Update app.py

app.py

@@ -1,160 +1,275 @@
 import os
+import cv2
+import gradio as gr
 import numpy as np
-import base64
-import json
 import random
-import cv2
-from PIL import Image
+import base64
 import requests
-import gradio as gr
+import json
+import time
 
-# In-memory user storage for demonstration
-users_db = {}
-
-# Ensure the model path is correct
-current_dir = os.path.dirname(os.path.abspath(__file__))
-default_model = os.path.join(current_dir, "models/eva/Eva_0.png")
-
-# Map of AI models with their corresponding file paths
-MODEL_MAP = {
-    "AI Model Rouyan_0": os.path.join(current_dir, 'models/rouyan_new/Rouyan_0.png'),
-    "AI Model Eva_0": os.path.join(current_dir, 'models/eva/Eva_0.png'),
-    "AI Model Eva_1": os.path.join(current_dir, 'models/eva/Eva_1.png'),
-    "AI Model Simon_0": os.path.join(current_dir, 'models/simon_online/Simon_0.png'),
-    "AI Model Simon_1": os.path.join(current_dir, 'models/simon_online/Simon_1.png'),
-    "AI Model Xuanxuan_0": os.path.join(current_dir, 'models/xiaoxuan_online/Xuanxuan_0.png'),
-    "AI Model Xuanxuan_1": os.path.join(current_dir, 'models/xiaoxuan_online/Xuanxuan_1.png'),
-    "AI Model Xuanxuan_2": os.path.join(current_dir, 'models/xiaoxuan_online/Xuanxuan_2.png'),
-    "AI Model Yaqi_0": os.path.join(current_dir, 'models/yaqi/Yaqi_0.png'),
-    "AI Model Yaqi_1": os.path.join(current_dir, 'models/yaqi/Yaqi_1.png'),
-    "AI Model Yaqi_2": os.path.join(current_dir, 'models/yaqi/Yaqi_2.png'),
-    "AI Model Yaqi_3": os.path.join(current_dir, 'models/yaqi/Yaqi_3.png'),
-    "AI Model Yifeng_0": os.path.join(current_dir, 'models/yifeng_online/Yifeng_0.png'),
-    "AI Model Yifeng_1": os.path.join(current_dir, 'models/yifeng_online/Yifeng_1.png'),
-    "AI Model Yifeng_2": os.path.join(current_dir, 'models/yifeng_online/Yifeng_2.png'),
-    "AI Model Yifeng_3": os.path.join(current_dir, 'models/yifeng_online/Yifeng_3.png'),
-}
 
-# Registration function
-def register(username, password, confirm_password):
-    if username in users_db:
-        return "Username already exists", gr.update(visible=True), gr.update(visible=False)
-    if password != confirm_password:
-        return "Passwords do not match", gr.update(visible=True), gr.update(visible=False)
-    users_db[username] = password
-    return "Registration successful! Please login.", gr.update(visible=True), gr.update(visible=False)
-
-# Login function
-def login(username, password):
-    if users_db.get(username) == password:
-        return gr.update(visible=False), gr.update(visible=True)
-    else:
-        return gr.update(visible=True), gr.update(visible=False)
-
-# Watermark function
-def add_watermark(image):
-    height, width, _ = image.shape
-    cv2.putText(image, 'Powered by OutfitAnyone', (int(0.3 * width), height - 20),
-                cv2.FONT_HERSHEY_PLAIN, 2, (128, 128, 128), 2, cv2.LINE_AA)
-    return image
-
-# Try-on result processing
-def get_tryon_result(model_name, top_garment, bottom_garment=None):
-    model_key = "AI Model " + model_name.split("/")[-1].split(".")[0]
-    print(f"Selected model: {model_key}")
-
-    encoded_top = base64.b64encode(cv2.imencode('.jpg', top_garment)[1].tobytes()).decode('utf-8')
-    
-    # Check if bottom_garment is not None and is not an empty array
-    encoded_bottom = ""
-    if bottom_garment is not None and bottom_garment.size > 0:
-        encoded_bottom = base64.b64encode(cv2.imencode('.jpg', bottom_garment)[1].tobytes()).decode('utf-8')
-
-    server_url = os.environ.get('OA_IP_ADDRESS', 'http://localhost:5000')
-    headers = {'Content-Type': 'application/json'}
-    payload = {
-        "garment1": encoded_top,
-        "garment2": encoded_bottom,
-        "model_name": model_key,
-        "seed": random.randint(0, 99999999)
-    }
+def tryon(person_img, garment_img, seed, randomize_seed):
+    post_start_time = time.time()
+    if person_img is None or garment_img is None:
+        gr.Warning("Empty image")
+        return None, None, "Empty image"
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[1].tobytes()
+    encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8')
+    encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes()
+    encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8')
 
