diff --git a/README.md b/README.md index 8d9a20ca..2b310cdd 100644 --- a/README.md +++ b/README.md @@ -25,6 +25,7 @@ Guidelines: | [PP-HumanSeg](./models/human_segmentation_pphumanseg) | 192x192 | 19.92 | 105.32 | 67.97 | | [WeChatQRCode](./models/qrcode_wechatqrcode) | 100x100 | 7.04 | 37.68 | --- | | [DaSiamRPN](./models/object_tracking_dasiamrpn) | 1280x720 | 36.15 | 705.48 | 76.82 | +| [YoutuReID](./models/person_reid_youtureid) | 128x256 | 35.81 | 521.98 | 90.07 | Hardware Setup: - `CPU x86_64`: INTEL CPU i7-5930K @ 3.50GHz, 6 cores, 12 threads. diff --git a/benchmark/config/person_reid_youtureid.yaml b/benchmark/config/person_reid_youtureid.yaml new file mode 100644 index 00000000..4643a956 --- /dev/null +++ b/benchmark/config/person_reid_youtureid.yaml @@ -0,0 +1,17 @@ +Benchmark: + name: "Person ReID Benchmark" + type: "Base" + data: + path: "benchmark/data/person_reid" + files: ["0030_c1_f0056923.jpg", "0042_c5_f0068994.jpg", "0056_c8_f0017063.jpg"] + sizes: [[128, 256]] + metric: + warmup: 30 + repeat: 10 + reduction: "median" + backend: "default" + target: "cpu" + +Model: + name: "YoutuReID" + modelPath: "models/person_reid_youtureid/person_reid_youtu_2021nov.onnx" \ No newline at end of file diff --git a/benchmark/download_data.py b/benchmark/download_data.py index 5d1f986c..5d7a4323 100644 --- a/benchmark/download_data.py +++ b/benchmark/download_data.py @@ -188,7 +188,11 @@ def get_confirm_token(response): # in case of large files object_tracking=Downloader(name='object_tracking', url='https://drive.google.com/u/0/uc?id=1_cw5pUmTF-XmQVcQAI8fIp-Ewi2oMYIn&export=download', sha='0bdb042632a245270013713bc48ad35e9221f3bb', - filename='object_tracking.zip') + filename='object_tracking.zip'), + person_reid=Downloader(name='person_reid', + url='https://drive.google.com/u/0/uc?id=1G8FkfVo5qcuyMkjSs4EA6J5e16SWDGI2&export=download', + sha='5b741fbf34c1fbcf59cad8f2a65327a5899e66f1', + filename='person_reid') ) if __name__ == '__main__': diff --git a/models/__init__.py b/models/__init__.py index c03bc613..7acc5784 100644 --- a/models/__init__.py +++ b/models/__init__.py @@ -6,6 +6,7 @@ from .human_segmentation_pphumanseg.pphumanseg import PPHumanSeg from .qrcode_wechatqrcode.wechatqrcode import WeChatQRCode from .object_tracking_dasiamrpn.dasiamrpn import DaSiamRPN +from .person_reid_youtureid.youtureid import YoutuReID class Registery: def __init__(self, name): @@ -26,4 +27,5 @@ def register(self, item): MODELS.register(PPResNet) MODELS.register(PPHumanSeg) MODELS.register(WeChatQRCode) -MODELS.register(DaSiamRPN) \ No newline at end of file +MODELS.register(DaSiamRPN) +MODELS.register(YoutuReID) \ No newline at end of file diff --git a/models/person_reid_youtureid/LICENSE b/models/person_reid_youtureid/LICENSE new file mode 100644 index 00000000..d6456956 --- /dev/null +++ b/models/person_reid_youtureid/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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This flag is invalid when using camera.') +parser.add_argument('--vis', '-v', type=str2bool, default=True, help='Set true to open a window for result visualization. This flag is invalid when using camera.') +args = parser.parse_args() + +def readImageFromDirectory(img_dir, w=128, h=256): + img_list = [] + file_list = os.listdir(img_dir) + for f in file_list: + img = cv.imread(os.path.join(img_dir, f)) + img = cv.resize(img, (w, h)) + img_list.append(img) + return img_list, file_list + +def visualize(results, query_dir, gallery_dir, output_size=(128, 384)): + def addBorder(img, color, borderSize=5): + border = cv.copyMakeBorder(img, top=borderSize, bottom=borderSize, left=borderSize, right=borderSize, borderType=cv.BORDER_CONSTANT, value=color) + return border + + results_vis = dict.fromkeys(results.keys(), None) + for f, topk_f in results.items(): + query_img = cv.imread(os.path.join(query_dir, f)) + query_img = cv.resize(query_img, output_size) + query_img = addBorder(query_img, [0, 0, 0]) + cv.putText(query_img, 'Query', (10, 30), cv.FONT_HERSHEY_COMPLEX, 1., (0, 255, 0), 2) + + gallery_img_list = [] + for idx, gallery_f in enumerate(topk_f): + gallery_img = cv.imread(os.path.join(gallery_dir, gallery_f)) + gallery_img = cv.resize(gallery_img, output_size) + gallery_img = addBorder(gallery_img, [255, 255, 255]) + cv.putText(gallery_img, 'G{:02d}'.format(idx), (10, 30), cv.FONT_HERSHEY_COMPLEX, 1., (0, 255, 0), 2) + gallery_img_list.append(gallery_img) + + results_vis[f] = np.concatenate([query_img] + gallery_img_list, axis=1) + + return results_vis + +if __name__ == '__main__': + # Instantiate YoutuReID for person ReID + net = YoutuReID(modelPath=args.model) + + # Read images from dir + query_img_list, query_file_list = readImageFromDirectory(args.query_dir) + gallery_img_list, gallery_file_list = readImageFromDirectory(args.gallery_dir) + + # Query + topk_indices = net.query(query_img_list, gallery_img_list, args.topk) + + # Index to filename + results = dict.fromkeys(query_file_list, None) + for f, indices in zip(query_file_list, topk_indices): + topk_matches = [] + for idx in indices: + topk_matches.append(gallery_file_list[idx]) + results[f] = topk_matches + # Print + print('Query: {}'.format(f)) + print('\tTop-{} from gallery: {}'.format(args.topk, str(topk_matches))) + + # Visualize + results_vis = visualize(results, args.query_dir, args.gallery_dir) + + if args.save: + for f, img in results_vis.items(): + cv.imwrite('result-{}'.format(f), img) + + if args.vis: + for f, img in results_vis.items(): + cv.namedWindow('result-{}'.format(f), cv.WINDOW_AUTOSIZE) + cv.imshow('result-{}'.format(f), img) + cv.waitKey(0) + cv.destroyAllWindows() \ No newline at end of file diff --git a/models/person_reid_youtureid/person_reid_youtu_2021nov.onnx b/models/person_reid_youtureid/person_reid_youtu_2021nov.onnx new file mode 100644 index 00000000..1e642cac --- /dev/null +++ b/models/person_reid_youtureid/person_reid_youtu_2021nov.onnx @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0579683334d4b9440221606dcb461656dd0dc64143b18f48faedaced9b4f580d +size 106878407 diff --git a/models/person_reid_youtureid/youtureid.py b/models/person_reid_youtureid/youtureid.py new file mode 100644 index 00000000..16490f6f --- /dev/null +++ b/models/person_reid_youtureid/youtureid.py @@ -0,0 +1,60 @@ +# This file is part of OpenCV Zoo project. +# It is subject to the license terms in the LICENSE file found in the same directory. +# +# Copyright (C) 2021, Shenzhen Institute of Artificial Intelligence and Robotics for Society, all rights reserved. +# Third party copyrights are property of their respective owners. + +import numpy as np +import cv2 as cv + +class YoutuReID: + def __init__(self, modelPath): + self._model = cv.dnn.readNet(modelPath) + self._input_size = (128, 256) # fixed + self._output_dim = 768 + self._mean = (0.485, 0.456, 0.406) + self._std = (0.229, 0.224, 0.225) + + @property + def name(self): + return self.__class__.__name__ + + def setBackend(self, backend_id): + self._model.setPreferableBackend(backend_id) + + def setTarget(self, target_id): + self._model.setPreferableTarget(target_id) + + def _preprocess(self, image): + image = image[:, :, ::-1] + image = (image / 255.0 - self._mean) / self._std + return cv.dnn.blobFromImage(image.astype(np.float32)) + # return cv.dnn.blobFromImage(image, scalefactor=(1.0/255.0), size=self._input_size, mean=self._mean) / self._std + + def infer(self, image): + # Preprocess + inputBlob = self._preprocess(image) + + # Forward + self._model.setInput(inputBlob) + features = self._model.forward() + return np.reshape(features, (features.shape[0], features.shape[1])) + + def query(self, query_img_list, gallery_img_list, topK=5): + query_features_list = [] + for q in query_img_list: + query_features_list.append(self.infer(q)) + query_features = np.concatenate(query_features_list, axis=0) + query_norm = np.linalg.norm(query_features, ord=2, axis=1, keepdims=True) + query_arr = query_features / (query_norm + np.finfo(np.float32).eps) + + gallery_features_list = [] + for g in gallery_img_list: + gallery_features_list.append(self.infer(g)) + gallery_features = np.concatenate(gallery_features_list, axis=0) + gallery_norm = np.linalg.norm(gallery_features, ord=2, axis=1, keepdims=True) + gallery_arr = gallery_features / (gallery_norm + np.finfo(np.float32).eps) + + dist = np.matmul(query_arr, gallery_arr.T) + idx = np.argsort(-dist, axis=1) + return [i[0:topK] for i in idx] \ No newline at end of file