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app.py
CHANGED
@@ -31,8 +31,8 @@ image_model_config_dict = OrderedDict({
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"ASLDM-256-obj": {
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# "config": "./configs/image_cond_diffuser_asl/image-ASLDM-256.yaml",
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# "ckpt_path": "./checkpoints/image_cond_diffuser_asl/image-ASLDM-256.ckpt",
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"config": "
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"ckpt_path": "
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},
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})
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@@ -40,8 +40,8 @@ text_model_config_dict = OrderedDict({
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"ASLDM-256": {
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# "config": "./configs/text_cond_diffuser_asl/text-ASLDM-256.yaml",
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# "ckpt_path": "./checkpoints/text_cond_diffuser_asl/text-ASLDM-256.ckpt",
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"config": "
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"ckpt_path": "
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},
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})
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@@ -313,7 +313,7 @@ with gr.Blocks() as app:
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gr.Markdown("2. Note that the Image-conditioned model is trained on multiple 3D datasets like ShapeNet and Objaverse")
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gr.Markdown("3. We provide some examples for you to try. You can also upload images or text as input.")
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gr.Markdown("4. Welcome to share your amazing results with us, and thanks for your interest in our work!")
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-
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with gr.Row():
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with gr.Column():
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@@ -360,7 +360,7 @@ with gr.Blocks() as app:
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file_out = gr.File(label="Files", visible=False)
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outputs = [model_3d, file_out]
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-
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img.upload(disable_cache, outputs=cache_dir)
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examples.select(set_cache, outputs=[img, cache_dir])
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print(f'line:404: {cache_dir}')
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"ASLDM-256-obj": {
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# "config": "./configs/image_cond_diffuser_asl/image-ASLDM-256.yaml",
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# "ckpt_path": "./checkpoints/image_cond_diffuser_asl/image-ASLDM-256.ckpt",
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"config": "/home/user/app/configs/image_cond_diffuser_asl/image-ASLDM-256.yaml",
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"ckpt_path": "/home/user/app/checkpoints/image_cond_diffuser_asl/image-ASLDM-256.ckpt",
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},
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})
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"ASLDM-256": {
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# "config": "./configs/text_cond_diffuser_asl/text-ASLDM-256.yaml",
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# "ckpt_path": "./checkpoints/text_cond_diffuser_asl/text-ASLDM-256.ckpt",
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"config": "/home/user/app/configs/text_cond_diffuser_asl/text-ASLDM-256.yaml",
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"ckpt_path": "/home/user/app/checkpoints/text_cond_diffuser_asl/text-ASLDM-256.ckpt",
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},
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})
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gr.Markdown("2. Note that the Image-conditioned model is trained on multiple 3D datasets like ShapeNet and Objaverse")
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gr.Markdown("3. We provide some examples for you to try. You can also upload images or text as input.")
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gr.Markdown("4. Welcome to share your amazing results with us, and thanks for your interest in our work!")
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print(os.path.abspath(os.path.dirname(__file__)))
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with gr.Row():
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with gr.Column():
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file_out = gr.File(label="Files", visible=False)
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outputs = [model_3d, file_out]
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img.upload(disable_cache, outputs=cache_dir)
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examples.select(set_cache, outputs=[img, cache_dir])
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print(f'line:404: {cache_dir}')
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configs/image_cond_diffuser_asl/image-ASLDM-256.yaml
CHANGED
@@ -24,7 +24,7 @@ model:
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target: michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
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params:
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# clip_model_version: "./checkpoints/clip/clip-vit-large-patch14"
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clip_model_version: "
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loss_cfg:
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target: torch.nn.Identity
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@@ -33,7 +33,7 @@ model:
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target: michelangelo.models.conditional_encoders.encoder_factory.FrozenCLIPImageGridEmbedder
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params:
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# version: "./checkpoints/clip/clip-vit-large-patch14"
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version: "
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zero_embedding_radio: 0.1
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first_stage_key: "surface"
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target: michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
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params:
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# clip_model_version: "./checkpoints/clip/clip-vit-large-patch14"
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clip_model_version: "/home/user/app/checkpoints/clip/clip-vit-large-patch14"
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loss_cfg:
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target: torch.nn.Identity
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target: michelangelo.models.conditional_encoders.encoder_factory.FrozenCLIPImageGridEmbedder
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params:
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# version: "./checkpoints/clip/clip-vit-large-patch14"
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version: "/home/user/app/checkpoints/clip/clip-vit-large-patch14"
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zero_embedding_radio: 0.1
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first_stage_key: "surface"
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configs/text_cond_diffuser_asl/text-ASLDM-256.yaml
CHANGED
@@ -23,7 +23,7 @@ model:
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aligned_module_cfg:
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target: michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
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params:
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clip_model_version: "
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loss_cfg:
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target: torch.nn.Identity
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@@ -31,7 +31,7 @@ model:
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cond_stage_config:
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target: michelangelo.models.conditional_encoders.encoder_factory.FrozenAlignedCLIPTextEmbedder
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params:
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version: "
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zero_embedding_radio: 0.1
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max_length: 77
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aligned_module_cfg:
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target: michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
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params:
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clip_model_version: "/home/user/app/checkpoints/clip/clip-vit-large-patch14"
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loss_cfg:
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target: torch.nn.Identity
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cond_stage_config:
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target: michelangelo.models.conditional_encoders.encoder_factory.FrozenAlignedCLIPTextEmbedder
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params:
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version: "/home/user/app/checkpoints/clip/clip-vit-large-patch14"
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zero_embedding_radio: 0.1
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max_length: 77
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