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import gradio as gr |
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import os |
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from pathlib import Path |
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import sys |
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import torch |
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from PIL import Image, ImageOps |
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from utils_ootd import get_mask_location |
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PROJECT_ROOT = Path(__file__).absolute().parents[1].absolute() |
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sys.path.insert(0, str(PROJECT_ROOT)) |
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from preprocess.openpose.run_openpose import OpenPose |
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from preprocess.humanparsing.run_parsing import Parsing |
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from ootd.inference_ootd_hd import OOTDiffusionHD |
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from ootd.inference_ootd_dc import OOTDiffusionDC |
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import spaces |
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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(1) |
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parsing_model_dc = Parsing(1) |
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ootd_model_dc = OOTDiffusionDC(1) |
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category_dict = ['upperbody', 'lowerbody', 'dress'] |
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category_dict_utils = ['upper_body', 'lower_body', 'dresses'] |
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example_path = os.path.join(os.path.dirname(__file__), 'examples') |
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model_hd = os.path.join(example_path, 'model/model_1.png') |
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garment_hd = os.path.join(example_path, 'garment/03244_00.jpg') |
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model_dc = os.path.join(example_path, 'model/model_8.png') |
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garment_dc = os.path.join(example_path, 'garment/048554_1.jpg') |
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+@spaces.GPU |
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def process_hd(vton_img, garm_img, n_samples, n_steps, image_scale, seed): |
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model_type = 'hd' |
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category = 0 |
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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_hd(vton_img.resize((384, 512))) |
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model_parse, _ = parsing_model_hd(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_hd( |
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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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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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with block: |
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with gr.Row(): |
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gr.Markdown("# OOTDiffusion Demo") |
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with gr.Row(): |
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gr.Markdown("## Half-body") |
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with gr.Row(): |
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gr.Markdown("***Support upper-body garments***") |
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with gr.Row(): |
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with gr.Column(): |
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vton_img = gr.Image(label="Model", sources='upload', type="filepath", height=384, value=model_hd) |
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example = gr.Examples( |
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inputs=vton_img, |
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examples_per_page=14, |
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examples=[ |
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os.path.join(example_path, 'model/model_1.png'), |
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os.path.join(example_path, 'model/model_2.png'), |
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os.path.join(example_path, 'model/model_3.png'), |
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os.path.join(example_path, 'model/model_4.png'), |
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os.path.join(example_path, 'model/model_5.png'), |
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os.path.join(example_path, 'model/model_6.png'), |
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os.path.join(example_path, 'model/model_7.png'), |
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os.path.join(example_path, 'model/01008_00.jpg'), |
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os.path.join(example_path, 'model/07966_00.jpg'), |
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os.path.join(example_path, 'model/05997_00.jpg'), |
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os.path.join(example_path, 'model/02849_00.jpg'), |
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os.path.join(example_path, 'model/14627_00.jpg'), |
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os.path.join(example_path, 'model/09597_00.jpg'), |
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os.path.join(example_path, 'model/01861_00.jpg'), |
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]) |
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with gr.Column(): |
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garm_img = gr.Image(label="Garment", sources='upload', type="filepath", height=384, value=garment_hd) |
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example = gr.Examples( |
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inputs=garm_img, |
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examples_per_page=14, |
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examples=[ |
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os.path.join(example_path, 'garment/03244_00.jpg'), |
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os.path.join(example_path, 'garment/00126_00.jpg'), |
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os.path.join(example_path, 'garment/03032_00.jpg'), |
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os.path.join(example_path, 'garment/06123_00.jpg'), |
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os.path.join(example_path, 'garment/02305_00.jpg'), |
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os.path.join(example_path, 'garment/00055_00.jpg'), |
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os.path.join(example_path, 'garment/00470_00.jpg'), |
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os.path.join(example_path, 'garment/02015_00.jpg'), |
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os.path.join(example_path, 'garment/10297_00.jpg'), |
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os.path.join(example_path, 'garment/07382_00.jpg'), |
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os.path.join(example_path, 'garment/07764_00.jpg'), |
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os.path.join(example_path, 'garment/00151_00.jpg'), |
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os.path.join(example_path, 'garment/12562_00.jpg'), |
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os.path.join(example_path, 'garment/04825_00.jpg'), |
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]) |
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with gr.Column(): |
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result_gallery = 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 = gr.Button(value="Run") |
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n_samples = gr.Slider(label="Images", minimum=1, maximum=4, value=1, step=1) |
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n_steps = gr.Slider(label="Steps", minimum=20, maximum=40, value=20, step=1) |
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image_scale = gr.Slider(label="Guidance scale", minimum=1.0, maximum=5.0, value=2.0, step=0.1) |
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seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, value=-1) |
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ips = [vton_img, garm_img, n_samples, n_steps, image_scale, seed] |
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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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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() |
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