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| from mtcnn.mtcnn import MTCNN | |
| from utils import * | |
| cloth_examples = get_cloth_examples() | |
| pose_examples = get_pose_examples() | |
| face_detector = MTCNN() | |
| # Description | |
| title = r""" | |
| <h1 align="center">IDM-VTON + Outfit Anyone in the Wild </h1> | |
| """ | |
| description = r""" | |
| This demo combines <a href='https://github.com/yisol/IDM-VTON' target='_blank'><b>IDM-VTON </b></a> and <a href='https://github.com/selfitcamera/Outfit-Anyone-in-the-Wild' target='_blank'><b>Outfit Anyone in the Wild </b></a> | |
| 1. Human body detection and reconstruction using large human models from Outfit Anyone in the Wild. | |
| 2. Use IDM-VTON for single-picture clothing change without training. | |
| 3. Fix discordant parts of your image using the refine network from Outfit Anyone in the Wild. | |
| This demo is for learning purposes only. | |
| <b>IDM-VTON + Outfit Anyone in the Wild test results on </b> <a href='https://heybeautify.online/ClothData/Publics/Shows/shows/IDM_OutfitAnyone/IDM_OutfitAnyone.html' target='_blank'><b>mix01</b></a>. | |
| <b>Outfit Anyone in the Wild test results on </b> <a href='https://heybeautify.online/ClothData/Publics/Shows/shows/man_v2/man_v2.html' target='_blank'><b>man01</b></a>. | |
| <b>Outfit Anyone in the Wild test results on </b> <a href='https://heybeautify.online/ClothData/Publics/Shows/shows/cider/cider_0403.html' target='_blank'><b>woman01</b></a>.<br> | |
| """ | |
| css = """ | |
| .gradio-container {width: 85% !important} | |
| """ | |
| mk_guide = "If image does not display successfully after button clicked in your browser(mostly Mac+Chrome), try [this demo](https://openxlab.org.cn/apps/detail/jiangxiaoguo/OutfitAnyone-in-the-Wild) please" | |
| def onUpload(): | |
| return "" | |
| def onClick(cloth_image, cloth_id, pose_image, pose_id, category, | |
| denoise_steps, caption, request: gr.Request): | |
| if pose_image is None: | |
| return None, "no pose image found !", "" | |
| if isinstance(cloth_id, dict): | |
| cloth_id = cloth_id['label'] | |
| if isinstance(pose_id, dict): | |
| pose_id = pose_id['label'] | |
| if len(pose_id)>0: | |
| res = get_result_example(cloth_id, pose_id) | |
| assert os.path.exists(res), res | |
| return res, "Done! Use the pre-run results directly, the cloth size does not take effect ", "" | |
| else: | |
| try: | |
| client_ip = request.client.host | |
| x_forwarded_for = dict(request.headers).get('x-forwarded-for') | |
| if x_forwarded_for: | |
| client_ip = x_forwarded_for | |
| faces = face_detector.detect_faces(pose_image[:,:,::-1]) | |
| if len(faces)==0: | |
| print(client_ip, 'faces num is 0! ', flush=True) | |
| return None, "Fatal Error !!! No face detected in pose image !!! ", "" | |
| else: | |
| x, y, w, h = faces[0]["box"] | |
| H, W = pose_image.shape[:2] | |
| max_face_ratio = 1/3.3 | |
| if w/W>max_face_ratio or h/H>max_face_ratio: | |
| return None, "Fatal Error !!! Headshot is not allowed in pose image!!!", "" | |
| if not check_warp(client_ip): | |
| return None, "Failed !!! Our server is under maintenance, please try again tomorrow", "" | |
| infId = upload_imgs(ApiUrl, OpenId, ApiKey, client_ip, cloth_image, pose_image) | |
| if infId==0: | |
| return None, "fail to upload", "" | |
| elif infId==2: | |
| return None, "There is a running task already, please wait and check the history tab. Please remember to give us a star on github, thx~", "" | |
| elif infId==3: | |
| return None, "can not creat task, you have exhausted free trial quota", "" | |
| isPub = publicFastSwap(ApiUrl, OpenId, ApiKey, infId, category, | |
| caption, denoise_steps) | |
| if not isPub: | |
| return None, "fail to public you task", "" | |
| info = "task has been created successfully, you can refresh the page 1~3 mins latter, and check the following history tab" | |
| info = info+"任务创建成功，请1-3分钟后刷新这个页面，历史结果会显示在下面的标签页" | |
| return None, info, "" | |
| except Exception as e: | |
| print(e) | |
| return None, "fail to create task", "" | |
| def onLoad(request: gr.Request): | |
