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Runtime error
Chao Xu
commited on
Commit
โข
2337f0d
1
Parent(s):
d492a58
adjust layout and fix rerun bug
Browse files
app.py
CHANGED
@@ -55,16 +55,16 @@ _DESCRIPTION = '''
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We reconstruct a 3D textured mesh from a single image by initially predicting multi-view images and then lifting them to 3D.
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'''
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_USER_GUIDE = "Please upload an image in the
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_BBOX_1 = "Predicting bounding box for the input image..."
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_BBOX_2 = "Bounding box adjusted. Continue adjusting or **Run Generation**."
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_BBOX_3 = "Bounding box predicted. Adjust it using sliders or **Run Generation**."
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_SAM = "Preprocessing the input image... (safety check, SAM segmentation, *etc*.)"
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_GEN_1 = "Predicting multi-view images... (may take \~
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_GEN_2 = "Predicting nearby views and generating mesh... (may take \~
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_DONE = "Done! Mesh is shown
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_REGEN_1 = "Selected view(s) are regenerated. You can click **Regenerate nearby views and mesh**. <br> Alternatively, if the regenerated view(s) are still not satisfactory, you can repeat the previous step (select the view and regenerate)."
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_REGEN_2 = "Regeneration done.
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class CameraVisualizer:
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def __init__(self, gradio_plot):
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@@ -197,7 +197,7 @@ class CameraVisualizer:
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# width=640,
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# height=480,
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# height=400,
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height=
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autosize=True,
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hovermode=False,
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margin=go.layout.Margin(l=0, r=0, b=0, t=0),
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@@ -279,7 +279,7 @@ def stage1_run(models, device, cam_vis, tmp_dir,
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rerun_idx = [i for i in range(len(btn_retrys)) if btn_retrys[i]]
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# elev_output = estimate_elev(tmp_dir)
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# if elev_output > 75:
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if 90-elev > 75:
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rerun_idx_in = [i if i < 4 else i+4 for i in rerun_idx]
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else:
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rerun_idx_in = rerun_idx
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@@ -525,89 +525,53 @@ def run_demo(
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# Compose demo layout & data flow.
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css="#model-3d-out {height: 400px;}"
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with gr.Blocks(title=_TITLE, css=css) as demo:
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gr.Markdown('# ' + _TITLE)
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gr.Markdown(_DESCRIPTION)
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with gr.Row(variant='panel'):
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with gr.Column(scale=
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image_block = gr.Image(type='pil', image_mode='RGBA', label='Input image', tool=None)
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with gr.Row():
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bbox_block = gr.Image(type='pil', label="Bounding box", interactive=False).style(height=300)
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sam_block = gr.Image(type='pil', label="SAM output", interactive=False)
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max_width = max_height = 256
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with gr.Row():
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x_min_slider = gr.Slider(
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label="X min",
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interactive=True,
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value=0,
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minimum=0,
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maximum=max_width,
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step=1,
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)
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y_min_slider = gr.Slider(
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label="Y min",
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interactive=True,
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value=0,
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minimum=0,
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maximum=max_height,
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step=1,
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)
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with gr.Row():
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x_max_slider = gr.Slider(
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label="X max",
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interactive=True,
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value=max_width,
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minimum=0,
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maximum=max_width,
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step=1,
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)
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y_max_slider = gr.Slider(
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label="Y max",
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interactive=True,
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value=max_height,
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minimum=0,
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maximum=max_height,
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step=1,
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)
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bbox_sliders = [x_min_slider, y_min_slider, x_max_slider, y_max_slider]
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with gr.Column(scale=1.15):
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gr.Examples(
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examples=examples_full, # NOTE: elements must match inputs list!
