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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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from pathlib import Path
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"data": None,
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"is_file": True,
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}
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for file in DATA_PATH.glob("**/*")
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if file.is_file()
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]
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usage = sum([f['size'] for f in files])
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return files, f"{usage/(1024.0 ** 3):.3f}GB"
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with gr.Row():
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with gr.Column():
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app.launch(allowed_paths=[str(DATA_PATH)])
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import numpy as np
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import gradio as gr
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def sepia(input_img, strength):
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sepia_filter = strength * np.array(
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[[0.393, 0.769, 0.189], [0.349, 0.686, 0.168], [0.272, 0.534, 0.131]]
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) + (1-strength) * np.identity(3)
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sepia_img = input_img.dot(sepia_filter.T)
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sepia_img /= sepia_img.max()
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return sepia_img
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callback = gr.CSVLogger()
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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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img_input = gr.Image()
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strength = gr.Slider(0, 1, 0.5)
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img_output = gr.Image()
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with gr.Row():
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btn = gr.Button("Flag")
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# This needs to be called at some point prior to the first call to callback.flag()
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callback.setup([img_input, strength, img_output], "flagged_data_points")
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img_input.change(sepia, [img_input, strength], img_output)
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strength.change(sepia, [img_input, strength], img_output)
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# We can choose which components to flag -- in this case, we'll flag all of them
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btn.click(lambda *args: callback.flag(args), [img_input, strength, img_output], None, preprocess=False)
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demo.launch()
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