[test_tipc] add paddle2onnx; fix onnxruntime infer_demo (#5857)

Co-authored-by: Nlyuwenyu <wenyu.lyu@gmail.com>

deploy/third_engine/demo_onnxruntime/infer_demo.py

@@ -38,8 +38,12 @@ class PicoDet():
         so = ort.SessionOptions()
         so.log_severity_level = 3
         self.net = ort.InferenceSession(model_pb_path, so)
-        self.input_shape = (self.net.get_inputs()[0].shape[2],
-                            self.net.get_inputs()[0].shape[3])
+        inputs_name = [a.name for a in self.net.get_inputs()]
+        inputs_shape = {
+            k: v.shape
+            for k, v in zip(inputs_name, self.net.get_inputs())
+        }
+        self.input_shape = inputs_shape['image'][2:]
 
     def _normalize(self, img):
         img = img.astype(np.float32)
@@ -51,6 +55,8 @@ class PicoDet():
         origin_shape = srcimg.shape[:2]
         im_scale_y = newh / float(origin_shape[0])
         im_scale_x = neww / float(origin_shape[1])
+        img_shape = np.array([[float(origin_shape[0]), float(origin_shape[1])]
+                              ]).astype('float32')
         scale_factor = np.array([[im_scale_y, im_scale_x]]).astype('float32')
 
         if keep_ratio and srcimg.shape[0] != srcimg.shape[1]:
@@ -87,7 +93,7 @@ class PicoDet():
             img = cv2.resize(
                 srcimg, self.input_shape, interpolation=cv2.INTER_AREA)
 
-        return img, scale_factor
+        return img, img_shape, scale_factor
 
     def get_color_map_list(self, num_classes):
         color_map = num_classes * [0, 0, 0]
@@ -104,15 +110,20 @@ class PicoDet():
         return color_map
 
     def detect(self, srcimg):
-        img, scale_factor = self.resize_image(srcimg)
+        img, im_shape, scale_factor = self.resize_image(srcimg)
         img = self._normalize(img)
 
         blob = np.expand_dims(np.transpose(img, (2, 0, 1)), axis=0)
 
-        outs = self.net.run(None, {
-            self.net.get_inputs()[0].name: blob,
-            self.net.get_inputs()[1].name: scale_factor
-        })
+        inputs_dict = {
+            'im_shape': im_shape,
+            'image': blob,
+            'scale_factor': scale_factor
+        }
+        inputs_name = [a.name for a in self.net.get_inputs()]
+        net_inputs = {k: inputs_dict[k] for k in inputs_name}
+
+        outs = self.net.run(None, net_inputs)
 
         outs = np.array(outs[0])
         expect_boxes = (outs[:, 1] > 0.5) & (outs[:, 0] > -1)
@@ -181,7 +192,7 @@ if __name__ == '__main__':
     parser.add_argument(
         "--img_fold", dest="img_fold", type=str, default="./imgs")
     parser.add_argument(
-        "--result_fold", dest="result_fold", type=str, default="./results")
+        "--result_fold", dest="result_fold", type=str, default="results")
     args = parser.parse_args()
 
     net = PicoDet(
@@ -191,3 +202,6 @@ if __name__ == '__main__':
         iou_threshold=args.nmsThreshold)
 
     net.detect_folder(args.img_fold, args.result_fold)
+    print(
+        f'infer results in ./deploy/third_engine/demo_onnxruntime/{args.result_fold}'
+    )

test_tipc/configs/picodet/picodet_s_320_coco_lcnet_linux_gpu_normal_normal_paddle2onnx_python_linux_gpu_cpu.txt

+===========================paddle2onnx_params===========================
+model_name:picodet_s_320_coco_lcnet
+python:python3.7
+filename:null
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_s_320_coco_lcnet.pdparams
+norm_export:tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml -o
+quant_export:tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml --slim_config configs/picodet/picodet_s_320_coco_lcnet.yml -o
+fpgm_export:tools/export_model.py -c configs/picodet/picodet_s_320_coco_lcnet.yml --slim_config configs/picodet/picodet_s_320_coco_lcnet.yml -o
+distill_export:null
+export1:null
+export2:null
+kl_quant_export:tools/post_quant.py -c configs/picodet/picodet_s_320_coco_lcnet.yml --slim_config configs/picodet/picodet_s_320_coco_lcnet.yml -o
+##
+2onnx: paddle2onnx
+--model_dir:./output_inference/picodet_s_320_coco_lcnet/
+--model_filename:model.pdmodel 
+--params_filename:model.pdiparams
+--save_file:./deploy/third_engine/demo_onnxruntime/onnx_file/picodet_s_320_coco.onnx
+--opset_version:11
+##
+inference:infer_demo.py
+--modelpath:./onnx_file/picodet_s_320_coco.onnx
+--img_fold:./imgs
+--result_fold:results
+infer_mode:norm
+null:null
\ No newline at end of file

test_tipc/prepare.sh

@@ -4,7 +4,7 @@ source test_tipc/utils_func.sh
 FILENAME=$1
 # MODE be one of ['lite_train_lite_infer' 'lite_train_whole_infer'
 #                 'whole_train_whole_infer', 'whole_infer', 'klquant_whole_infer',
-#                 'cpp_infer', 'serving_infer',  'lite_infer']
+#                 'cpp_infer', 'serving_infer',  'lite_infer', 'paddle2onnx_infer']
 MODE=$2
 