+    url = "http://" + os.environ['tryon_url'] + "Submit"
+    token = os.environ['token']
+    cookie = os.environ['Cookie']
+    referer = os.environ['referer']
+    headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer}
+    data = {
+        "clothImage": encoded_garment_img,
+        "humanImage": encoded_person_img,
+        "seed": seed
+    }
     try:
-        response = requests.post(server_url, headers=headers, data=json.dumps(payload))
+        response = requests.post(url, headers=headers, data=json.dumps(data), timeout=50)
+        # print("post response code", response.status_code)
+        if response.status_code == 200:
+            result = response.json()['result']
+            status = result['status']
+            if status == "success":
+                uuid = result['result']
+                # print(uuid)
+    except Exception as err:
+        print(f"Post Exception Error: {err}")
+        raise gr.Error("Too many users, please try again later")
+    post_end_time = time.time()
+    print(f"post time used: {post_end_time-post_start_time}")
+
+    get_start_time =time.time()
+    time.sleep(9)
+    Max_Retry = 12
+    result_img = None
+    info = ""
+    err_log = ""
+    for i in range(Max_Retry):
+        try:
+            url = "http://" + os.environ['tryon_url'] + "Query?taskId=" + uuid
+            response = requests.get(url, headers=headers, timeout=20)
+            # print("get response code", response.status_code)
+            if response.status_code == 200:
+                result = response.json()['result']
+                status = result['status']
+                if status == "success":
+                    result = base64.b64decode(result['result'])
+                    result_np = np.frombuffer(result, np.uint8)
+                    result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
+                    result_img = cv2.cvtColor(result_img, cv2.COLOR_RGB2BGR)
+                    info = "Success"
+                    break
+                elif status == "error":
+                    err_log = f"Status is Error"
+                    info = "Error"
+                    break
+            else:
+                # print(response.text)
+                err_log = "URL error, pleace contact the admin"
+                info = "URL error, pleace contact the admin"
+                break
+        except requests.exceptions.ReadTimeout:
+            err_log = "Http Timeout"
+            info = "Http Timeout, please try again later"
+        except Exception as err:
+            err_log = f"Get Exception Error: {err}"
+        time.sleep(1)
+    get_end_time = time.time()
+    print(f"get time used: {get_end_time-get_start_time}")
+    print(f"all time used: {get_end_time-get_start_time+post_end_time-post_start_time}")
+    if info == "":
+        err_log = f"No image after {Max_Retry} retries"
+        info = "Too many users, please try again later"
+    if info != "Success":
+        print(f"Error Log: {err_log}")
+        gr.Warning("Too many users, please try again later")
+
+    return result_img, seed, info
+
+def start_tryon(person_img, garment_img, seed, randomize_seed):
+    start_time = time.time()
+    if person_img is None or garment_img is None:
+        return None, None, "Empty image"
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[1].tobytes()
+    encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8')
+    encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes()
+    encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8')
 
