Delete app.py

app.py

@@ -1,261 +0,0 @@
-import gradio as gr
-import os
-from pathlib import Path
-import sys
-import torch
-from PIL import Image, ImageOps
-
-from run.utils_ootd import get_mask_location
-
-PROJECT_ROOT = Path(__file__).absolute().parents[0].absolute()
-sys.path.insert(0, str(PROJECT_ROOT))
-
-from preprocess.openpose.run_openpose import OpenPose
-from preprocess.humanparsing.run_parsing import Parsing
-from ootd.inference_ootd_hd import OOTDiffusionHD
-from ootd.inference_ootd_dc import OOTDiffusionDC
-
-import spaces
-
-
-openpose_model_hd = OpenPose(0)
-parsing_model_hd = Parsing(0)
-ootd_model_hd = OOTDiffusionHD(0)
-
-openpose_model_dc = OpenPose(1)
-parsing_model_dc = Parsing(1)
-ootd_model_dc = OOTDiffusionDC(1)
-
-
-category_dict = ['upperbody', 'lowerbody', 'dress']
-category_dict_utils = ['upper_body', 'lower_body', 'dresses']
-
-example_path = os.path.join(os.path.dirname(__file__), 'run/examples')
-model_hd = os.path.join(example_path, 'model/model_1.png')
-garment_hd = os.path.join(example_path, 'garment/03244_00.jpg')
-model_dc = os.path.join(example_path, 'model/model_8.png')
-garment_dc = os.path.join(example_path, 'garment/048554_1.jpg')
-
-@spaces.GPU
-def process_hd(vton_img, garm_img, n_samples, n_steps, image_scale, seed):
-    model_type = 'hd'
-    category = 0 # 0:upperbody; 1:lowerbody; 2:dress
-
-    with torch.no_grad():
-        garm_img = Image.open(garm_img).resize((768, 1024))
-        vton_img = Image.open(vton_img).resize((768, 1024))
-        keypoints = openpose_model_hd(vton_img.resize((384, 512)))
-        model_parse, _ = parsing_model_hd(vton_img.resize((384, 512)))
-
-        mask, mask_gray = get_mask_location(model_type, category_dict_utils[category], model_parse, keypoints)
-        mask = mask.resize((768, 1024), Image.NEAREST)
-        mask_gray = mask_gray.resize((768, 1024), Image.NEAREST)
-        
-        masked_vton_img = Image.composite(mask_gray, vton_img, mask)
-
-        images = ootd_model_hd(
-            model_type=model_type,
-            category=category_dict[category],
-            image_garm=garm_img,
-            image_vton=masked_vton_img,
-            mask=mask,
-            image_ori=vton_img,
-            num_samples=n_samples,
-            num_steps=n_steps,
-            image_scale=image_scale,
-            seed=seed,
-        )
-
-    return images
-
-def process_dc(vton_img, garm_img, category, n_samples, n_steps, image_scale, seed):
-    model_type = 'dc'
-    if category == 'Upper-body':
-        category = 0
-    elif category == 'Lower-body':
-        category = 1
-    else:
-        category =2
-
-    with torch.no_grad():
-        garm_img = Image.open(garm_img).resize((768, 1024))
-        vton_img = Image.open(vton_img).resize((768, 1024))
-        keypoints = openpose_model_dc(vton_img.resize((384, 512)))
-        model_parse, _ = parsing_model_dc(vton_img.resize((384, 512)))
-
-        mask, mask_gray = get_mask_location(model_type, category_dict_utils[category], model_parse, keypoints)
-        mask = mask.resize((768, 1024), Image.NEAREST)
-        mask_gray = mask_gray.resize((768, 1024), Image.NEAREST)
-        
-        masked_vton_img = Image.composite(mask_gray, vton_img, mask)
-
-        images = ootd_model_dc(
-            model_type=model_type,
-            category=category_dict[category],
-            image_garm=garm_img,
-            image_vton=masked_vton_img,
-            mask=mask,
-            image_ori=vton_img,
-            num_samples=n_samples,
-            num_steps=n_steps,
-            image_scale=image_scale,
-            seed=seed,
-        )
-
-    return images
-
-
-block = gr.Blocks().queue()
-with block:
-    with gr.Row():
-        gr.Markdown("# OOTDiffusion Demo")
-    with gr.Row():
-        gr.Markdown("## Half-body")
-    with gr.Row():
-        gr.Markdown("***Support upper-body garments***")
-    with gr.Row():
-        with gr.Column():
-            vton_img = gr.Image(label="Model", sources='upload', type="filepath", height=384, value=model_hd)
-            example = gr.Examples(
-                inputs=vton_img,
