeta *)user_meta->user_meta_data;
+    for (unsigned int i = 0; i < meta->num_output_layers; i++) {
+        NvDsInferLayerInfo *info = &meta->output_layers_info[i];
+        info->buffer = meta->out_buf_ptrs_host[i];
+        if (use_device_mem && meta->out_buf_ptrs_dev[i]) {
+            cudaMemcpy(meta->out_buf_ptrs_host[i], meta->out_buf_ptrs_dev[i],
+                       info->inferDims.numElements * 4, cudaMemcpyDeviceToHost);
+        }
+    }
+    /* Parse output tensor and fill detection results into objectList.
+     */
+    std::vector<NvDsInferLayerInfo> outputLayersInfo(
+        meta->output_layers_info,
+        meta->output_layers_info + meta->num_output_layers);
+#if NVDS_VERSION_MAJOR >= 5
+    if (nvds_lib_major_version >= 5) {
+        if (meta->network_info.width != networkInfo.width ||
+            meta->network_info.height != networkInfo.height ||
+            meta->network_info.channels != networkInfo.channels) {
+            g_error("failed to check pgie network info\n");
+        }
+    }
+#endif
+
+    float *outputBuffer = (float *)outputLayersInfo[0].buffer;
+    (void)outputBuffer;
+    // NvDsInferDims dims = outputLayersInfo[0].inferDims;
+
+    for (size_t jkl = 0; jkl < outputLayersInfo.size(); jkl++) {
+        const NvDsInferLayerInfo &layer = outputLayersInfo[jkl];
+
+        unsigned int numDims = layer.inferDims.numDims;
+        unsigned int numElements = layer.inferDims.numElements;
+        (void)numElements;
+        (void)numDims;
+
+        // std::cout << "Layer " << jkl << " (" << layer.layerName <<
+        // "):\n"; std::cout << "  Num Dims: " << numDims << "\n";
+        // std::cout << "  Num Elements: " << numElements << "\n";
+        // std::cout << "  Dims: [";
+        // for (unsigned int mno = 0; mno < numDims; ++mno) {
+        //     std::cout << layer.inferDims.d[mno];
+        //     // layer.inferDims.d[0] = 100;
+        //     // layer.inferDims.d[1] = 57;
+        //     if (mno < numDims - 1)
+        //        std::cout << ", ";
+        // }
+        // std::cout << "]\n";
+    }
+    const NvDsInferLayerInfo &layer = outputLayersInfo[0];  // or loop over all
+
+    uint detected_persons = 0;
+    float *data = static_cast<float *>(layer.buffer);
+    for (unsigned int jkl = 0; jkl < 100;
+         jkl++) {  // maximum 100 persons for each frame
+        if (data[jkl * 57 + 4] > threshold_body_detection) {
+            detected_persons++;
+        }
+    }
+    update_frame_with_face_body_meta(detected_persons, batch_meta, meta, data,
+                                     frame_meta);
+}
+
 void NvInferServerManager::update_frame_with_face_body_meta(
     uint detected_persons, NvDsBatchMeta *batch_meta, NvDsInferTensorMeta *meta,
     float *data, NvDsFrameMeta *frame_meta) {

src/nv_infer_server_manager.hpp

@@ -43,4 +43,6 @@ class NvInferServerManager {
     static void update_frame_with_face_body_meta(uint, NvDsBatchMeta *,
                                                  NvDsInferTensorMeta *, float *,
                                                  NvDsFrameMeta *);
+    static void extract_tensor_metadata(NvDsUserMeta *, NvDsInferNetworkInfo,
+                                        NvDsBatchMeta *, NvDsFrameMeta *);
 };