Update app.py

app.py

@@ -1,116 +1,66 @@
-import os
 import requests
-import json
-import time
-import cv2
-import base64
-import random
-import numpy as np
 import gradio as gr
 
-MAX_SEED = 999999
+# Set your Pixelcut API key directly
+API_KEY = "sk_7c19e4f2ad434a3ebc70fdd85ade5309"
 
-# ✅ Hardcoded Pixelcut API key
-pixelcut_api_key = "sk_7c19e4f2ad434a3ebc70fdd85ade5309"
-
-
-# Convert images to PNG format
-def convert_to_png(image):
-    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-
-
-# Encode images to base64 PNG format
-def encode_image(image):
-    image = convert_to_png(image)
-    _, buffer = cv2.imencode('.png', image)
-    return base64.b64encode(buffer).decode('utf-8')
-
-
-# Main try-on function using Pixelcut API
-def tryon(person_img, garment_img, seed, randomize_seed):
-    start_time = time.time()
-
-    # 🛑 Check if images are provided
-    if person_img is None or garment_img is None:
-        return None, None, "Empty image"
-
-    # 🎲 Handle seed randomization
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-
-    # 🔥 Convert images to base64 PNG
-    encoded_person_img = encode_image(person_img)
-    encoded_garment_img = encode_image(garment_img)
+# Function to remove background from a local image file
+def remove_bg(image_path):
+    try:
+        with open(image_path, "rb") as image_file:
+            response = requests.post(
+                "https://api.developer.pixelcut.ai/v1/remove-background",
+                headers={
+                    "Accept": "application/json",
+                    "X-API-KEY": API_KEY,
+                },
+                files={"image": image_file},
+                data={"format": "png"},
+            )
 
-    # 🌟 Setup Pixelcut API endpoint and headers
-    url = "https://api.developer.pixelcut.ai/v1/remove-background"
-    headers = {
-        'Content-Type': 'application/json',
-        'Accept': 'application/json',
-        'X-API-KEY': pixelcut_api_key
-    }
+        # Handle API response
+        if response.status_code == 200:
+            result = response.json()
+            return result["output_url"]  # Return the output image URL from API
+        else:
+            return f"Error: {response.status_code} - {response.json()['error']}"
 
-    # 📩 Setup request payload (matches the curl command structure)
-    data = {
-    "image": encoded_person_img,
-    "format": "png"
-}
+    except Exception as e:
+        return f"Exception: {e}"
 
 
-    result_img = None
-    max_retries = 5
-    retry_delay = 5
+# Define the Tryonn function without CSS
+def tryonn(person_image, garment_image):
+    # Process the images using the Pixelcut API
+    person_result = remove_bg(person_image)
+    garment_result = remove_bg(garment_image)
 
-    try:
-        session = requests.Session()
-
-        # 🔁 Retry loop for "Too many users" error
-        for attempt in range(max_retries):
-            response = session.post(url, headers=headers, json=data, timeout=60)
-            print("Response code:", response.status_code)
-
-            # ✅ Success — process the result
-            if response.status_code == 200:
-                result_url = response.json().get('result_url', '')
-                print("✅ Success:", result_url)
-
-                # If Pixelcut returns a result URL, fetch the final image
-                if result_url:
-                    result_img_data = requests.get(result_url).content
-                    result_np = np.frombuffer(result_img_data, np.uint8)
-                    result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
-                    info = "Success"
-                    break
-
-            else:
-                # 🔥 If API returns "Too many users" error, retry with delay
-                print("Full response:", response.text)
-                if "Too many users" in response.text:
-                    print(f"Attempt {attempt + 1}/{max_retries}: API busy. Retrying in {retry_delay} seconds...")
-                    time.sleep(retry_delay)
-                else:
-                    info = f"Error: {response.status_code} - {response.text}"
-                    break
+    # If both images are processed successfully, combine them (mock-up display)
+    if "Error" not in person_result and "Error" not in garment_result:
+        return person_result, garment_result, "✅ Success!"
+    else:
+        return person_result, garment_result, "❌ Failed, check errors."
 
-        else:
-            # ❌ If all retries fail
-            info = "API still overloaded — please try again later."
+# Gradio interface setup (CSS removed)
+with gr.Blocks() as Tryon:
+    gr.Markdown("## Upload a Person Image and Garment Image")
+    with gr.Row():
+        person_input = gr.Image(type="filepath", label="Person Image")
+        garment_input = gr.Image(type="filepath", label="Garment Image")
+    output_person = gr.Image(label="Processed Person Image")
+    output_garment = gr.Image(label="Processed Garment Image")
+    status = gr.Textbox(label="Status")
 
-    # 🛑 Handle timeouts specifically
-    except requests.exceptions.ReadTimeout:
-        print("Timeout!")
-        info = "Too many users, please try again later"
-        raise gr.Error("Too many users, please try again later")
+    submit_button = gr.Button("Run Try-On")
 
-    # ❗ Handle any other unexpected errors
-    except Exception as err:
-        print(f"❌ Other error: {err}")
-        info = "Error, please contact the admin"
+    submit_button.click(
+        fn=tryonn,
+        inputs=[person_input, garment_input],
+        outputs=[output_person, output_garment, status],
+    )
 
-    end_time = time.time()
-    print(f"⏳ Time used: {end_time - start_time:.2f} seconds")
+Tryon.launch()
 
-    return result_img, seed, info
 
 example_path = os.path.join(os.path.dirname(__file__), 'assets')