-                examples_per_page=14,
-                examples=[
-                    os.path.join(example_path, 'model/model_1.png'),
-                    os.path.join(example_path, 'model/model_2.png'),
-                    os.path.join(example_path, 'model/model_3.png'),
-                    os.path.join(example_path, 'model/model_4.png'),
-                    os.path.join(example_path, 'model/model_5.png'),
-                    os.path.join(example_path, 'model/model_6.png'),
-                    os.path.join(example_path, 'model/model_7.png'),
-                    os.path.join(example_path, 'model/01008_00.jpg'),
-                    os.path.join(example_path, 'model/07966_00.jpg'),
-                    os.path.join(example_path, 'model/05997_00.jpg'),
-                    os.path.join(example_path, 'model/02849_00.jpg'),
-                    os.path.join(example_path, 'model/14627_00.jpg'),
-                    os.path.join(example_path, 'model/09597_00.jpg'),
-                    os.path.join(example_path, 'model/01861_00.jpg'),
-                ])
-        with gr.Column():
-            garm_img = gr.Image(label="Garment", sources='upload', type="filepath", height=384, value=garment_hd)
-            example = gr.Examples(
-                inputs=garm_img,
-                examples_per_page=14,
-                examples=[
-                    os.path.join(example_path, 'garment/03244_00.jpg'),
-                    os.path.join(example_path, 'garment/00126_00.jpg'),
-                    os.path.join(example_path, 'garment/03032_00.jpg'),
-                    os.path.join(example_path, 'garment/06123_00.jpg'),
-                    os.path.join(example_path, 'garment/02305_00.jpg'),
-                    os.path.join(example_path, 'garment/00055_00.jpg'),
-                    os.path.join(example_path, 'garment/00470_00.jpg'),
-                    os.path.join(example_path, 'garment/02015_00.jpg'),
-                    os.path.join(example_path, 'garment/10297_00.jpg'),
-                    os.path.join(example_path, 'garment/07382_00.jpg'),
-                    os.path.join(example_path, 'garment/07764_00.jpg'),
-                    os.path.join(example_path, 'garment/00151_00.jpg'),
-                    os.path.join(example_path, 'garment/12562_00.jpg'),
-                    os.path.join(example_path, 'garment/04825_00.jpg'),
-                ])
-        with gr.Column():
-            result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery", preview=True, scale=1)   
-    with gr.Column():
-        run_button = gr.Button(value="Run")
-        n_samples = gr.Slider(label="Images", minimum=1, maximum=4, value=1, step=1)
-        n_steps = gr.Slider(label="Steps", minimum=20, maximum=40, value=20, step=1)
-        # scale = gr.Slider(label="Scale", minimum=1.0, maximum=12.0, value=5.0, step=0.1)
-        image_scale = gr.Slider(label="Guidance scale", minimum=1.0, maximum=5.0, value=2.0, step=0.1)
-        seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, value=-1)
-        
-    ips = [vton_img, garm_img, n_samples, n_steps, image_scale, seed]
-    run_button.click(fn=process_hd, inputs=ips, outputs=[result_gallery])
-
-
-    with gr.Row():
-        gr.Markdown("## Full-body")
-    with gr.Row():
-        gr.Markdown("***Support upper-body/lower-body/dresses; garment category must be paired!!!***")
-    with gr.Row():
-        with gr.Column():
-            vton_img_dc = gr.Image(label="Model", sources='upload', type="filepath", height=384, value=model_dc)
-            example = gr.Examples(
-                label="Examples (upper-body/lower-body)",
-                inputs=vton_img_dc,
-                examples_per_page=7,
-                examples=[
-                    os.path.join(example_path, 'model/model_8.png'),
-                    os.path.join(example_path, 'model/049447_0.jpg'),
-                    os.path.join(example_path, 'model/049713_0.jpg'),
-                    os.path.join(example_path, 'model/051482_0.jpg'),
-                    os.path.join(example_path, 'model/051918_0.jpg'),
-                    os.path.join(example_path, 'model/051962_0.jpg'),
