Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -93,25 +93,6 @@ with gr.Blocks(css=css) as demo:
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colored_normal_file = gr.File(label="Colored Normal Image", elem_id="download")
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raw_normal_file = gr.File(label="Raw Normal Data (.npy)", elem_id="download")
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# with gr.Row():
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# input_image = gr.Image(label="Input Image", type='numpy', elem_id='img-display-input')
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# depth_image_slider = ImageSlider(label="Depth Map with Slider View", elem_id='img-display-output', position=0.5)
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# with gr.Row():
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# submit = gr.Button(value="Compute Depth")
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# processing_res_choice = gr.Radio(
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# [
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# ("Recommended (768)", 768),
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# ("Native", 0),
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# ],
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# label="Processing resolution",
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# value=768,
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# )
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# gray_depth_file = gr.File(label="Grayscale depth map", elem_id="download",)
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# raw_file = gr.File(label="Raw Depth Data (.npy)", elem_id="download")
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cmap = matplotlib.colormaps.get_cmap('Spectral_r')
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def on_submit(image, processing_res_choice):
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@@ -150,24 +131,6 @@ with gr.Blocks(css=css) as demo:
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tmp_npy_normal.name
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)
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# pil_image = Image.fromarray(image.astype('uint8'))
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# depth_npy, depth_colored = predict_depth(pil_image, processing_res_choice)
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# # Save the npy data (raw depth map)
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# tmp_npy_depth = tempfile.NamedTemporaryFile(suffix='.npy', delete=False)
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# np.save(tmp_npy_depth.name, depth_npy)
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# # Save the grayscale depth map
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# depth_gray = (depth_npy * 65535.0).astype(np.uint16)
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# tmp_gray_depth = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
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# Image.fromarray(depth_gray).save(tmp_gray_depth.name, mode="I;16")
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# # Save the colored depth map
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# tmp_colored_depth = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
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# depth_colored.save(tmp_colored_depth.name)
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# return [(image, depth_colored), tmp_gray_depth.name, tmp_npy_depth.name]
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submit.click(on_submit, inputs=[input_image, processing_res_choice], outputs=[depth_image_slider,normal_image_slider,colored_depth_file,gray_depth_file,raw_depth_file,colored_normal_file,raw_normal_file])
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example_files = os.listdir('assets/examples')
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colored_normal_file = gr.File(label="Colored Normal Image", elem_id="download")
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raw_normal_file = gr.File(label="Raw Normal Data (.npy)", elem_id="download")
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cmap = matplotlib.colormaps.get_cmap('Spectral_r')
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def on_submit(image, processing_res_choice):
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tmp_npy_normal.name
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)
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submit.click(on_submit, inputs=[input_image, processing_res_choice], outputs=[depth_image_slider,normal_image_slider,colored_depth_file,gray_depth_file,raw_depth_file,colored_normal_file,raw_normal_file])
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example_files = os.listdir('assets/examples')
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