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Update app.py
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app.py
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import gradio as gr
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import torch
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def snap(video):
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return [video]
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model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt')
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# Define the face detector function
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# def detect_faces(image):
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# # Loading in yolov5s - you can switch to larger models such as yolov5m or yolov5l, or smaller such as yolov5n
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# results = model(image)
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# return results.render()[0]
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# Create a Gradio interface
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iface = gr.Interface(
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snap,
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)
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# import gradio as gr
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# import torch
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# model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt')
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# # Define the face detector function
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# def detect_faces(image):
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# # Loading in yolov5s - you can switch to larger models such as yolov5m or yolov5l, or smaller such as yolov5n
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# results = model(image)
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# return results.render()[0]
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# # Create a Gradio interface
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# iface = gr.Interface(fn=detect_faces, inputs="image", outputs="image")
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# # Launch the interface
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# iface.launch(debug=True)
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import gradio as gr
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def snap(video):
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results = model(image)
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return [results.render()[0], video]
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# def detect_faces(image):
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# # # Loading in yolov5s - you can switch to larger models such as yolov5m or yolov5l, or smaller such as yolov5n
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# results = model(image)
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# return results.render()[0]
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demo = gr.Interface(
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snap,
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inputs = gr.Video(source="webcam"),
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outputs = "image",
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if __name__ == "__main__":
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demo.launch()
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