Spaces:
Running
on
Zero
Running
on
Zero
Add slider view and cache examples (#3)
Browse files- Add slider view (21401baacb957c78a138966bc35a6ef8db6af5d5)
- Cache examples (392f705912d2c6bd326dfcbe79becb9f3cfc7792)
Co-authored-by: hysts <[email protected]>
- app.py +9 -6
- requirements.txt +2 -1
app.py
CHANGED
@@ -8,6 +8,7 @@ import torch
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import torch.nn.functional as F
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from torchvision.transforms import Compose
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import tempfile
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from depth_anything.dpt import DPT_DINOv2
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from depth_anything.util.transform import Resize, NormalizeImage, PrepareForNet
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@@ -58,11 +59,13 @@ with gr.Blocks(css=css) as demo:
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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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-
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raw_file = gr.File(label="16-bit raw depth (can be considered as disparity)")
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submit = gr.Button("Submit")
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def on_submit(image):
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h, w = image.shape[:2]
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) / 255.0
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@@ -80,16 +83,16 @@ with gr.Blocks(css=css) as demo:
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depth = depth.cpu().numpy().astype(np.uint8)
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colored_depth = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)[:, :, ::-1]
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return [colored_depth, tmp.name]
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submit.click(on_submit, inputs=[input_image], outputs=[depth_image, raw_file])
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example_files = os.listdir('examples')
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example_files.sort()
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example_files = [os.path.join('examples', filename) for filename in example_files]
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examples = gr.Examples(examples=example_files, inputs=[input_image])
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if __name__ == '__main__':
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demo.queue().launch()
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import torch.nn.functional as F
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from torchvision.transforms import Compose
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import tempfile
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from gradio_imageslider import ImageSlider
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from depth_anything.dpt import DPT_DINOv2
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from depth_anything.util.transform import Resize, NormalizeImage, PrepareForNet
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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)
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raw_file = gr.File(label="16-bit raw depth (can be considered as disparity)")
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submit = gr.Button("Submit")
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def on_submit(image):
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original_image = image.copy()
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h, w = image.shape[:2]
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) / 255.0
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depth = depth.cpu().numpy().astype(np.uint8)
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colored_depth = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)[:, :, ::-1]
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return [(original_image, colored_depth), tmp.name]
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submit.click(on_submit, inputs=[input_image], outputs=[depth_image_slider, raw_file])
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example_files = os.listdir('examples')
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example_files.sort()
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example_files = [os.path.join('examples', filename) for filename in example_files]
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examples = gr.Examples(examples=example_files, inputs=[input_image], outputs=[depth_image_slider, raw_file], fn=on_submit, cache_examples=True)
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if __name__ == '__main__':
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demo.queue().launch()
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requirements.txt
CHANGED
@@ -1,3 +1,4 @@
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torch
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torchvision
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opencv-python
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gradio_imageslider
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torch
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torchvision
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opencv-python
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