 # parse params
@@ -67,6 +67,10 @@ elif [ ${MODE} = "benchmark_train" ];then
     wget -nc -P ./dataset/mot/ https://paddledet.bj.bcebos.com/data/mot_benchmark.tar
     cd ./dataset/mot/ && tar -xvf mot_benchmark.tar && mv -u mot_benchmark/* .
     rm -rf mot_benchmark/ && cd ../../
+elif [ ${MODE} = "paddle2onnx_infer" ];then
+    # set paddle2onnx_infer enve
+    ${python} -m pip install install paddle2onnx
+    ${python} -m pip install onnxruntime==1.10.0
 else
     # download coco lite data
     wget -nc -P ./dataset/coco/ https://paddledet.bj.bcebos.com/data/tipc/coco_tipc.tar

test_tipc/test_paddle2onnx.sh

+#!/bin/bash
+source test_tipc/utils_func.sh
+
+FILENAME=$1
+
+# parser model_name
+dataline=$(cat ${FILENAME})
+IFS=$'\n'
+lines=(${dataline})
+model_name=$(func_parser_value "${lines[1]}")
+echo "ppdet onnx_infer: ${model_name}"
+python=$(func_parser_value "${lines[2]}")
+filename_key=$(func_parser_key "${lines[3]}")
+filename_value=$(func_parser_value "${lines[3]}")
+
+# export params
+save_export_key=$(func_parser_key "${lines[5]}")
+save_export_value=$(func_parser_value "${lines[5]}")
+export_weight_key=$(func_parser_key "${lines[6]}")
+export_weight_value=$(func_parser_value "${lines[6]}")
+norm_export=$(func_parser_value "${lines[7]}")
+pact_export=$(func_parser_value "${lines[8]}")
+fpgm_export=$(func_parser_value "${lines[9]}")
+distill_export=$(func_parser_value "${lines[10]}")
+export_key1=$(func_parser_key "${lines[11]}")
+export_value1=$(func_parser_value "${lines[11]}")
+export_key2=$(func_parser_key "${lines[12]}")
+export_value2=$(func_parser_value "${lines[12]}")
+kl_quant_export=$(func_parser_value "${lines[13]}")
+
+# parser paddle2onnx
+padlle2onnx_cmd=$(func_parser_value "${lines[15]}")
+infer_model_dir_key=$(func_parser_key "${lines[16]}")
+infer_model_dir_value=$(func_parser_value "${lines[16]}")
+model_filename_key=$(func_parser_key "${lines[17]}")
+model_filename_value=$(func_parser_value "${lines[17]}")
+params_filename_key=$(func_parser_key "${lines[18]}")
+params_filename_value=$(func_parser_value "${lines[18]}")
+save_file_key=$(func_parser_key "${lines[19]}")
+save_file_value=$(func_parser_value "${lines[19]}")
+opset_version_key=$(func_parser_key "${lines[20]}")
+opset_version_value=$(func_parser_value "${lines[20]}")
+
+# parser onnx inference 
+inference_py=$(func_parser_value "${lines[22]}")
+model_file_key=$(func_parser_key "${lines[23]}")
+model_file_value=$(func_parser_value "${lines[23]}")
+img_fold_key=$(func_parser_key "${lines[24]}")
+img_fold_value=$(func_parser_value "${lines[24]}")
+results_fold_key=$(func_parser_key "${lines[25]}")
+results_fold_value=$(func_parser_value "${lines[25]}")
+onnx_infer_mode_list=$(func_parser_value "${lines[26]}")
+
+LOG_PATH="./test_tipc/output"
+mkdir -p ${LOG_PATH}
+status_log="${LOG_PATH}/results_paddle2onnx.log"
+
+function func_paddle2onnx(){
+    IFS='|'
+    _script=$1
+
+    # paddle2onnx
+    echo "################### run onnx export ###################"
+    _save_log_path="${LOG_PATH}/paddle2onnx_infer_cpu.log"
+    set_dirname=$(func_set_params "${infer_model_dir_key}" "${infer_model_dir_value}")
+    set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
+    set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
+    set_save_model=$(func_set_params "${save_file_key}" "${save_file_value}")
+    set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}")
+    trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version}"
+    eval $trans_model_cmd
+    last_status=${PIPESTATUS[0]}
+    status_check $last_status "${trans_model_cmd}" "${status_log}"
+    # python inference
+    echo "################### run infer ###################"
+    cd ./deploy/third_engine/demo_onnxruntime/
+    model_file=$(func_set_params "${model_file_key}" "${model_file_value}")
+    img_fold=$(func_set_params "${img_fold_key}" "${img_fold_value}")
+    results_fold=$(func_set_params "${results_fold_key}" "${results_fold_value}")
+    infer_model_cmd="${python} ${inference_py} ${model_file} ${img_fold} ${results_fold}"
+    eval $infer_model_cmd
+    last_status=${PIPESTATUS[0]}
+    status_check $last_status "${infer_model_cmd}" "${status_log}"
+}
+
+export Count=0
+IFS="|"
+echo "################### run paddle export ###################"
+for infer_mode in ${onnx_infer_mode_list[*]}; do
+
+    # run export
+    case ${infer_mode} in
+        norm) run_export=${norm_export} ;;
+        quant) run_export=${pact_export} ;;
+        fpgm) run_export=${fpgm_export} ;;
+        distill) run_export=${distill_export} ;;
+        kl_quant) run_export=${kl_quant_export} ;;
+        *) echo "Undefined infer_mode!"; exit 1;
+    esac
+    if [ ${run_export} = "null" ]; then
+        continue
+    fi
+    set_export_weight=$(func_set_params "${export_weight_key}" "${export_weight_value}")
+    set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}")
+    set_filename=$(func_set_params "${filename_key}" "${model_name}")
+    export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_save_export_dir} "
+    echo  $export_cmd
+    eval $export_cmd
+    status_export=$?
+    status_check $status_export "${export_cmd}" "${status_log}"
+done
+func_paddle2onnx 
\ No newline at end of file