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Runtime error
jiaweir
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Commit
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# This is a combination of 2 commits.
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init
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- .gitattributes +2 -1
- app.py +11 -5
- requirements.txt +2 -0
.gitattributes
CHANGED
@@ -33,4 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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-
*.png* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.png* filter=lfs diff=lfs merge=lfs -text
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*.whl filter=lfs diff=lfs merge=lfs -text
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app.py
CHANGED
@@ -6,8 +6,12 @@ from gradio_model4dgs import Model4DGS
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import numpy
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import hashlib
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-
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-
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from huggingface_hub import hf_hub_download
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ckpt_path = hf_hub_download(repo_id="ashawkey/LGM", filename="model_fp16_fixrot.safetensors")
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@@ -34,7 +38,7 @@ def check_video_input(image_block: Image.Image):
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if not os.path.exists(os.path.join('tmp_data', f'{img_hash}_rgba_generated.mp4')):
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raise gr.Error("Please generate a video first")
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-
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def optimize_stage_1(image_block: Image.Image, preprocess_chk: bool, seed_slider: int):
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if not os.path.exists('tmp_data'):
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os.makedirs('tmp_data')
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@@ -55,7 +59,7 @@ def optimize_stage_1(image_block: Image.Image, preprocess_chk: bool, seed_slider
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# return [os.path.join('logs', 'tmp_rgba_model.ply')]
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return os.path.join('tmp_data', f'{img_hash}_rgba_generated.mp4')
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-
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def optimize_stage_2(image_block: Image.Image, seed_slider: int):
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img_hash = hashlib.sha256(image_block.tobytes()).hexdigest()
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subprocess.run(f'python lgm/infer.py big --resume {ckpt_path} --test_path tmp_data/{img_hash}_rgba.png', shell=True)
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@@ -86,6 +90,8 @@ if __name__ == "__main__":
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example_fns.sort()
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examples_full = [os.path.join(example_folder, x) for x in example_fns if x.endswith('.png')]
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# Compose demo layout & data flow
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with gr.Blocks(title=_TITLE, theme=gr.themes.Soft(), js=js_func) as demo:
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with gr.Row():
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@@ -132,4 +138,4 @@ if __name__ == "__main__":
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# demo.queue().launch(share=True)
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demo.queue(max_size=10) # <-- Sets up a queue with default parameters
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demo.launch(
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import numpy
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import hashlib
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import spaces
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@spaces.GPU
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def install():
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subprocess.run(shlex.split("pip install wheel/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl"))
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os.system('pip install xformers==0.0.23 --no-deps --index-url https://download.pytorch.org/whl/cu118')
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from huggingface_hub import hf_hub_download
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ckpt_path = hf_hub_download(repo_id="ashawkey/LGM", filename="model_fp16_fixrot.safetensors")
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if not os.path.exists(os.path.join('tmp_data', f'{img_hash}_rgba_generated.mp4')):
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raise gr.Error("Please generate a video first")
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@spaces.GPU
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def optimize_stage_1(image_block: Image.Image, preprocess_chk: bool, seed_slider: int):
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if not os.path.exists('tmp_data'):
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os.makedirs('tmp_data')
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# return [os.path.join('logs', 'tmp_rgba_model.ply')]
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return os.path.join('tmp_data', f'{img_hash}_rgba_generated.mp4')
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@spaces.GPU
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def optimize_stage_2(image_block: Image.Image, seed_slider: int):
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img_hash = hashlib.sha256(image_block.tobytes()).hexdigest()
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subprocess.run(f'python lgm/infer.py big --resume {ckpt_path} --test_path tmp_data/{img_hash}_rgba.png', shell=True)
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example_fns.sort()
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examples_full = [os.path.join(example_folder, x) for x in example_fns if x.endswith('.png')]
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install()
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# Compose demo layout & data flow
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with gr.Blocks(title=_TITLE, theme=gr.themes.Soft(), js=js_func) as demo:
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with gr.Row():
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# demo.queue().launch(share=True)
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demo.queue(max_size=10) # <-- Sets up a queue with default parameters
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demo.launch()
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requirements.txt
CHANGED
@@ -30,5 +30,7 @@ rembg[gpu,cli]
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# gradio demo
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gradio
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gradio-model4dgs
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-e git+https://github.com/ashawkey/kiuikit.git@main#egg=kiui
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# gradio demo
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gradio
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gradio-model4dgs
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tyro
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roma
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-e git+https://github.com/ashawkey/kiuikit.git@main#egg=kiui
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