Update app.py

app.py

@@ -1,609 +1,77 @@
-import gradio as gr
 import insightface
-from insightface.app import FaceAnalysis
-import cv2
 import numpy as np
-import logging
-from PIL import Image
-
-assert insightface.__version__ >= '0.7'
-
-# Set up logging
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-def prepare_app():
-    app = FaceAnalysis(name='buffalo_l')
-    app.prepare(ctx_id=0, det_size=(384, 384))
-    swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download=True, download_zip=True)
-    return app, swapper
-
-def sort_faces(faces):
-    return sorted(faces, key=lambda x: x.bbox[0])
-
-def get_face(faces, face_id):
-    if len(faces) < face_id or face_id < 1:
-        raise gr.Error(f"Only {len(faces)} faces found. You asked for face {face_id}.")
-    return faces[face_id - 1]
-
-def align_face(image, face, target_shape):
-    src_pts = np.array(face.kps, dtype=np.float32)[:5]
-    h, w = target_shape[:2]
-    dst_pts = np.array([
-        [w * 0.3, h * 0.3], [w * 0.7, h * 0.3], [w * 0.5, h * 0.5],
-        [w * 0.35, h * 0.7], [w * 0.65, h * 0.7]
-    ], dtype=np.float32)
-    M, _ = cv2.estimateAffinePartial2D(src_pts, dst_pts)
-    if M is None:
-        raise gr.Error("Face alignment failed.")
-    return cv2.warpAffine(image, M, (w, h))
-
-def create_feathered_mask(shape, hull, feather=3):
-    mask = np.zeros(shape, dtype=np.uint8)
-    cv2.fillConvexPoly(mask, hull, (255, 255, 255))
-    return cv2.GaussianBlur(mask, (feather * 2 + 1, feather * 2 + 1), 0)
-
-def skin_tone_match(source, target, face_region):
-    source_lab = cv2.cvtColor(source, cv2.COLOR_BGR2LAB)
-    target_lab = cv2.cvtColor(target, cv2.COLOR_BGR2LAB)
-    mask = face_region.astype(np.uint8)
-    mean_source = cv2.mean(source_lab, mask=mask)[:3]
-    mean_target = cv2.mean(target_lab, mask=mask)[:3]
-    diff = np.array(mean_target) - np.array(mean_source)
-    source_lab = source_lab.astype(np.float32)
-    for i in range(3):
-        source_lab[:, :, i] = np.clip(source_lab[:, :, i] + diff[i], 0, 255)
-    return cv2.cvtColor(source_lab.astype(np.uint8), cv2.COLOR_LAB2BGR)
-
-def enhance_face(image):
-    lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)
-    l, a, b = cv2.split(lab)
-    l = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8)).apply(l)
-    enhanced = cv2.merge((l, a, b))
-    sharpen = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
-    return cv2.filter2D(cv2.cvtColor(enhanced, cv2.COLOR_LAB2BGR), -1, sharpen)
-
-app, swapper = prepare_app()
-
-def swap_faces(sourceImage, sourceFaceIndex, destinationImage, destinationFaceIndex):
-    if sourceImage is None or destinationImage is None:
-        raise gr.Error("Both source and destination images are required.")
-
-    source = cv2.cvtColor(np.array(sourceImage), cv2.COLOR_RGB2BGR)
-    destination = cv2.cvtColor(np.array(destinationImage), cv2.COLOR_RGB2BGR)
-
-    for image in (source, destination):
-        h, w = image.shape[:2]
-        if h < 128 or w < 128:
-            raise gr.Error("Images must be at least 128px in size.")
-        if max(h, w) > 512:
-            scale = 512 / max(h, w)
-            image = cv2.resize(image, (int(w * scale), int(h * scale)))
-
-    source_faces = sort_faces(app.get(source))
-    dest_faces = sort_faces(app.get(destination))
-
-    source_face = get_face(source_faces, sourceFaceIndex)
-    dest_face = get_face(dest_faces, destinationFaceIndex)
+import cv2
+import gradio as gr
+from insightface.app import FaceAnalysis
+import onnxruntime
+import os
 
-    source_aligned = align_face(source, source_face, destination.shape)
+app = FaceAnalysis(name='buffalo_l', providers=['CPUExecutionProvider'])
+app.prepare(ctx_id=0, det_size=(640, 640))
 
-    swapped = swapper.get(destination.copy(), dest_face, source_face, paste_back=False)
-    if swapped is None or np.any(np.isnan(swapped)):
-        swapped = swapper.get(destination.copy(), dest_face, source_face, paste_back=True)
-        if swapped is None:
-            raise gr.Error("Face swap failed.")
+inswapper_path = "checkpoints/inswapper_128.onnx"
+if not os.path.exists(inswapper_path):
+    raise FileNotFoundError(f"Model not found at {inswapper_path}")
+swapper = insightface.model_zoo.get_model(inswapper_path, providers=['CPUExecutionProvider'])
 
-    pts = np.array(dest_face.kps).astype(np.int32)
-    hull = cv2.convexHull(pts)
-    mask = create_feathered_mask(swapped.shape, hull)
+def preprocess_image(img):
+    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    img_eq = cv2.equalizeHist(img_gray)
+    img_rgb = cv2.cvtColor(img_eq, cv2.COLOR_GRAY2RGB)
+    return img_rgb
 
