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support rgba input
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app.py
CHANGED
@@ -61,7 +61,10 @@ This model is trained on Objaverse-LVIS (**~45K** synthetic objects) only. And n
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2. Please wait until the completion of the reconstruction of the previous model before proceeding with the next one, otherwise, it may cause bug. We will fix it soon.
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"""
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def preprocess(image_path, save_path=None, lower_contrast=False):
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input_raw = Image.open(image_path)
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input_raw.thumbnail([512, 512], Image.Resampling.LANCZOS)
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@@ -125,8 +128,15 @@ def launch(port):
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with gr.Row(variant='panel'):
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with gr.Column(scale=1):
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input_image = gr.Image(value=None, width=512, height=512, type="filepath", label="Input Image")
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camera_dist_slider = gr.Slider(1.0, 4.0, value=1.9, step=0.1, label="Camera Distance")
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img_run_btn = gr.Button("Reconstruction", variant="primary")
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gr.Examples(
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@@ -159,7 +169,7 @@ def launch(port):
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trial_dir = gr.State()
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img_run_btn.click(
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fn=preprocess,
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inputs=[input_image],
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outputs=[seg_image],
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concurrency_limit=1,
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).success(
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2. Please wait until the completion of the reconstruction of the previous model before proceeding with the next one, otherwise, it may cause bug. We will fix it soon.
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"""
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def preprocess(image_path, preprocess, save_path=None, lower_contrast=False):
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if not preprocess:
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return image_path
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input_raw = Image.open(image_path)
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input_raw.thumbnail([512, 512], Image.Resampling.LANCZOS)
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with gr.Row(variant='panel'):
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with gr.Column(scale=1):
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input_image = gr.Image(value=None, image_mode="RGBA", width=512, height=512, type="filepath", label="Input Image")
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gr.Markdown(
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"""
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**Camera distance** denotes the distance between camera center and scene center.
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If you find the 3D model appears flattened, you can increase it. Conversely, if the 3D model appears thick, you can decrease it.
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"""
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)
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camera_dist_slider = gr.Slider(1.0, 4.0, value=1.9, step=0.1, label="Camera Distance")
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preprocess_ckb = gr.Checkbox(value=True, label="Remove background")
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img_run_btn = gr.Button("Reconstruction", variant="primary")
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gr.Examples(
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trial_dir = gr.State()
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img_run_btn.click(
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fn=preprocess,
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inputs=[input_image, preprocess_ckb],
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outputs=[seg_image],
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concurrency_limit=1,
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).success(
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