mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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adddd3c452
* update .gitignore * Added checking for cmake include dir * fixed missing trt_backend option bug when init from trt * remove un-need data layout and add pre-check for dtype * changed RGB2BRG to BGR2RGB in ppcls model * add model_zoo yolov6 c++/python demo * fixed CMakeLists.txt typos * update yolov6 cpp/README.md * add yolox c++/pybind and model_zoo demo * move some helpers to private * fixed CMakeLists.txt typos * add normalize with alpha and beta * add version notes for yolov5/yolov6/yolox * add copyright to yolov5.cc * revert normalize * fixed some bugs in yolox * Add RetinaFace Model support * fixed retinaface/api.md typos
25 lines
769 B
Python
25 lines
769 B
Python
import fastdeploy as fd
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import cv2
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# 下载模型
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model_url = "https://github.com/DefTruth/Pytorch_Retinaface/releases/download/v0.1/Pytorch_RetinaFace_mobile0.25-640-640.onnx"
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test_img_url = "https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB/raw/master/imgs/3.jpg"
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fd.download(model_url, ".", show_progress=True)
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fd.download(test_img_url, ".", show_progress=True)
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# 加载模型
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model = fd.vision.biubug6.RetinaFace(
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"Pytorch_RetinaFace_mobile0.25-640-640.onnx")
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# 预测图片
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im = cv2.imread("3.jpg")
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result = model.predict(im, conf_threshold=0.7, nms_iou_threshold=0.3)
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# 可视化结果
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fd.vision.visualize.vis_face_detection(im, result)
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cv2.imwrite("vis_result.jpg", im)
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# 输出预测结果
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print(result)
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print(model.runtime_option)
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