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	ce4867d14e
	
	
	
		
			
			* 测试 * delete test * add yolov7-face * fit vision.h * add yolov7-face test * fit: yolov7-face infer.cc * fit * fit Yolov7-face Cmakelist * fit yolov7Face.cc * add yolov7-face pybind * add yolov7-face python infer * feat yolov7-face pybind * feat yolov7-face format error * feat yolov7face_pybind error * feat add yolov7face-pybind to facedet-pybind * same as before * same sa before * feat __init__.py * add yolov7face.py * feat yolov7face.h ignore "," * feat .py * fit yolov7face.py * add yolov7face test teadme file * add test file * fit postprocess * delete remain annotation * fit preview * fit yolov7facepreprocessor * fomat code * fomat code * fomat code * fit format error and confthreshold and nmsthres * fit confthreshold and nmsthres * fit test-yolov7-face * fit test_yolov7face * fit review * fit ci error Co-authored-by: kongbohua <kongbh2022@stu.pku.edu.cn> Co-authored-by: CoolCola <49013063+kongbohua@users.noreply.github.com>
		
			
				
	
	
		
			143 lines
		
	
	
		
			5.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			143 lines
		
	
	
		
			5.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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| #
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| # Licensed under the Apache License, Version 2.0 (the "License");
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| # you may not use this file except in compliance with the License.
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| # You may obtain a copy of the License at
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| #
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| #     http://www.apache.org/licenses/LICENSE-2.0
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| #
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| # Unless required by applicable law or agreed to in writing, software
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| # distributed under the License is distributed on an "AS IS" BASIS,
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| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| # See the License for the specific language governing permissions and
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| # limitations under the License.
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| 
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| from fastdeploy import ModelFormat
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| import fastdeploy as fd
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| import cv2
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| import os
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| import pickle
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| import numpy as np
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| import runtime_config as rc
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| 
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| 
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| def test_detection_yolov7face():
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|     model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-lite-e.onnx"
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|     input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
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|     input_url2 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000570688.jpg"
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|     result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7face_result1.pkl"
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|     result_url2 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7face_result2.pkl"
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|     fd.download(model_url, "resources")
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|     fd.download(input_url1, "resources")
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|     fd.download(input_url2, "resources")
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|     fd.download(result_url1, "resources")
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|     fd.download(result_url2, "resources")
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| 
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|     model_file = "resources/yolov7-lite-e.onnx"
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|     model = fd.vision.facedet.YOLOv7Face(
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|         model_file, runtime_option=rc.test_option)
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|     model.postprocessor.conf_threshold = 0.3
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| 
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|     with open("resources/yolov7face_result1.pkl", "rb") as f:
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|         expect1 = pickle.load(f)
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| 
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|     with open("resources/yolov7face_result2.pkl", "rb") as f:
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|         expect2 = pickle.load(f)
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| 
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|     im1 = cv2.imread("./resources/000000014439.jpg")
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|     im2 = cv2.imread("./resources/000000570688.jpg")
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| 
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|     for i in range(3):
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|         # test single predict
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|         result1 = model.predict(im1)
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|         result2 = model.predict(im2)
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| 
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|         diff_boxes_1 = np.fabs(
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|             np.array(result1.boxes) - np.array(expect1["boxes"]))
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|         diff_boxes_2 = np.fabs(
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|             np.array(result2.boxes) - np.array(expect2["boxes"]))
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| 
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|         diff_scores_1 = np.fabs(
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|             np.array(result1.scores) - np.array(expect1["scores"]))
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|         diff_scores_2 = np.fabs(
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|             np.array(result2.scores) - np.array(expect2["scores"]))
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| 
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|         assert diff_boxes_1.max(
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|         ) < 1e-03, "There's difference in detection boxes 1."
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|         assert diff_scores_1.max(
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|         ) < 1e-04, "There's difference in detection score 1."
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| 
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|         assert diff_boxes_2.max(
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|         ) < 1e-03, "There's difference in detection boxes 2."
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|         assert diff_scores_2.max(
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|         ) < 1e-04, "There's difference in detection score 2."
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| 
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|         # test batch predict
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|         results = model.batch_predict([im1, im2])
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|         result1 = results[0]
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|         result2 = results[1]
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| 
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|         diff_boxes_1 = np.fabs(
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|             np.array(result1.boxes) - np.array(expect1["boxes"]))
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|         diff_boxes_2 = np.fabs(
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|             np.array(result2.boxes) - np.array(expect2["boxes"]))
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| 
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|         diff_scores_1 = np.fabs(
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|             np.array(result1.scores) - np.array(expect1["scores"]))
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|         diff_scores_2 = np.fabs(
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|             np.array(result2.scores) - np.array(expect2["scores"]))
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|         assert diff_boxes_1.max(
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|         ) < 1e-03, "There's difference in detection boxes 1."
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|         assert diff_scores_1.max(
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|         ) < 1e-04, "There's difference in detection score 1."
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| 
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|         assert diff_boxes_2.max(
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|         ) < 1e-03, "There's difference in detection boxes 2."
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|         assert diff_scores_2.max(
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|         ) < 1e-04, "There's difference in detection score 2."
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| 
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| 
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| def test_detection_yolov7face_runtime():
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|     model_url = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7-lite-e.onnx"
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|     input_url1 = "https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg"
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|     result_url1 = "https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_result1.pkl"
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|     fd.download(model_url, "resources")
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|     fd.download(input_url1, "resources")
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|     fd.download(result_url1, "resources")
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| 
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|     model_file = "resources/yolov7-lite-e.onnx"
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| 
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|     preprocessor = fd.vision.detection.Yolov7FacePreprocessor()
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|     postprocessor = fd.vision.detection.YOLOv7FacePostprocessor()
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| 
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|     rc.test_option.set_model_path(model_file, model_format=ModelFormat.ONNX)
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|     rc.test_option.use_openvino_backend()
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|     runtime = fd.Runtime(rc.test_option)
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| 
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|     with open("resources/yolov7_result1.pkl", "rb") as f:
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|         expect1 = pickle.load(f)
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| 
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|     im1 = cv2.imread("resources/000000014439.jpg")
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| 
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|     for i in range(3):
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|         # test runtime
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|         input_tensors, ims_info = preprocessor.run([im1.copy()])
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|         output_tensors = runtime.infer({"images": input_tensors[0]})
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|         results = postprocessor.run(output_tensors, ims_info)
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|         result1 = results[0]
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| 
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|         diff_boxes_1 = np.fabs(
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|             np.array(result1.boxes) - np.array(expect1["boxes"]))
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|         diff_scores_1 = np.fabs(
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|             np.array(result1.scores) - np.array(expect1["scores"]))
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| 
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|         assert diff_boxes_1.max(
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|         ) < 1e-03, "There's difference in detection boxes 1."
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|         assert diff_scores_1.max(
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|         ) < 1e-04, "There's difference in detection score 1."
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| 
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| 
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| if __name__ == "__main__":
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|     test_detection_yolov7face()
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|     test_detection_yolov7face_runtime()
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