From d1e5bea2cb6c67492b397b84c4307386040ae0d2 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Mon, 13 Jun 2022 14:37:30 +0800 Subject: [PATCH] debug --- .../serving_client_conf.prototxt | 0 .../serving_server_conf.prototxt | 0 .../serving_client_conf.prototxt | 0 .../serving_server_conf.prototxt | 0 .../recognition/test_cpp_serving_client.py | 275 +++++++----------- test_tipc/docs/test_serving_infer_cpp.md | 18 +- test_tipc/prepare.sh | 2 + test_tipc/test_serving_infer.sh | 8 +- 8 files changed, 115 insertions(+), 188 deletions(-) rename deploy/paddleserving/{ => recognition}/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/serving_client_conf.prototxt (100%) rename deploy/paddleserving/{ => recognition}/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/serving_server_conf.prototxt (100%) rename deploy/paddleserving/{ => recognition}/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/serving_client_conf.prototxt (100%) rename deploy/paddleserving/{ => recognition}/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/serving_server_conf.prototxt (100%) diff --git a/deploy/paddleserving/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/serving_client_conf.prototxt b/deploy/paddleserving/recognition/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/serving_client_conf.prototxt similarity index 100% rename from deploy/paddleserving/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/serving_client_conf.prototxt rename to deploy/paddleserving/recognition/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/serving_client_conf.prototxt diff --git a/deploy/paddleserving/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/serving_server_conf.prototxt b/deploy/paddleserving/recognition/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/serving_server_conf.prototxt similarity index 100% rename from deploy/paddleserving/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/serving_server_conf.prototxt rename to deploy/paddleserving/recognition/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/serving_server_conf.prototxt diff --git a/deploy/paddleserving/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/serving_client_conf.prototxt b/deploy/paddleserving/recognition/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/serving_client_conf.prototxt similarity index 100% rename from deploy/paddleserving/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/serving_client_conf.prototxt rename to deploy/paddleserving/recognition/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/serving_client_conf.prototxt diff --git a/deploy/paddleserving/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/serving_server_conf.prototxt b/deploy/paddleserving/recognition/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/serving_server_conf.prototxt similarity index 100% rename from deploy/paddleserving/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/serving_server_conf.prototxt rename to deploy/paddleserving/recognition/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/serving_server_conf.prototxt diff --git a/deploy/paddleserving/recognition/test_cpp_serving_client.py b/deploy/paddleserving/recognition/test_cpp_serving_client.py index a2bf1ae3..60412f6e 100644 --- a/deploy/paddleserving/recognition/test_cpp_serving_client.py +++ b/deploy/paddleserving/recognition/test_cpp_serving_client.py @@ -22,181 +22,102 @@ import faiss import os import pickle - -class MainbodyDetect(): - """ - pp-shitu mainbody detect. - include preprocess, process, postprocess - return detect results - Attention: Postprocess include num limit and box filter; no nms - """ - - def __init__(self): - self.preprocess = DetectionSequential([ - DetectionFile2Image(), DetectionNormalize( - [0.485, 0.456, 0.406], [0.229, 0.224, 0.225], True), - DetectionResize( - (640, 640), False, interpolation=2), DetectionTranspose( - (2, 0, 1)) - ]) - - self.client = Client() - self.client.load_client_config( - "../../models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/serving_client_conf.prototxt" - ) - self.client.connect(['127.0.0.1:9293']) - - self.max_det_result = 5 - self.conf_threshold = 0.2 - - def predict(self, imgpath): - im, im_info = self.preprocess(imgpath) - im_shape = np.array(im.shape[1:]).reshape(-1) - scale_factor = np.array(list(im_info['scale_factor'])).reshape(-1) - - fetch_map = self.client.predict( - feed={ - "image": im, - "im_shape": im_shape, - "scale_factor": scale_factor, - }, - fetch=["save_infer_model/scale_0.tmp_1"], - batch=False) - return self.postprocess(fetch_map, imgpath) - - def postprocess(self, fetch_map, imgpath): - #1. get top max_det_result - det_results = fetch_map["save_infer_model/scale_0.tmp_1"] - if len(det_results) > self.max_det_result: - boxes_reserved = fetch_map[ - "save_infer_model/scale_0.tmp_1"][:self.max_det_result] - else: - boxes_reserved = det_results - - #2. do conf threshold - boxes_list = [] - for i in range(boxes_reserved.shape[0]): - if (boxes_reserved[i, 1]) > self.conf_threshold: - boxes_list.append(boxes_reserved[i, :]) - - #3. add origin image box - origin_img = cv2.imread(imgpath) - boxes_list.append( - np.array([0, 1.0, 0, 0, origin_img.shape[1], origin_img.shape[0]])) - return np.array(boxes_list) - - -class ObjectRecognition(): - """ - pp-shitu object recognion for all objects detected by MainbodyDetect. - include preprocess, process, postprocess - preprocess include preprocess for each image and batching. - Batch process - postprocess include retrieval and nms - """ - - def __init__(self): - self.client = Client() - self.client.load_client_config( - "../../models/general_PPLCNet_x2_5_lite_v1.0_client/serving_client_conf.prototxt" - ) - self.client.connect(["127.0.0.1:9294"]) - - self.seq = Sequential([ - BGR2RGB(), Resize((224, 224)), Div(255), - Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225], - False), Transpose((2, 0, 1)) - ]) - - self.searcher, self.id_map = self.init_index() - - self.rec_nms_thresold = 0.05 - self.rec_score_thres = 0.5 - self.feature_normalize = True - self.return_k = 1 - - def init_index(self): - index_dir = "../../drink_dataset_v1.0/index" - assert os.path.exists(os.path.join( - index_dir, "vector.index")), "vector.index not found ..." - assert os.path.exists(os.path.join( - index_dir, "id_map.pkl")), "id_map.pkl not found ... " - - searcher = faiss.read_index(os.path.join(index_dir, "vector.index")) - - with open(os.path.join(index_dir, "id_map.pkl"), "rb") as fd: - id_map = pickle.load(fd) - return searcher, id_map - - def predict(self, det_boxes, imgpath): - #1. preprocess - batch_imgs = [] - origin_img = cv2.imread(imgpath) - for i in range(det_boxes.shape[0]): - box = det_boxes[i] - x1, y1, x2, y2 = [int(x) for x in box[2:]] - cropped_img = origin_img[y1:y2, x1:x2, :].copy() - tmp = self.seq(cropped_img) - batch_imgs.append(tmp) - batch_imgs = np.array(batch_imgs) - - #2. process - fetch_map = self.client.predict( - feed={"x": batch_imgs}, fetch=["features"], batch=True) - batch_features = fetch_map["features"] - - #3. postprocess - if self.feature_normalize: - feas_norm = np.sqrt( - np.sum(np.square(batch_features), axis=1, keepdims=True)) - batch_features = np.divide(batch_features, feas_norm) - scores, docs = self.searcher.search(batch_features, self.return_k) - - results = [] - for i in range(scores.shape[0]): - pred = {} - if scores[i][0] >= self.rec_score_thres: - pred["bbox"] = [int(x) for x in det_boxes[i, 2:]] - pred["rec_docs"] = self.id_map[docs[i][0]].split()[1] - pred["rec_scores"] = scores[i][0] - results.append(pred) - return self.nms_to_rec_results(results) - - def nms_to_rec_results(self, results): - filtered_results = [] - x1 = np.array([r["bbox"][0] for r in results]).astype("float32") - y1 = np.array([r["bbox"][1] for r in results]).astype("float32") - x2 = np.array([r["bbox"][2] for r in results]).astype("float32") - y2 = np.array([r["bbox"][3] for r in results]).astype("float32") - scores = np.array([r["rec_scores"] for r in results]) - - areas = (x2 - x1 + 1) * (y2 - y1 + 1) - order = scores.argsort()[::-1] - while order.size > 0: - i = order[0] - xx1 = np.maximum(x1[i], x1[order[1:]]) - yy1 = np.maximum(y1[i], y1[order[1:]]) - xx2 = np.minimum(x2[i], x2[order[1:]]) - yy2 = np.minimum(y2[i], y2[order[1:]]) - - w = np.maximum(0.0, xx2 - xx1 + 1) - h = np.maximum(0.0, yy2 - yy1 + 1) - inter = w * h - ovr = inter / (areas[i] + areas[order[1:]] - inter) - inds = np.where(ovr <= self.rec_nms_thresold)[0] - order = order[inds + 1] - filtered_results.append(results[i]) - return filtered_results - - +rec_nms_thresold = 0.05 +rec_score_thres = 0.5 +feature_normalize = True +return_k = 1 +index_dir = "../../drink_dataset_v1.0/index" + + +def init_index(index_dir): + assert os.path.exists(os.path.join( + index_dir, "vector.index")), "vector.index not found ..." + assert os.path.exists(os.path.join( + index_dir, "id_map.pkl")), "id_map.pkl not found ... " + + searcher = faiss.read_index(os.path.join(index_dir, "vector.index")) + + with open(os.path.join(index_dir, "id_map.pkl"), "rb") as fd: + id_map = pickle.load(fd) + return searcher, id_map + + +#get box +def nms_to_rec_results(results, thresh=0.1): + filtered_results = [] + + x1 = np.array([r["bbox"][0] for r in results]).astype("float32") + y1 = np.array([r["bbox"][1] for r in results]).astype("float32") + x2 = np.array([r["bbox"][2] for r in results]).astype("float32") + y2 = np.array([r["bbox"][3] for r in results]).astype("float32") + scores = np.array([r["rec_scores"] for r in results]) + + areas = (x2 - x1 + 1) * (y2 - y1 + 1) + order = scores.argsort()[::-1] + while order.size > 0: + i = order[0] + xx1 = np.maximum(x1[i], x1[order[1:]]) + yy1 = np.maximum(y1[i], y1[order[1:]]) + xx2 = np.minimum(x2[i], x2[order[1:]]) + yy2 = np.minimum(y2[i], y2[order[1:]]) + + w = np.maximum(0.0, xx2 - xx1 + 1) + h = np.maximum(0.0, yy2 - yy1 + 1) + inter = w * h + ovr = inter / (areas[i] + areas[order[1:]] - inter) + inds = np.where(ovr <= thresh)[0] + order = order[inds + 1] + filtered_results.append(results[i]) + return filtered_results + + +def postprocess(fetch_dict, feature_normalize, det_boxes, searcher, id_map, + return_k, rec_score_thres, rec_nms_thresold): + batch_features = fetch_dict["features"] + + #do feature norm + if feature_normalize: + feas_norm = np.sqrt( + np.sum(np.square(batch_features), axis=1, keepdims=True)) + batch_features = np.divide(batch_features, feas_norm) + + scores, docs = searcher.search(batch_features, return_k) + + results = [] + for i in range(scores.shape[0]): + pred = {} + if scores[i][0] >= rec_score_thres: + pred["bbox"] = [int(x) for x in det_boxes[i, 2:]] + pred["rec_docs"] = id_map[docs[i][0]].split()[1] + pred["rec_scores"] = scores[i][0] + results.append(pred) + + #do nms + results = nms_to_rec_results(results, rec_nms_thresold) + return results + + +#do client if __name__ == "__main__": - det = MainbodyDetect() - rec = ObjectRecognition() - - #1. get det_results - imgpath = "../../drink_dataset_v1.0/test_images/001.jpeg" - det_results = det.predict(imgpath) - - #2. get rec_results - rec_results = rec.predict(det_results, imgpath) - print(rec_results) + client = Client() + client.load_client_config([ + "../../models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client", + "../../models/general_PPLCNet_x2_5_lite_v1.0_client" + ]) + client.connect(['127.0.0.1:9400']) + + im = cv2.imread("../../drink_dataset_v1.0/test_images/001.jpeg") + im_shape = np.array(im.shape[:2]).reshape(-1) + fetch_map = client.predict( + feed={"image": im, + "im_shape": im_shape}, + fetch=["features", "boxes"], + batch=False) + print(fetch_map.keys()) + #add retrieval procedure + det_boxes = fetch_map["boxes"] + print(det_boxes) + searcher, id_map = init_index(index_dir) + results = postprocess(fetch_map, feature_normalize, det_boxes, searcher, + id_map, return_k, rec_score_thres, rec_nms_thresold) + print(results) diff --git a/test_tipc/docs/test_serving_infer_cpp.md b/test_tipc/docs/test_serving_infer_cpp.md index 64b9bb04..2d966816 100644 --- a/test_tipc/docs/test_serving_infer_cpp.md +++ b/test_tipc/docs/test_serving_infer_cpp.md @@ -52,7 +52,7 @@ Linux GPU/CPU PYTHON 服务化部署测试的主程序为`test_serving_infer.sh ``` - 安装 PaddleServing 相关组件，包括serving_client、serving-app，自动编译带自定义OP的serving_server包（测试PP-ShiTu时），以及自动下载并解压推理模型 ```bash - bash test_tipc/prepare.sh test_tipc/configs/ResNet50/ResNet50_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt serving_infer + bash test_tipc/prepare.sh test_tipc/configs/PPLCNet/PPLCNet_x1_0_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt serving_infer ``` ### 2.3 功能测试 @@ -63,24 +63,28 @@ Linux GPU/CPU PYTHON 服务化部署测试的主程序为`test_serving_infer.sh bash test_tipc/test_serving_infer.sh ${your_params_file} ``` -以`ResNet50`的`Linux GPU/CPU PYTHON 服务化部署测试`为例，命令如下所示。 +以`PPLCNet_x1_0`的`Linux GPU/CPU C++ 服务化部署测试`为例，命令如下所示。 ```bash -bash test_tipc/test_serving_infer.sh test_tipc/configs/ResNet50/ResNet50_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt +bash test_tipc/test_serving_infer.sh test_tipc/configs/PPLCNet/PPLCNet_x1_0_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt ``` 输出结果如下，表示命令运行成功。 ``` -Run successfully with command - python3.7 pipeline_http_client.py > ../../test_tipc/output/ResNet50/server_infer_gpu_pipeline_http_batchsize_1.log 2>&1! -Run successfully with command - python3.7 pipeline_http_client.py > ../../test_tipc/output/ResNet50/server_infer_cpu_pipeline_http_batchsize_1.log 2>&1 ! +Run successfully with command - PPLCNet_x1_0 - python3.7 test_cpp_serving_client.py > ../../test_tipc/output/PPLCNet_x1_0/server_infer_cpp_gpu_pipeline_batchsize_1.log 2>&1 ! +Run successfully with command - PPLCNet_x1_0 - python3.7 test_cpp_serving_client.py > ../../test_tipc/output/PPLCNet_x1_0/server_infer_cpp_cpu_pipeline_batchsize_1.log 2>&1 ! ``` -预测结果会自动保存在 `./test_tipc/output/ResNet50/server_infer_gpu_pipeline_http_batchsize_1.log` ，可以看到 PaddleServing 的运行结果： +预测结果会自动保存在 `./test_tipc/output/PPLCNet_x1_0/server_infer_gpu_pipeline_http_batchsize_1.log` ，可以看到 PaddleServing 的运行结果： ``` -{'err_no': 0, 'err_msg': '', 'key': ['label', 'prob'], 'value': ["['daisy']", '[0.998314619064331]']} +WARNING: Logging before InitGoogleLogging() is written to STDERR +I0612 09:55:16.109890 38303 naming_service_thread.cpp:202] brpc::policy::ListNamingService("127.0.0.1:9292"): added 1 +I0612 09:55:16.172924 38303 general_model.cpp:490] [client]logid=0,client_cost=60.772ms,server_cost=57.6ms. +prediction: daisy, probability: 0.9099399447441101 +0.06275796890258789 ``` diff --git a/test_tipc/prepare.sh b/test_tipc/prepare.sh index 9f98f60b..4c638b43 100644 --- a/test_tipc/prepare.sh +++ b/test_tipc/prepare.sh @@ -204,7 +204,9 @@ if [[ ${MODE} = "serving_infer" ]]; then ${python_name} -m pip install paddle-serving-app==0.9.0 -i https://pypi.tuna.tsinghua.edu.cn/simple python_name=$(func_parser_value "${lines[2]}") if [[ ${FILENAME} =~ "cpp" ] && [ ${model_name} =~ "ShiTu" ]]; then + pushd ./deploy/paddleserving bash build_server.sh ${python_name} + popd else ${python_name} -m pip install install paddle-serving-server-gpu==0.9.0.post101 -i https://pypi.tuna.tsinghua.edu.cn/simple fi diff --git a/test_tipc/test_serving_infer.sh b/test_tipc/test_serving_infer.sh index bccdd039..002d12a7 100644 --- a/test_tipc/test_serving_infer.sh +++ b/test_tipc/test_serving_infer.sh @@ -263,13 +263,13 @@ function func_serving_rec(){ det_trans_model_cmd="${python_interp} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}" eval $det_trans_model_cmd - cp_prototxt_cmd="cp ./paddleserving/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/*.prototxt ${cls_serving_server_value}" + cp_prototxt_cmd="cp ./paddleserving/recognition/preprocess/general_PPLCNet_x2_5_lite_v1.0_serving/*.prototxt ${cls_serving_server_value}" eval ${cp_prototxt_cmd} - cp_prototxt_cmd="cp ./paddleserving/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/*.prototxt ${cls_serving_client_value}" + cp_prototxt_cmd="cp ./paddleserving/recognition/preprocess/general_PPLCNet_x2_5_lite_v1.0_client/*.prototxt ${cls_serving_client_value}" eval ${cp_prototxt_cmd} - cp_prototxt_cmd="cp ./paddleserving/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/*.prototxt ${det_serving_client_value}" + cp_prototxt_cmd="cp ./paddleserving/recognition/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_client/*.prototxt ${det_serving_client_value}" eval ${cp_prototxt_cmd} - cp_prototxt_cmd="cp ./paddleserving/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/*.prototxt ${det_serving_server_value}" + cp_prototxt_cmd="cp ./paddleserving/recognition/preprocess/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_serving/*.prototxt ${det_serving_server_value}" eval ${cp_prototxt_cmd} prototxt_dataline=$(awk 'NR==1, NR==3{print}' ${cls_serving_server_value}/serving_server_conf.prototxt) -- GitLab