Update app.py

app.py

@@ -3,118 +3,42 @@ import cv2
 import gradio as gr
 import numpy as np
 import random
-import base64
-import requests
-import json
-import time
 
 MAX_SEED = 999999
 example_path = os.path.join(os.path.dirname(__file__), 'assets')
+
+# Load example images
 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]
 
-# API details
-base_url = "https://huggingface.co/spaces/zaghamrasool/Z-Virtual-Try-On"
-upload_image_url = f"{base_url}/upload_image"
-create_save_task_url = f"{base_url}/create_save_task"
-execute_task_url = f"{base_url}/execute_task"
-query_task_url = f"{base_url}/query_task"
-
-def tryon(person_img, garment_img, seed, randomize_seed):
-    post_start_time = time.time()
+def mock_tryon(person_img, garment_img, seed, randomize_seed, progress=gr.Progress()):
+    progress(0, desc="Starting mock try-on...")
+    
     if person_img is None or garment_img is None:
-        gr.Warning("Empty image")
-        return None, None, "Empty image"
+        gr.Warning("Please upload both images!")
+        return None, None, "Error: Empty image"
+    
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
-    
-    # Encode images
-    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')
-
-    # Prepare data
-    data = {
-        "clothImage": encoded_garment_img,
-        "humanImage": encoded_person_img,
-        "seed": seed
-    }
-
-    uuid = None
-    try:
-        # First API call to create task
-        response = requests.post(create_save_task_url, data=json.dumps(data), timeout=50)
-        if response.status_code == 200:
-            result = response.json().get('result', {})
-            if result.get('status') == "success":
-                uuid = result.get('taskId')  # Use taskId for querying
-            else:
-                raise Exception("Failed to create task, no task ID received.")
-        else:
-            raise Exception(f"Failed to create task. Status Code: {response.status_code}")
-    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}")
+    progress(0.3, desc="Processing person image...")
+    # Convert to grayscale for demo (replace with actual try-on logic)
+    person_gray = cv2.cvtColor(person_img, cv2.COLOR_RGB2GRAY)
+    person_gray = cv2.cvtColor(person_gray, cv2.COLOR_GRAY2RGB)
 
-    # Retry loop to query task status
-    get_start_time = time.time()
-    time.sleep(5)
-    Max_Retry = 20
-    result_img = None
-    info = ""
-    err_log = ""
+    progress(0.6, desc="Adding garment...")
+    # Resize garment to fit person (demo only)
+    garment_resized = cv2.resize(garment_img, (person_img.shape[1], person_img.shape[0]))
 
-    if not uuid:
-        err_log = "No task ID received from backend."
-        info = "Failed to get task ID from backend"
-    else:
-        for i in range(Max_Retry):
-            try:
-                url = f"{query_task_url}?taskId={uuid}"
-                response = requests.get(url, timeout=20)
-                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 = "Status is Error"
-                        info = "Error"
-                        break
-                else:
-                    err_log = "URL error, please contact the admin"
-                    info = "URL error, please 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(5)
+    progress(0.8, desc="Blending images...")
+    # Simple alpha blending (replace with real try-on)
+    alpha = 0.7
+    result = cv2.addWeighted(person_gray, 1-alpha, garment_resized, alpha, 0)
 
-    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(info)
-
-    return result_img, seed, info
+    progress(1.0, desc="Done!")
+    return result, seed, "Mock try-on complete"
 
 def load_description(fp):
     with open(fp, 'r', encoding='utf-8') as f:
@@ -133,41 +57,42 @@ with gr.Blocks(css=css) as Tryon:
 
     with gr.Row():
         with gr.Column(elem_id="col-left"):
-            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 1.  Upload a person image ⬇️</div>")
-        with gr.Column(elem_id="col-mid"):
-            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 2. Upload a garment image ⬇️</div>")
-        with gr.Column(elem_id="col-right"):
-            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 3. Press “Run” to get try-on results</div>")
-
-    with gr.Row():
-        with gr.Column(elem_id="col-left"):
-            imgs = gr.Image(label="Person image", sources='upload', type="numpy")
+            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 1. Upload person ⬇️</div>")
+            imgs = gr.Image(label="Person", sources='upload', type="numpy")
             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")
+            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 2. Upload garment ⬇️</div>")
+            garm_img = gr.Image(label="Garment", sources='upload', type="numpy")
             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)
+            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 3. Click Run</div>")
+            image_out = gr.Image(label="Result")
             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")
-            test_button = gr.Button(value="Run", elem_id="button")
+                result_info = gr.Text(label="Status")
+            test_button = gr.Button("Run", elem_id="button")
 
-    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)
+    test_button.click(
+        fn=mock_tryon,
+        inputs=[imgs, garm_img, seed, randomize_seed],
+        outputs=[image_out, seed_used, result_info],
+        concurrency_limit=5
+    )
 
     with gr.Column(elem_id="col-showcase"):
-        gr.HTML("<div style='text-align: center; font-size: 20px;'>Virtual try-on examples in pairs of person and garment images</div>")
+        gr.HTML("<div style='text-align: center; font-size: 20px;'>Examples</div>")
         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]
+            examples=[
+                [human_list_path[0], garm_list_path[0]],  # First human + first garment
+                [human_list_path[1], garm_list_path[1]],  # Second pair
+            ],
+            inputs=[imgs, garm_img],
+            outputs=[image_out]
         )
 
-Tryon.queue(api_open=False).launch(show_api=False)
-Tryon.launch()
-print("Gradio app is running...")
-print("Please open the link in your browser to access the app.")
+Tryon.queue().launch()