Spaces:
Sleeping
Sleeping
Siyun He
commited on
Commit
·
d04b2ef
1
Parent(s):
35c6cce
add transform effect
Browse files- __pycache__/app.cpython-311.pyc +0 -0
- app.py +55 -6
__pycache__/app.cpython-311.pyc
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Binary files a/__pycache__/app.cpython-311.pyc and b/__pycache__/app.cpython-311.pyc differ
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app.py
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@@ -88,18 +88,67 @@ def process_frame(frame):
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return frame
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# Gradio webcam input
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def webcam_input(frame):
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frame = process_frame(frame)
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return frame
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# Gradio Interface
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with gr.Blocks() as demo:
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with gr.
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with gr.
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next_button = gr.Button("Next Glasses")
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input_img.stream(webcam_input, [input_img], [input_img], stream_every=0.1
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next_button.click(change_glasses, [], [])
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if __name__ == "__main__":
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demo.launch(share=True)
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return frame
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# Transform function
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def transform_cv2(frame, transform):
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if transform == "cartoon":
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# prepare color
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img_color = cv2.pyrDown(cv2.pyrDown(frame))
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for _ in range(6):
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img_color = cv2.bilateralFilter(img_color, 9, 9, 7)
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img_color = cv2.pyrUp(cv2.pyrUp(img_color))
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# prepare edges
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img_edges = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
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img_edges = cv2.adaptiveThreshold(
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cv2.medianBlur(img_edges, 7),
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255,
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cv2.ADAPTIVE_THRESH_MEAN_C,
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cv2.THRESH_BINARY,
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9,
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2,
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)
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img_edges = cv2.cvtColor(img_edges, cv2.COLOR_GRAY2RGB)
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# combine color and edges
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img = cv2.bitwise_and(img_color, img_edges)
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return img
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elif transform == "edges":
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# perform edge detection
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img = cv2.cvtColor(cv2.Canny(frame, 100, 200), cv2.COLOR_GRAY2BGR)
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return img
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else:
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return frame
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# Gradio webcam input
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def webcam_input(frame, transform):
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frame = process_frame(frame)
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frame = transform_cv2(frame, transform)
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return frame
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# Gradio Interface
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with gr.Blocks() as demo:
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with gr.Column(elem_classes=["my-column"]):
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with gr.Group(elem_classes=["my-group"]):
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transform = gr.Dropdown(choices=["cartoon", "edges", "none"],
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value="none", label="Transformation")
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input_img = gr.Image(sources=["webcam"], type="numpy", streaming=True)
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next_button = gr.Button("Next Glasses")
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input_img.stream(webcam_input, [input_img, transform], [input_img], time_limit=30, stream_every=0.1)
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next_button.click(change_glasses, [], [])
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if __name__ == "__main__":
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demo.launch(share=True)
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# # Gradio Interface
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# with gr.Blocks() as demo:
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# with gr.Row():
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# with gr.Column():
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# input_img = gr.Image(label="Input", sources="webcam", streaming=True)
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# next_button = gr.Button("Next Glasses")
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# input_img.stream(webcam_input, [input_img], [input_img], stream_every=0.1, concurrency_limit=30)
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# next_button.click(change_glasses, [], [])
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# if __name__ == "__main__":
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# demo.launch(share=True)
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