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# fn=save_img,
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fn=lambda x: x,
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inputs=[image_block],
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# outputs=[image_block, bbox_block, *bbox_sliders],
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outputs=[image_block],
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cache_examples=False,
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run_on_click=True,
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label='Examples (click one of the images below to start)',
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)
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True, label='Reduce image contrast (mitigate shadows on the backside)')
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with gr.Accordion('Advanced options', open=False):
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scale_slider = gr.Slider(0, 30, value=3, step=1,
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label='Diffusion guidance scale')
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steps_slider = gr.Slider(5, 200, value=75, step=5,
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label='Number of diffusion inference steps')
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# with gr.Row():
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run_btn = gr.Button('Run Generation', variant='primary', interactive=False)
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# guide_title = gr.Markdown(_GUIDE_TITLE, visible=True)
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guide_text = gr.Markdown(_USER_GUIDE, visible=True)
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mesh_output = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="One-2-3-45's Textured Mesh", elem_id="model-3d-out")
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with gr.Row(variant='panel'):
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with gr.Column(scale=0.85):
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vis_output = gr.Plot(
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label='Camera poses of the input view (red) and predicted views (blue)')
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with gr.Column(scale=1.15):
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gr.Markdown('Predicted multi-view images')
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@@ -631,7 +595,6 @@ def run_demo(
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btn_retry_6 = gr.Checkbox(label='Retry view 6')
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btn_retry_7 = gr.Checkbox(label='Retry view 7')
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btn_retry_8 = gr.Checkbox(label='Retry view 8')
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# regen_btn = gr.Button('Regenerate selected views and mesh', variant='secondary', visible=False)
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with gr.Row():
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regen_view_btn = gr.Button('1. Regenerate selected view(s)', variant='secondary', visible=False)
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regen_mesh_btn = gr.Button('2. Regenerate nearby views and mesh', variant='secondary', visible=False)
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@@ -683,12 +646,10 @@ def run_demo(
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def on_retry_button_click(*btn_retrys):
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any_checked = any([btn_retry for btn_retry in btn_retrys])
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print('any_checked:', any_checked, [btn_retry for btn_retry in btn_retrys])
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# return regen_btn.update(visible=any_checked)
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if any_checked:
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return (gr.update(visible=True), gr.update(visible=True))
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else:
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return (gr.update(), gr.update())
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# return regen_view_btn.update(visible=any_checked), regen_mesh_btn.update(visible=any_checked)
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# make regen_btn visible when any of the btn_retry is checked
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for btn_retry in btn_retrys:
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# Add the event handlers to the btn_retry buttons
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We reconstruct a 3D textured mesh from a single image by initially predicting multi-view images and then lifting them to 3D.
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'''
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_USER_GUIDE = "Please upload an image in the block above (or choose an example above) and click **Run Generation**."
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_BBOX_1 = "Predicting bounding box for the input image..."
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_BBOX_2 = "Bounding box adjusted. Continue adjusting or **Run Generation**."
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_BBOX_3 = "Bounding box predicted. Adjust it using sliders or **Run Generation**."
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_SAM = "Preprocessing the input image... (safety check, SAM segmentation, *etc*.)"
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_GEN_1 = "Predicting multi-view images... (may take \~21 seconds) <br> Images will be shown in the bottom right blocks."
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_GEN_2 = "Predicting nearby views and generating mesh... (may take \~43 seconds) <br> Mesh will be shown on the right."
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_DONE = "Done! Mesh is shown on the right. <br> If it is not satisfactory, please select **Retry view** checkboxes for inaccurate views and click **Regenerate selected view(s)** at the bottom."
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_REGEN_1 = "Selected view(s) are regenerated. You can click **Regenerate nearby views and mesh**. <br> Alternatively, if the regenerated view(s) are still not satisfactory, you can repeat the previous step (select the view and regenerate)."
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_REGEN_2 = "Regeneration done. Mesh is shown on the right."
