app.py

from mtcnn.mtcnn import MTCNN
from utils import *



cloth_examples = get_cloth_examples()
pose_examples = get_pose_examples()
tip1, tip2 = get_tips()
face_detector = MTCNN()

# Description
title = r"""
<h1 align="center">Outfit Anyone in the Wild: Get rid of Annoying Restrictions for Virtual Try-on Task</h1>
"""

description = r"""
<b>Official 🤗 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>
1. Clothing models are fixed in this demo, but you can create your own in our WeChat applet (for Chainese users).
2. You can upload your own pose photo, then click the run button and wait for 3~5 minutes to see the results.
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).
4. Share your try-on photo with your friends and enjoy! 😊.<br>
<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>
<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>
<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>
"""

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_id, pose_image, pose_id, size, request: gr.Request):
    if pose_image is None:
        return None, "no pose image found !", ""

    # pose_id, cloth_id = pose_id['label'], cloth_id['label']
    # print(pose_id, cloth_id, size, (pose_image is None), len(pose_id)>0)
    if len(pose_id)>0:
        res = get_result_example(cloth_id, pose_id)
        # print(res)
        assert os.path.exists(res), res
        # res = cv2.imread(res)
        return res, "Done! Use the pre-run results directly, the cloth size does not take effect ", mk_guide
    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:
                client_ip = request.client.host
                print(client_ip, 'faces num is 0! ', flush=True)
                return None, "Fatal Error !!! No face detected !!! You must upload a human photo!!! Not clothing photo!!!", ""
            
            timeId = int(  str(time.time()).replace(".", "")  )+random.randint(1000, 9999)
            isUpload = upload_pose_img(ApiUrl, OpenId, ApiKey, client_ip, timeId, pose_image)
            if isUpload==0:
                return None, "fail to upload", ""
            elif isUpload==-1:
                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 isUpload==-2:
                return None, "can not creat task, you have exhausted free trial quota", ""

            taskId = publicClothSwap(ApiUrl, OpenId, ApiKey, client_ip, cloth_id, timeId, size)
            if taskId==0:
                return None, "fail to public you task", ""

            max_try = 1
            wait_s = 30
            for i in range(max_try):
                time.sleep(wait_s)
                state = getInfRes(ApiUrl, OpenId, ApiKey, client_ip, timeId)
                if state=='stateIs-1':
                    return None, "task failed, it may be that no human was detected, or there may be illegal content, etc. ", ""
                elif state=='stateIs0':
                    return None, "task not public success", ""
                elif len(state)>20:
                    return state, "task finished", ""
                elif (not state.startswith('stateIs')):
                    # return None, 'task is in queue, position is '+str(state)
                    pass
                else:
                    return None, state, ""
            return None, "task has been created successfully, you can refresh the page 5~15 mins latter, and check the following history tab", ""
        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 = getAllInfs(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:
            info = info+" Wait for 3~10 mins and refresh this page, successed results will display in the history tab at the bottom"
        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.Accordion('upload tips', open=False):
        with gr.Row():
            gr.HTML(f"<img src=\"{tip1}\" >")
            gr.HTML(f"<img src=\"{tip2}\" >")
                    
    with gr.Row():
        with gr.Column():
            with gr.Column():
                # cloth_image = gr.Image(type="numpy", value=cloth_examples[0][1], label="")
                cloth_image = gr.Image(sources='clipboard', type="filepath", label="", 
                    value=None)
                cloth_id = gr.Label(value=cloth_examples[0][0], label="Clothing 3D Model", 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(source='upload', value=pose_examples[0][1], 
                #     type="numpy", label="")
                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():
                size_slider = gr.Slider(-2.5, 2.5, value=1, interactive=True, label="clothes size")
                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")
                # res_image = gr.Image(label="result image", value=None, type="numpy")
                # res_image = gr.Image(label="result image", value=cv2.imread(init_res), 
                #     type="numpy")
                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_id, pose_image, pose_id, size_slider], 
                     outputs=[res_image, info_text, MK01], concurrency_limit=50)

    pose_image.upload(fn=onUpload, inputs=[], outputs=[pose_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.queue(concurrency_count=60)
    # demo.launch(server_name='0.0.0.0', server_port=225)
    demo.launch(server_name='0.0.0.0')