updates
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10
detect.py
10
detect.py
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@ -43,7 +43,13 @@ def detect(save_txt=False, save_img=False):
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# Export mode
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if ONNX_EXPORT:
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img = torch.zeros((1, 3) + img_size) # (1, 3, 320, 192)
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torch.onnx.export(model, img, 'weights/export.onnx', verbose=True)
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torch.onnx.export(model, img, 'weights/export.onnx', verbose=False, opset_version=11)
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# Validate exported model
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import onnx
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model = onnx.load('weights/export.onnx') # Load the ONNX model
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onnx.checker.check_model(model) # Check that the IR is well formed
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print(onnx.helper.printable_graph(model.graph)) # Print a human readable representation of the graph
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return
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# Half precision
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@ -148,7 +154,7 @@ if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
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parser.add_argument('--weights', type=str, default='weights/yolov3-spp.weights', help='path to weights file')
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parser.add_argument('--weights', type=str, default='weights/last49.pt', help='path to weights file')
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parser.add_argument('--source', type=str, default='data/samples', help='source') # input file/folder, 0 for webcam
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parser.add_argument('--output', type=str, default='output', help='output folder') # output folder
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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