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class CameraVisualizer:
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def __init__(self, gradio_plot):
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# width=640,
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# height=480,
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# height=400,
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height=450,
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autosize=True,
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hovermode=False,
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margin=go.layout.Margin(l=0, r=0, b=0, t=0),
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rerun_idx = [i for i in range(len(btn_retrys)) if btn_retrys[i]]
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# elev_output = estimate_elev(tmp_dir)
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# if elev_output > 75:
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if 90-int(elev["label"]) > 75:
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rerun_idx_in = [i if i < 4 else i+4 for i in rerun_idx]
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else:
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rerun_idx_in = rerun_idx
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# Compose demo layout & data flow.
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css = "#model-3d-out {height: 400px;} #plot-out {height: 425px;}"
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with gr.Blocks(title=_TITLE, css=css) as demo:
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gr.Markdown('# ' + _TITLE)
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gr.Markdown(_DESCRIPTION)
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with gr.Row(variant='panel'):
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with gr.Column(scale=1.2):
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image_block = gr.Image(type='pil', image_mode='RGBA', label='Input image', tool=None).style(height=290)
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gr.Examples(
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examples=examples_full, # NOTE: elements must match inputs list!
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inputs=[image_block],
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outputs=[image_block],
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cache_examples=False,
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label='Examples (click one of the images below to start)',
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)
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with gr.Accordion('Advanced options', open=False):
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preprocess_chk = gr.Checkbox(
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False, label='Reduce image contrast (mitigate shadows on the backside)')
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scale_slider = gr.Slider(0, 30, value=3, step=1,
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label='Diffusion guidance scale')
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steps_slider = gr.Slider(5, 200, value=75, step=5,
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label='Number of diffusion inference steps')
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run_btn = gr.Button('Run Generation', variant='primary', interactive=False)
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guide_text = gr.Markdown(_USER_GUIDE, visible=True)
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with gr.Column(scale=.8):
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with gr.Row():
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bbox_block = gr.Image(type='pil', label="Bounding box", interactive=False).style(height=290)
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sam_block = gr.Image(type='pil', label="SAM output", interactive=False)
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max_width = max_height = 256
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with gr.Row():
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x_min_slider = gr.Slider(label="X min", interactive=True, value=0, minimum=0, maximum=max_width, step=1)
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y_min_slider = gr.Slider(label="Y min", interactive=True, value=0, minimum=0, maximum=max_height, step=1)
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with gr.Row():
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x_max_slider = gr.Slider(label="X max", interactive=True, value=max_width, minimum=0, maximum=max_width, step=1)
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y_max_slider = gr.Slider(label="Y max", interactive=True, value=max_height, minimum=0, maximum=max_height, step=1)
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bbox_sliders = [x_min_slider, y_min_slider, x_max_slider, y_max_slider]
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mesh_output = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="One-2-3-45's Textured Mesh", elem_id="model-3d-out")
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with gr.Row(variant='panel'):
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with gr.Column(scale=0.85):
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elev_output = gr.Label(label='Estimated elevation (degree, w.r.t. the horizontal plane)')
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vis_output = gr.Plot(label='Camera poses of the input view (red) and predicted views (blue)', elem_id="plot-out")
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with gr.Column(scale=1.15):
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gr.Markdown('Predicted multi-view images')
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btn_retry_6 = gr.Checkbox(label='Retry view 6')
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btn_retry_7 = gr.Checkbox(label='Retry view 7')
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btn_retry_8 = gr.Checkbox(label='Retry view 8')
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with gr.Row():
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regen_view_btn = gr.Button('1. Regenerate selected view(s)', variant='secondary', visible=False)
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regen_mesh_btn = gr.Button('2. Regenerate nearby views and mesh', variant='secondary', visible=False)
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def on_retry_button_click(*btn_retrys):
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any_checked = any([btn_retry for btn_retry in btn_retrys])
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print('any_checked:', any_checked, [btn_retry for btn_retry in btn_retrys])
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if any_checked:
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return (gr.update(visible=True), gr.update(visible=True))
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else:
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return (gr.update(), gr.update())
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# make regen_btn visible when any of the btn_retry is checked
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for btn_retry in btn_retrys:
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# Add the event handlers to the btn_retry buttons
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