-                    os.path.join(example_path, 'model/049205_0.jpg'),
-                ])
-            example = gr.Examples(
-                label="Examples (dress)",
-                inputs=vton_img_dc,
-                examples_per_page=7,
-                examples=[
-                    os.path.join(example_path, 'model/model_9.png'),
-                    os.path.join(example_path, 'model/052767_0.jpg'),
-                    os.path.join(example_path, 'model/052472_0.jpg'),
-                    os.path.join(example_path, 'model/053514_0.jpg'),
-                    os.path.join(example_path, 'model/053228_0.jpg'),
-                    os.path.join(example_path, 'model/052964_0.jpg'),
-                    os.path.join(example_path, 'model/053700_0.jpg'),
-                ])
-        with gr.Column():
-            garm_img_dc = gr.Image(label="Garment", sources='upload', type="filepath", height=384, value=garment_dc)
-            category_dc = gr.Dropdown(label="Garment category (important option!!!)", choices=["Upper-body", "Lower-body", "Dress"], value="Upper-body")
-            example = gr.Examples(
-                label="Examples (upper-body)",
-                inputs=garm_img_dc,
-                examples_per_page=7,
-                examples=[
-                    os.path.join(example_path, 'garment/048554_1.jpg'),
-                    os.path.join(example_path, 'garment/049920_1.jpg'),
-                    os.path.join(example_path, 'garment/049965_1.jpg'),
-                    os.path.join(example_path, 'garment/049949_1.jpg'),
-                    os.path.join(example_path, 'garment/050181_1.jpg'),
-                    os.path.join(example_path, 'garment/049805_1.jpg'),
-                    os.path.join(example_path, 'garment/050105_1.jpg'),
-                ])
-            example = gr.Examples(
-                label="Examples (lower-body)",
-                inputs=garm_img_dc,
-                examples_per_page=7,
-                examples=[
-                    os.path.join(example_path, 'garment/051827_1.jpg'),
-                    os.path.join(example_path, 'garment/051946_1.jpg'),
-                    os.path.join(example_path, 'garment/051473_1.jpg'),
-                    os.path.join(example_path, 'garment/051515_1.jpg'),
-                    os.path.join(example_path, 'garment/051517_1.jpg'),
-                    os.path.join(example_path, 'garment/051988_1.jpg'),
-                    os.path.join(example_path, 'garment/051412_1.jpg'),
-                ])
-            example = gr.Examples(
-                label="Examples (dress)",
-                inputs=garm_img_dc,
-                examples_per_page=7,
-                examples=[
-                    os.path.join(example_path, 'garment/053290_1.jpg'),
-                    os.path.join(example_path, 'garment/053744_1.jpg'),
-                    os.path.join(example_path, 'garment/053742_1.jpg'),
-                    os.path.join(example_path, 'garment/053786_1.jpg'),
-                    os.path.join(example_path, 'garment/053790_1.jpg'),
-                    os.path.join(example_path, 'garment/053319_1.jpg'),
-                    os.path.join(example_path, 'garment/052234_1.jpg'),
-                ])
-        with gr.Column():
-            result_gallery_dc = gr.Gallery(label='Output', show_label=False, elem_id="gallery", preview=True, scale=1)   
-    with gr.Column():
-        run_button_dc = gr.Button(value="Run")
-        n_samples_dc = gr.Slider(label="Images", minimum=1, maximum=4, value=1, step=1)
-        n_steps_dc = gr.Slider(label="Steps", minimum=20, maximum=40, value=20, step=1)
-        # scale_dc = gr.Slider(label="Scale", minimum=1.0, maximum=12.0, value=5.0, step=0.1)
-        image_scale_dc = gr.Slider(label="Guidance scale", minimum=1.0, maximum=5.0, value=2.0, step=0.1)
-        seed_dc = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, value=-1)
-        
-    ips_dc = [vton_img_dc, garm_img_dc, category_dc, n_samples_dc, n_steps_dc, image_scale_dc, seed_dc]
-    run_button_dc.click(fn=process_dc, inputs=ips_dc, outputs=[result_gallery_dc])
-
-block.launch()