chenlei
commited on
Commit
·
8c19fbe
1
Parent(s):
bfa0351
update
Browse files- ootd/inference_ootd_dc.py +4 -4
- run/gradio_ootd.py +119 -119
ootd/inference_ootd_dc.py
CHANGED
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@@ -24,10 +24,10 @@ import torch.nn.functional as F
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from transformers import AutoProcessor, CLIPVisionModelWithProjection
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from transformers import CLIPTextModel, CLIPTokenizer
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VIT_PATH = "
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VAE_PATH = "
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UNET_PATH = "
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MODEL_PATH =
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class OOTDiffusionDC:
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from transformers import AutoProcessor, CLIPVisionModelWithProjection
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from transformers import CLIPTextModel, CLIPTokenizer
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VIT_PATH = "openai/clip-vit-large-patch14"
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VAE_PATH = "levihsu/OOTDiffusion"
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UNET_PATH = "levihsu/OOTDiffusion"
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MODEL_PATH ="/home/user/app/checkpoints/ootd"
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class OOTDiffusionDC:
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run/gradio_ootd.py
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@@ -21,9 +21,9 @@ openpose_model_hd = OpenPose(0)
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parsing_model_hd = Parsing(0)
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ootd_model_hd = OOTDiffusionHD(0)
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openpose_model_dc = OpenPose(0)
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parsing_model_dc = Parsing(0)
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ootd_model_dc = OOTDiffusionDC(0)
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category_dict = ['upperbody', 'lowerbody', 'dress']
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return images
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def process_dc(vton_img, garm_img, category, n_samples, n_steps, image_scale, seed):
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block = gr.Blocks().queue()
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@@ -169,92 +169,92 @@ with block:
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run_button.click(fn=process_hd, inputs=ips, outputs=[result_gallery])
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with gr.Row():
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with gr.Row():
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with gr.Row():
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with gr.Column():
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ips_dc = [vton_img_dc, garm_img_dc, category_dc, n_samples_dc, n_steps_dc, image_scale_dc, seed_dc]
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run_button_dc.click(fn=process_dc, inputs=ips_dc, outputs=[result_gallery_dc])
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block.launch(server_name='0.0.0.0', server_port=7865)
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parsing_model_hd = Parsing(0)
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ootd_model_hd = OOTDiffusionHD(0)
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# openpose_model_dc = OpenPose(0)
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# parsing_model_dc = Parsing(0)
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# ootd_model_dc = OOTDiffusionDC(0)
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category_dict = ['upperbody', 'lowerbody', 'dress']
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return images
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# def process_dc(vton_img, garm_img, category, n_samples, n_steps, image_scale, seed):
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# model_type = 'dc'
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# if category == 'Upper-body':
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# category = 0
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# elif category == 'Lower-body':
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# category = 1
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# else:
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# category =2
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# with torch.no_grad():
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# garm_img = Image.open(garm_img).resize((768, 1024))
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# vton_img = Image.open(vton_img).resize((768, 1024))
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# keypoints = openpose_model_dc(vton_img.resize((384, 512)))
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# model_parse, _ = parsing_model_dc(vton_img.resize((384, 512)))
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# mask, mask_gray = get_mask_location(model_type, category_dict_utils[category], model_parse, keypoints)
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# mask = mask.resize((768, 1024), Image.NEAREST)
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# mask_gray = mask_gray.resize((768, 1024), Image.NEAREST)
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# masked_vton_img = Image.composite(mask_gray, vton_img, mask)
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# images = ootd_model_dc(
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# model_type=model_type,
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# category=category_dict[category],
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# image_garm=garm_img,
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# image_vton=masked_vton_img,
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# mask=mask,
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# image_ori=vton_img,
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# num_samples=n_samples,
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# num_steps=n_steps,
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# image_scale=image_scale,
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# seed=seed,
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# )
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# return images
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block = gr.Blocks().queue()
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run_button.click(fn=process_hd, inputs=ips, outputs=[result_gallery])
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# with gr.Row():
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# gr.Markdown("## Full-body")
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# with gr.Row():
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# gr.Markdown("***Support upper-body/lower-body/dresses; garment category must be paired!!!***")
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# with gr.Row():
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# with gr.Column():
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# vton_img_dc = gr.Image(label="Model", sources='upload', type="filepath", height=384, value=model_dc)
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# example = gr.Examples(
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# label="Examples (upper-body/lower-body)",