| client_ip = request.client.host | |
| x_forwarded_for = dict(request.headers).get('x-forwarded-for') | |
| if x_forwarded_for: | |
| client_ip = x_forwarded_for | |
| his_datas = [None for _ in range(10)] | |
| info = '' | |
| try: | |
| infs = getAllFastInfs(ApiUrl, OpenId, ApiKey, client_ip) | |
| print(client_ip, 'history infs: ', len(infs)) | |
| cnt = 0 | |
| finish_n, fail_n, queue_n = 0, 0, 0 | |
| for i, inf in enumerate(infs): | |
| if inf['state']==2: | |
| if cnt>4: continue | |
| pose, res = inf['pose'], inf['res'] | |
| his_datas[cnt*2] = f"<img src=\"{pose}\" >" | |
| his_datas[cnt*2+1] = f"<img src=\"{res}\" >" | |
| finish_n += 1 | |
| cnt += 1 | |
| elif inf['state'] in [-1, -2, 0]: | |
| fail_n += 1 | |
| elif inf['state'] in [1]: | |
| queue_n += 1 | |
| info = f"{client_ip}, you have {finish_n} successed tasks, {queue_n} running tasks, {fail_n} failed tasks." | |
| if fail_n>0: | |
| info = info+" Please upload a half/full-body human image, not just a clothing image!!!" | |
| if queue_n>0: | |
| position = inf['position'] | |
| info = info+" Wait for 3~10 mins and refresh this page, successed results will display in the history tab at the bottom. " | |
| info = info+f" your task position in queue is {position}. " | |
| info = info+f" 任务正在排队，队列位置 {position}. " | |
| time.sleep(3) | |
| except Exception as e: | |
| print(e) | |
| his_datas = his_datas + [info] | |
| return his_datas | |
| with gr.Blocks(css=css) as demo: | |
| # description | |
| gr.Markdown(title) | |
| gr.Markdown(description) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Column(): | |
| cloth_image = gr.Image(value=None, type="numpy", label="") | |
| cloth_id = gr.Label(value=cloth_examples[0][0], label="Clothing Image", visible=False) | |
| example = gr.Examples(inputs=[cloth_id, cloth_image], | |
| examples_per_page=3, | |
| examples = cloth_examples) | |
| with gr.Column(): | |
| with gr.Column(): | |
| pose_image = gr.Image(value=None, type="numpy", label="") | |
| pose_id = gr.Label(value=pose_examples[0][0], label="Pose Image", visible=False) | |
| example_pose = gr.Examples(inputs=[pose_id, pose_image], | |
| examples_per_page=3, | |
| examples=pose_examples) | |
| with gr.Column(): | |
| with gr.Column(): | |
| category = gr.Dropdown(value="upper_cloth", choices=["upper_cloth", | |
| "lower_cloth", "full_body", "dresses"], interactive=True) | |
| denoise_steps = gr.Slider(20, 30, value=20, interactive=True, label="denoise_steps") | |
| caption = gr.Textbox(value="", interactive=True, label='cloth caption') | |
| info_text = gr.Textbox(value="", interactive=False, label='runtime information') | |
| run_button = gr.Button(value="Run") | |
| init_res = get_result_example(cloth_examples[0][0], pose_examples[0][0]) | |
| res_image = gr.Image(label="result image", value=None, type="filepath") | |
| MK01 = gr.Markdown() | |
| with gr.Tab('history'): | |
| with gr.Row(): | |
| MK02 = gr.Markdown() | |
| with gr.Row(): | |
| his_pose_image1 = gr.HTML() | |
| his_res_image1 = gr.HTML() | |
| with gr.Row(): | |
| his_pose_image2 = gr.HTML() | |
| his_res_image2 = gr.HTML() | |
| with gr.Row(): | |
| his_pose_image3 = gr.HTML() | |
| his_res_image3 = gr.HTML() | |
| with gr.Row(): | |
| his_pose_image4 = gr.HTML() | |
| his_res_image4 = gr.HTML() | |
| with gr.Row(): | |
| his_pose_image5 = gr.HTML() | |
| his_res_image5 = gr.HTML() | |
| run_button.click(fn=onClick, inputs=[cloth_image, cloth_id, pose_image, | |
| pose_id, category, denoise_steps, caption, ], | |
| outputs=[res_image, info_text, MK01]) | |
| pose_image.upload(fn=onUpload, inputs=[], outputs=[pose_id],) | |
| cloth_image.upload(fn=onUpload, inputs=[], outputs=[cloth_id],) | |
| demo.load(onLoad, inputs=[], outputs=[his_pose_image1, his_res_image1, | |
| his_pose_image2, his_res_image2, his_pose_image3, his_res_image3, | |
| his_pose_image4, his_res_image4, his_pose_image5, his_res_image5, | |
| MK02]) | |
| if __name__ == "__main__": | |
| demo.queue(max_size=50) | |
| # demo.launch(server_name='0.0.0.0', server_port=225) | |
| demo.launch(server_name='0.0.0.0') | |