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from mtcnn.mtcnn import MTCNN |
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from utils import * |
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cloth_examples = get_cloth_examples() |
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pose_examples = get_pose_examples() |
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tip1, tip2 = get_tips() |
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face_detector = MTCNN() |
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title = r""" |
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<h1 align="center">Outfit Anyone in the Wild: Get rid of Annoying Restrictions for Virtual Try-on Task</h1> |
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""" |
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description = r""" |
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<b>Official π€ Gradio demo</b> for <a href='https://github.com/selfitcamera/Outfit-Anyone-in-the-Wild' target='_blank'><b>Outfit Anyone in the Wild: Get rid of Annoying Restrictions for Virtual Try-on Task</b></a>.<br> |
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1. Clothing models are fixed in this demo, but you can create your own in our WeChat applet (for Chainese users). |
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2. You can upload your own pose photo, then click the run button and wait for 3~5 minutes to see the results. |
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3. After submitting the task, feel free to leave this page. Everytime you refresh this page, completed tasks will be displayed on the history tab (bind with your ip address). |
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4. Share your try-on photo with your friends and enjoy! π.<br> |
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<b>Test results on </b> <a href='https://selfitcamera.online/ClothData/Publics/Shows/shows/man_v2/man_v2.html' target='_blank'><b>man01</b></a>.<br> |
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<b>Test results on </b> <a href='https://selfitcamera.online/ClothData/Publics/Shows/shows/cider/cider_0403.html' target='_blank'><b>woman01</b></a>.<br> |
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<b>Test results on </b> <a href='https://selfitcamera.online/ClothData/Publics/Shows/shows/baifa/baifa_0408.html' target='_blank'><b>woman02</b></a>.<br> |
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""" |
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css = """ |
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.gradio-container {width: 85% !important} |
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""" |
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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" |
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def onUpload(): |
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return "" |
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def onClick(cloth_id, pose_image, pose_id, size, request: gr.Request): |
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if pose_image is None: |
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return None, "no pose image found !", "" |
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if len(pose_id)>0: |
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res = get_result_example(cloth_id, pose_id) |
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assert os.path.exists(res), res |
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return res, "Done! Use the pre-run results directly, the cloth size does not take effect ", mk_guide |
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else: |
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try: |
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client_ip = request.client.host |
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x_forwarded_for = dict(request.headers).get('x-forwarded-for') |
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if x_forwarded_for: |
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client_ip = x_forwarded_for |
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faces = face_detector.detect_faces(pose_image[:,:,::-1]) |
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if len(faces)==0: |
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client_ip = request.client.host |
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print(client_ip, 'faces num is 0! ', flush=True) |
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return None, "Fatal Error !!! No face detected !!! You must upload a human photo!!! Not clothing photo!!!", "" |
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timeId = int( str(time.time()).replace(".", "") )+random.randint(1000, 9999) |
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isUpload = upload_pose_img(ApiUrl, OpenId, ApiKey, client_ip, timeId, pose_image) |
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if isUpload==0: |
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return None, "fail to upload", "" |
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elif isUpload==-1: |
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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~", "" |
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elif isUpload==-2: |
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return None, "can not creat task, you have exhausted free trial quota", "" |
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taskId = publicClothSwap(ApiUrl, OpenId, ApiKey, client_ip, cloth_id, timeId, size) |
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if taskId==0: |
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return None, "fail to public you task", "" |
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max_try = 1 |
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wait_s = 30 |
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for i in range(max_try): |
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time.sleep(wait_s) |
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state = getInfRes(ApiUrl, OpenId, ApiKey, client_ip, timeId) |
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if state=='stateIs-1': |
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return None, "task failed, it may be that no human was detected, or there may be illegal content, etc. ", "" |
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elif state=='stateIs0': |
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return None, "task not public success", "" |
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elif len(state)>20: |
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return state, "task finished", "" |
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elif (not state.startswith('stateIs')): |
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pass |
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else: |
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return None, state, "" |
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return None, "task has been created successfully, you can refresh the page 5~15 mins latter, and check the following history tab", "" |
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except Exception as e: |
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print(e) |
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return None, "fail to create task", "" |
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def onLoad(request: gr.Request): |
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client_ip = request.client.host |
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x_forwarded_for = dict(request.headers).get('x-forwarded-for') |
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if x_forwarded_for: |