+    url = "http://" + os.environ['tryon_url']
+    token = os.environ['token']
+    cookie = os.environ['Cookie']
+    referer = os.environ['referer']
+
+    headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer}
+    data = {
+        "clothImage": encoded_garment_img,
+        "humanImage": encoded_person_img,
+        "seed": seed
+    }
+
+    result_img = None
+    try:
+        session = requests.Session()
+        response = session.post(url, headers=headers, data=json.dumps(data), timeout=60)
+        print("response code", response.status_code)
         if response.status_code == 200:
-            result = response.json()
-            result_img = cv2.imdecode(np.frombuffer(base64.b64decode(result['images'][0]), np.uint8), cv2.IMREAD_UNCHANGED)
-            final_img = add_watermark(result_img)
-            return final_img
+            result = response.json()['result']
+            status = result['status']
+            if status == "success":
+                result = base64.b64decode(result['result'])
+                result_np = np.frombuffer(result, np.uint8)
+                result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
+                result_img = cv2.cvtColor(result_img, cv2.COLOR_RGB2BGR)
+                info = "Success"
+            else:
+                info = "Try again latter"
         else:
-            print(f"Error: Server responded with status code {response.status_code}")
-            return None
-    except requests.exceptions.ConnectionError as e:
-        print(f"ConnectionError: Could not connect to server at {server_url}. Please ensure the server is running.")
-        print(f"Details: {e}")
-        return None
-    except requests.exceptions.RequestException as e:
-        print(f"RequestException: An error occurred during the request.")
-        print(f"Details: {e}")
-        return None
-
-# Gradio Interface
-with gr.Blocks() as demo:
-    gr.HTML("<script>console.log('Custom JavaScript');</script>")
-    login_block = gr.Column(visible=True)
-    register_block = gr.Column(visible=False)
-    main_app = gr.Column(visible=False)
-    
-    # Registration Page
-    with register_block:
-        gr.HTML("<h2>Register for Outfit Anyone</h2>")
-        username = gr.Textbox(label="Username")
-        password = gr.Textbox(label="Password", type="password", elem_id="reg_pass")
-        confirm_password = gr.Textbox(label="Confirm Password", type="password", elem_id="reg_conf_pass")
-        register_button = gr.Button("Register")
-        back_to_login_button = gr.Button("Back to Login")
-        register_message = gr.Textbox(label="", visible=False)
-
-    # Login Page
-    with login_block:
-        gr.HTML("<h2>Login to Outfit Anyone</h2>")
-        username_login = gr.Textbox(label="Username")
-        password_login = gr.Textbox(label="Password", type="password", elem_id="login_pass")
-        login_button = gr.Button("Login")
-        go_to_register_button = gr.Button("Register")
-        login_message = gr.Textbox(label="", visible=False)
-    
-    # Main App Interface
-    with main_app:
+            print(response.text)
+            info = "URL error, pleace contact the admin"
+    except requests.exceptions.ReadTimeout:
+        print("timeout")
+        info = "Too many users, please try again later"
+        raise gr.Error("Too many users, please try again later")
+    except Exception as err:
+        print(f"其他错误: {err}")
+        info = "Error, pleace contact the admin"
+    end_time = time.time()
+    print(f"time used: {end_time-start_time}")
+
+    return result_img, seed, info
+
+MAX_SEED = 999999
+
+example_path = os.path.join(os.path.dirname(__file__), 'assets')
+
+garm_list = os.listdir(os.path.join(example_path,"cloth"))
+garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]
+
+human_list = os.listdir(os.path.join(example_path,"human"))
+human_list_path = [os.path.join(example_path,"human",human) for human in human_list]
+
+css="""
+#col-left {
+    margin: 0 auto;
+    max-width: 430px;
+}
+#col-mid {
+    margin: 0 auto;
+    max-width: 430px;
+}
+#col-right {
+    margin: 0 auto;
+    max-width: 430px;
+}
+#col-showcase {
+    margin: 0 auto;
+    max-width: 1100px;
+}
+#button {
+    color: blue;
+}
+"""
+
+def load_description(fp):
+    with open(fp, 'r', encoding='utf-8') as f:
+        content = f.read()
+    return content
+
+def change_imgs(image1, image2):
+    return image1, image2
+
+with gr.Blocks(css=css) as Tryon:
+    gr.HTML(load_description("assets/title.md"))
+    with gr.Row():
+        with gr.Column(elem_id = "col-left"):
+            gr.HTML("""
+            <div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
+                <div>
+                Step 1.  Upload a person image ⬇️
+                </div>
+            </div>
+            """)
+        with gr.Column(elem_id = "col-mid"):
+            gr.HTML("""