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# inputs=vton_img_dc,
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# examples_per_page=7,
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# examples=[
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# os.path.join(example_path, 'model/model_8.png'),
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# os.path.join(example_path, 'model/049447_0.jpg'),
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# os.path.join(example_path, 'model/049713_0.jpg'),
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# os.path.join(example_path, 'model/051482_0.jpg'),
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# os.path.join(example_path, 'model/051918_0.jpg'),
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# os.path.join(example_path, 'model/051962_0.jpg'),
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# os.path.join(example_path, 'model/049205_0.jpg'),
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# ])
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# example = gr.Examples(
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# label="Examples (dress)",
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# inputs=vton_img_dc,
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# examples_per_page=7,
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# examples=[
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# os.path.join(example_path, 'model/model_9.png'),
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# os.path.join(example_path, 'model/052767_0.jpg'),
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# os.path.join(example_path, 'model/052472_0.jpg'),
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# os.path.join(example_path, 'model/053514_0.jpg'),
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# os.path.join(example_path, 'model/053228_0.jpg'),
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# os.path.join(example_path, 'model/052964_0.jpg'),
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# os.path.join(example_path, 'model/053700_0.jpg'),
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# ])
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# with gr.Column():
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# garm_img_dc = gr.Image(label="Garment", sources='upload', type="filepath", height=384, value=garment_dc)
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# category_dc = gr.Dropdown(label="Garment category (important option!!!)", choices=["Upper-body", "Lower-body", "Dress"], value="Upper-body")
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# example = gr.Examples(
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# label="Examples (upper-body)",
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# inputs=garm_img_dc,
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# examples_per_page=7,
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# examples=[
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# os.path.join(example_path, 'garment/048554_1.jpg'),
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# os.path.join(example_path, 'garment/049920_1.jpg'),
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# os.path.join(example_path, 'garment/049965_1.jpg'),
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# os.path.join(example_path, 'garment/049949_1.jpg'),
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# os.path.join(example_path, 'garment/050181_1.jpg'),
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# os.path.join(example_path, 'garment/049805_1.jpg'),
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# os.path.join(example_path, 'garment/050105_1.jpg'),
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# ])
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# example = gr.Examples(
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# label="Examples (lower-body)",
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# inputs=garm_img_dc,
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# examples_per_page=7,
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# examples=[
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# os.path.join(example_path, 'garment/051827_1.jpg'),
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# os.path.join(example_path, 'garment/051946_1.jpg'),
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# os.path.join(example_path, 'garment/051473_1.jpg'),
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# os.path.join(example_path, 'garment/051515_1.jpg'),
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# os.path.join(example_path, 'garment/051517_1.jpg'),
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# os.path.join(example_path, 'garment/051988_1.jpg'),
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# os.path.join(example_path, 'garment/051412_1.jpg'),
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# ])
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# example = gr.Examples(
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# label="Examples (dress)",
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# inputs=garm_img_dc,
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# examples_per_page=7,
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# examples=[
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# os.path.join(example_path, 'garment/053290_1.jpg'),
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# os.path.join(example_path, 'garment/053744_1.jpg'),
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# os.path.join(example_path, 'garment/053742_1.jpg'),
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# os.path.join(example_path, 'garment/053786_1.jpg'),
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# os.path.join(example_path, 'garment/053790_1.jpg'),
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# os.path.join(example_path, 'garment/053319_1.jpg'),
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# os.path.join(example_path, 'garment/052234_1.jpg'),
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# ])
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# with gr.Column():
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# result_gallery_dc = gr.Gallery(label='Output', show_label=False, elem_id="gallery", preview=True, scale=1)
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# with gr.Column():
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# run_button_dc = gr.Button(value="Run")
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# n_samples_dc = gr.Slider(label="Images", minimum=1, maximum=4, value=1, step=1)
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# n_steps_dc = gr.Slider(label="Steps", minimum=20, maximum=40, value=20, step=1)
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# # scale_dc = gr.Slider(label="Scale", minimum=1.0, maximum=12.0, value=5.0, step=0.1)
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# image_scale_dc = gr.Slider(label="Guidance scale", minimum=1.0, maximum=5.0, value=2.0, step=0.1)
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# seed_dc = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, value=-1)
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# ips_dc = [vton_img_dc, garm_img_dc, category_dc, n_samples_dc, n_steps_dc, image_scale_dc, seed_dc]
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# run_button_dc.click(fn=process_dc, inputs=ips_dc, outputs=[result_gallery_dc])
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block.launch(server_name='0.0.0.0', server_port=7865)
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