change_loading_options
Browse files
app.py
CHANGED
@@ -105,7 +105,10 @@ if type == "local":
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"std": "../data_hf/data/motionverse/statistics/std.npy",
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"skeleton": "../data_hf/data/motionverse/statistics/skeleton.npy",
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"lmm": "../data_hf/data/motionverse/pretrained/lmm_small_demo.pth",
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-
"imagebind": "../data_hf/data/motionverse/pretrained/imagebind_huge.pth"
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}
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os.environ["NO_PROXY"] = os.environ["no_proxy"] = "localhost, 127.0.0.1:7860"
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else:
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@@ -114,7 +117,10 @@ else:
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"std": "data/motionverse/statistics/std.npy",
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"skeleton": "data/motionverse/statistics/skeleton.npy",
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"lmm": "data/motionverse/pretrained/lmm_small_demo.pth",
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-
"imagebind": "data/motionverse/pretrained/imagebind_huge.pth"
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}
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load_file_list = {}
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for key in src_file_list.keys():
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@@ -238,11 +244,11 @@ demo = gr.Interface(
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inputs=[input_text, input_audio, gr.Slider(20, 200, value=60, label="Motion length (fps 20):")],
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outputs=gr.Video(label="Video:"),
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examples=[
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["A person walks in a circle.", "
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["A person jumps forward.", "
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["A person is stretching arms.", "
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["", "
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["", "
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],
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title="LMM: Large Motion Model for Unified Multi-Modal Motion Generation",
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description="\nThis is an interactive demo for LMM. For more information, feel free to visit our project page(https://github.com/mingyuan-zhang/LMM).")
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"std": "../data_hf/data/motionverse/statistics/std.npy",
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"skeleton": "../data_hf/data/motionverse/statistics/skeleton.npy",
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"lmm": "../data_hf/data/motionverse/pretrained/lmm_small_demo.pth",
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+
"imagebind": "../data_hf/data/motionverse/pretrained/imagebind_huge.pth",
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+
"audio_placeholder": "../data_hf/examples/placeholder.m4a",
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+
"audio_surprise": "../data_hf/examples/surprise.m4a",
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+
"audio_angry": "../data_hf/examples/angry.m4a"
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}
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os.environ["NO_PROXY"] = os.environ["no_proxy"] = "localhost, 127.0.0.1:7860"
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else:
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"std": "data/motionverse/statistics/std.npy",
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"skeleton": "data/motionverse/statistics/skeleton.npy",
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"lmm": "data/motionverse/pretrained/lmm_small_demo.pth",
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+
"imagebind": "data/motionverse/pretrained/imagebind_huge.pth",
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+
"audio_placeholder": "examples/placeholder.m4a",
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+
"audio_surprise": "examples/surprise.m4a",
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"audio_angry": "examples/angry.m4a"
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}
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load_file_list = {}
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for key in src_file_list.keys():
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inputs=[input_text, input_audio, gr.Slider(20, 200, value=60, label="Motion length (fps 20):")],
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outputs=gr.Video(label="Video:"),
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examples=[
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+
["A person walks in a circle.", load_file_list["audio_placeholder"], 120],
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["A person jumps forward.", load_file_list["audio_placeholder"], 100],
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["A person is stretching arms.", load_file_list["audio_placeholder"], 80],
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["", load_file_list["audio_surprise"], 200],
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["", load_file_list["audio_angry"], 200],
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],
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title="LMM: Large Motion Model for Unified Multi-Modal Motion Generation",
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description="\nThis is an interactive demo for LMM. For more information, feel free to visit our project page(https://github.com/mingyuan-zhang/LMM).")
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