+            <div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
+                <div>
+                Step 2. Upload a garment image ⬇️
+                </div>
+            </div>
+            """)
+        with gr.Column(elem_id = "col-right"):
+            gr.HTML("""
+            <div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
+                <div>
+                Step 3. Press “Run” to get try-on results
+                </div>
+            </div>
+            """)
+    with gr.Row():
+        with gr.Column(elem_id = "col-left"):
+            imgs = gr.Image(label="Person image", sources='upload', type="numpy")
+            # category = gr.Dropdown(label="Garment category", choices=['upper_body', 'lower_body', 'dresses'],  value="upper_body")
+            example = gr.Examples(
+                inputs=imgs,
+                examples_per_page=12,
+                examples=human_list_path
+            )
+        with gr.Column(elem_id = "col-mid"):
+            garm_img = gr.Image(label="Garment image", sources='upload', type="numpy")
+            example = gr.Examples(
+                inputs=garm_img,
+                examples_per_page=12,
+                examples=garm_list_path
+            )
+        with gr.Column(elem_id = "col-right"):
+            image_out = gr.Image(label="Result", show_share_button=False)
+            with gr.Row():
+                seed = gr.Slider(
+                    label="Seed",
+                    minimum=0,
+                    maximum=MAX_SEED,
+                    step=1,
+                    value=0,
+                )
+                randomize_seed = gr.Checkbox(label="Random seed", value=True)
+            with gr.Row():
+                seed_used = gr.Number(label="Seed used")
+                result_info = gr.Text(label="Response")
+            # try_button = gr.Button(value="Run", elem_id="button")
+            test_button = gr.Button(value="Run", elem_id="button")
+
+
+    # try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name='tryon',concurrency_limit=10)
+    test_button.click(fn=tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name=False, concurrency_limit=45)
+
+    with gr.Column(elem_id = "col-showcase"):
         gr.HTML("""
-            <div style="text-align: center;">
-                <h1>Outfit Anyone: Virtual Try-On</h1>
-                <h4>v1.0</h4>
-                <p>Upload your garments and choose a model to see the virtual try-on.</p>
+        <div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;">
+            <div> </div>
+            <br>
+            <div>
+            Virtual try-on examples in pairs of person and garment images
             </div>
+        </div>
         """)
-        with gr.Row():
-            with gr.Column():
-                model_selector = gr.Image(sources='upload', type="filepath", label="Model", value=default_model)
-                example_models = gr.Examples(inputs=model_selector, examples=[MODEL_MAP['AI Model Rouyan_0'], MODEL_MAP['AI Model Eva_0']], examples_per_page=4)
-            with gr.Column():
-                gr.HTML("<h3>Select Garments for Virtual Try-On</h3>")
-                top_garment_input = gr.Image(sources='upload', type="numpy", label="Top Garment")
-                bottom_garment_input = gr.Image(sources='upload', type="numpy", label="Bottom Garment (Optional)")
-                generate_button = gr.Button(value="Generate Outfit")
-            with gr.Column():
-                result_display = gr.Image()
-
-                generate_button.click(fn=get_tryon_result, inputs=[model_selector, top_garment_input, bottom_garment_input], outputs=[result_display])
-
-    # Button Click Actions
-    register_button.click(fn=register, inputs=[username, password, confirm_password], outputs=[register_message, register_block, login_block])
-    back_to_login_button.click(lambda: (gr.update(visible=False), gr.update(visible=True)), None, [register_block, login_block])
-    go_to_register_button.click(lambda: (gr.update(visible=True), gr.update(visible=False)), None, [register_block, login_block])
-    login_button.click(fn=login, inputs=[username_login, password_login], outputs=[login_block, main_app])
-    
-if __name__ == "__main__":
-    demo.queue(max_size=10)
-    demo.launch(server_name="127.0.0.1", server_port=3300)
+        show_case = gr.Examples(
+            examples=[
+                ["assets/examples/model2.png", "assets/examples/garment2.png", "assets/examples/result2.png"],
+                ["assets/examples/model3.png", "assets/examples/garment3.png", "assets/examples/result3.png"],
+                ["assets/examples/model1.png", "assets/examples/garment1.png", "assets/examples/result1.png"],
+            ],
+            inputs=[imgs, garm_img, image_out],
+            label=None
+        )
 
+Tryon.queue(api_open=False).launch(show_api=False)