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client_ip = x_forwarded_for |
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his_datas = [None for _ in range(10)] |
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info = '' |
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try: |
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infs = getAllInfs(ApiUrl, OpenId, ApiKey, client_ip) |
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print(client_ip, 'history infs: ', len(infs)) |
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cnt = 0 |
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finish_n, fail_n, queue_n = 0, 0, 0 |
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for i, inf in enumerate(infs): |
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if inf['state']==2: |
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if cnt>4: continue |
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pose, res = inf['pose'], inf['res'] |
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his_datas[cnt*2] = f"<img src=\"{pose}\" >" |
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his_datas[cnt*2+1] = f"<img src=\"{res}\" >" |
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finish_n += 1 |
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cnt += 1 |
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elif inf['state'] in [-1, -2, 0]: |
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fail_n += 1 |
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elif inf['state'] in [1]: |
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queue_n += 1 |
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info = f"{client_ip}, you have {finish_n} successed tasks, {queue_n} running tasks, {fail_n} failed tasks." |
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if fail_n>0: |
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info = info+" Please upload a half/full-body human image, not just a clothing image!!!" |
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if queue_n>0: |
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info = info+" Wait for 3~10 mins and refresh this page, successed results will display in the history tab at the bottom" |
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time.sleep(3) |
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except Exception as e: |
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print(e) |
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his_datas = his_datas + [info] |
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return his_datas |
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with gr.Blocks(css=css) as demo: |
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gr.Markdown(title) |
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gr.Markdown(description) |
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with gr.Accordion('upload tips', open=False): |
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with gr.Row(): |
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gr.HTML(f"<img src=\"{tip1}\" >") |
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gr.HTML(f"<img src=\"{tip2}\" >") |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Column(): |
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cloth_image = gr.Image(sources='clipboard', type="filepath", label="", |
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value=None) |
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cloth_id = gr.Label(value=cloth_examples[0][0], label="Clothing 3D Model", visible=False) |
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example = gr.Examples(inputs=[cloth_id, cloth_image], |
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examples_per_page=3, |
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examples = cloth_examples) |
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with gr.Column(): |
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with gr.Column(): |
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pose_image = gr.Image(value=None, type="numpy", label="") |
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pose_id = gr.Label(value=pose_examples[0][0], label="Pose Image", visible=False) |
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example_pose = gr.Examples(inputs=[pose_id, pose_image], |
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examples_per_page=3, |
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examples=pose_examples) |
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with gr.Column(): |
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with gr.Column(): |
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size_slider = gr.Slider(-2.5, 2.5, value=1, interactive=True, label="clothes size") |
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info_text = gr.Textbox(value="", interactive=False, |
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label='runtime information') |
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run_button = gr.Button(value="Run") |
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init_res = get_result_example(cloth_examples[0][0], pose_examples[0][0]) |
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res_image = gr.Image(label="result image", value=None, type="filepath") |
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MK01 = gr.Markdown() |
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with gr.Tab('history'): |
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with gr.Row(): |
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MK02 = gr.Markdown() |
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with gr.Row(): |
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his_pose_image1 = gr.HTML() |
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his_res_image1 = gr.HTML() |
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with gr.Row(): |
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his_pose_image2 = gr.HTML() |
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his_res_image2 = gr.HTML() |
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with gr.Row(): |
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his_pose_image3 = gr.HTML() |
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his_res_image3 = gr.HTML() |
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with gr.Row(): |
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his_pose_image4 = gr.HTML() |
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his_res_image4 = gr.HTML() |
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with gr.Row(): |
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his_pose_image5 = gr.HTML() |
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his_res_image5 = gr.HTML() |
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run_button.click(fn=onClick, inputs=[cloth_id, pose_image, pose_id, size_slider], |
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outputs=[res_image, info_text, MK01], concurrency_limit=50) |
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pose_image.upload(fn=onUpload, inputs=[], outputs=[pose_id],) |
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demo.load(onLoad, inputs=[], outputs=[his_pose_image1, his_res_image1, |
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his_pose_image2, his_res_image2, his_pose_image3, his_res_image3, |
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his_pose_image4, his_res_image4, his_pose_image5, his_res_image5, |
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MK02]) |
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if __name__ == "__main__": |
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demo.queue(max_size=50) |
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demo.launch(server_name='0.0.0.0') |
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