[~] Refactor
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@ -843,3 +843,41 @@ def kernel_9_benchmark(
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pprint.pprint(
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pprint.pprint(
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['kernel_9_benchmark', dict(t4=t4, t5=t5)]
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['kernel_9_benchmark', dict(t4=t4, t5=t5)]
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)
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)
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def kernel_10():
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import torch
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# Model
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model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # or yolov5m, yolov5x, custom
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# Images
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img = 'https://ultralytics.com/images/zidane.jpg' # or file, PIL, OpenCV, numpy, multiple
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# Inference
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results = model(img)
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# Results
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results.print() # or .show(), .save(), .crop(), .pandas(), etc.
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return dict(
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model=model,
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)
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def kernel_11_benchmark(
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o_7,
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o_10,
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):
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import datetime
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t1 = o_7['cv2'].imread('../input/indonesian-traditional-dance/tgagrakanyar/tga_0000.jpg')
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t5 = 10
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t2 = datetime.datetime.now()
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for k in range(t5):
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t6 = o_10['model'](img_ori)
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t7 = t6.pandas().xywhn
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t3 = datetime.datetime.now()
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t4 = (t3 - t2).total_seconds() / t5
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pprint.pprint(
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['kernel_11_benchmark', dict(t4=t4, t5=t5)]
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)
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