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Update app.py
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app.py
CHANGED
@@ -3,6 +3,7 @@ import os
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os.system("wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt")
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os.system("wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-e6e.pt")
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import argparse
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import time
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@@ -22,7 +23,7 @@ from utils.torch_utils import select_device, load_classifier, time_synchronized,
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from PIL import Image
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parser = argparse.ArgumentParser()
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parser.add_argument('--weights', nargs='+', type=str, default='yolov7-
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parser.add_argument('--source', type=str, default='Inference/', help='source') # file/folder, 0 for webcam
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parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
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parser.add_argument('--conf-thres', type=float, default=0.25, help='object confidence threshold')
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@@ -185,7 +186,7 @@ def detect(img):
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with torch.no_grad():
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if opt.update: # update all models (to fix SourceChangeWarning)
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for opt.weights in ['yolov7-
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strip_optimizer(opt.weights)
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gr.Interface(detect,gr.Image(type="pil"), gr.Image(type="pil"),title="Yolov7",examples=[["horses.jpeg"]],description="demo for <a href='https://github.com/WongKinYiu/yolov7' style='text-decoration: underline' target='_blank'>WongKinYiu/yolov7</a> Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors").launch()
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os.system("wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt")
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os.system("wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-e6e.pt")
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os.system("wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-e6.pt")
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import argparse
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import time
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from PIL import Image
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parser = argparse.ArgumentParser()
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parser.add_argument('--weights', nargs='+', type=str, default='yolov7-e6.pt', help='model.pt path(s)')
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parser.add_argument('--source', type=str, default='Inference/', help='source') # file/folder, 0 for webcam
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parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
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parser.add_argument('--conf-thres', type=float, default=0.25, help='object confidence threshold')
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with torch.no_grad():
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if opt.update: # update all models (to fix SourceChangeWarning)
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for opt.weights in ['yolov7-e6.pt']:
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strip_optimizer(opt.weights)
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gr.Interface(detect,gr.Image(type="pil"), gr.Image(type="pil"),title="Yolov7",examples=[["horses.jpeg"]],description="demo for <a href='https://github.com/WongKinYiu/yolov7' style='text-decoration: underline' target='_blank'>WongKinYiu/yolov7</a> Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors").launch()
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