-    face_region = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY) > 0
-    swapped = skin_tone_match(swapped, destination, face_region)
-    swapped = enhance_face(swapped)
+def sharpen_image(img):
+    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
+    sharpened = cv2.filter2D(img, -1, kernel)
+    return np.clip(sharpened, 0, 255).astype(np.uint8)
 
-    center = tuple(np.mean(hull[:, 0, :], axis=0).astype(np.int32))
+def swap_faces(src_img, dst_img, blur_strength=3, sharpen=False):
     try:
-        blended = cv2.seamlessClone(swapped, destination, mask, center, cv2.NORMAL_CLONE)
-    except:
-        blended = swapper.get(destination.copy(), dest_face, source_face, paste_back=True)
-        if blended is None:
-            raise gr.Error("Blending failed.")
-    return cv2.cvtColor(blended, cv2.COLOR_BGR2RGB)
-
-# Updated CSS with further shrunk heading and darker tagline
-custom_css = """
-/* Import futuristic fonts */
-@import url('https://fonts.googleapis.com/css2?family=Fira+Code:wght@400;500;600&family=Neuropol:wght@400;700&display=swap');
-
-/* Global styles */
-body, .gradio-container {
-    background: linear-gradient(135deg, #0A0A1F 0%, #1C2526 100%); /* Dark AI gradient */
-    color: #E0E7FF !important;
-    font-family: 'Fira Code', monospace !important;
-    overflow-x: hidden;
-    position: relative;
-    margin: 0;
-}
-
-/* AI-themed circuit background with animated nodes */
-body::before {
-    content: '';
-    position: fixed;
-    top: 0;
-    left: 0;
-    width: 100%;
-    height: 100%;
-    background: repeating-linear-gradient(
-        45deg,
-        rgba(0, 209, 255, 0.05),
-        rgba(0, 209, 255, 0.05) 2px,
-        transparent 2px,
-        transparent 50px
-    );
-    opacity: 0.3;
-    pointer-events: none;
-    animation: circuitFlow 20s linear infinite;
-}
-
-body::after {
-    content: '';
-    position: fixed;
-    top: 0;
-    left: 0;
-    width: 100%;
-    height: 100%;
-    background: radial-gradient(
-        circle at 20% 30%,
-        rgba(0, 209, 255, 0.2) 0%,
-        transparent 10%
-    ),
-    radial-gradient(
-        circle at 80% 70%,
-        rgba(161, 0, 255, 0.2) 0%,
-        transparent 10%
-    );
-    opacity: 0.5;
-    animation: nodePulse 5s ease-in-out infinite;
-}
-
-@keyframes circuitFlow {
-    0% { background-position: 0 0; }
-    100% { background-position: 50px 50px; }
-}
-
-@keyframes nodePulse {
-    0% { opacity: 0.5; transform: scale(1); }
-    50% { opacity: 0.8; transform: scale(1.1); }
-    100% { opacity: 0.5; transform: scale(1); }
-}
-
-/* Header */
-.header {
-    text-align: center;
-    margin: 60px 0 40px;
-    position: relative;
-    z-index: 10;
-}
-
-h1 {
-    font-size: 2.5rem; /* Further reduced from 3rem */
-    font-family: 'Neuropol', sans-serif;
-    background: linear-gradient(90deg, #00D1FF, #A100FF); /* AI-themed gradient */
-    -webkit-background-clip: text;
-    -webkit-text-fill-color: transparent;
-    margin: 10px 0 5px; /* Reduced margin to minimize vertical space */
-    letter-spacing: 4px;
-    text-transform: uppercase;
-    opacity: 1 !important;
-    animation: enhancedGlowPulse 3s ease-in-out infinite;
-}
-
-@keyframes enhancedGlowPulse {
-    0% {
-        text-shadow: 0 0 8px rgba(0, 209, 255, 0.5), 0 0 8px rgba(161, 0, 255, 0.5);
-        transform: scale(1);
-    }
-    50% {
-        text-shadow: 0 0 20px rgba(0, 209, 255, 0.9), 0 0 20px rgba(161, 0, 255, 0.9), 0 0 30px rgba(0, 209, 255, 0.7);
-        transform: scale(1.02); /* Further reduced from 1.03 */
-    }
-    100% {
-        text-shadow: 0 0 8px rgba(0, 209, 255, 0.5), 0 0 8px rgba(161, 0, 255, 0.5);
-        transform: scale(1);
-    }
-}
-
-/* Tagline - Darkened for better contrast */
-.tagline {
-    font-size: 1.2rem;
-    color: #B0B8D1 !important; /* Light grayish-blue, darker than #ffffff */
-    text-shadow: 0 0 4px rgba(176, 184, 209, 0.3); /* Adjusted shadow to match new color */
-    font-family: 'Fira Code', monospace;
-    font-weight: 400;
-    opacity: 1 !important;
-    margin-top: 20px; /* Spacing from header */
-}
-
-/* Main container - Circuit texture and glowing edges */
-.container {
-    background: rgba(10, 10, 31, 0.9);
-    border: 3px solid transparent;
-    border-image: linear-gradient(45deg, #00D1FF, #A100FF) 1;
-    border-radius: 20px;
-    padding: 40px;
-    margin: 30px auto;
-    max-width: 1100px;
-    box-shadow: 0 0 30px rgba(0, 209, 255, 0.3), 0 0 30px rgba(161, 0, 255, 0.3);
-    position: relative;
-    transform: translateY(0);
-    transition: transform 0.4s ease, box-shadow 0.4s ease;
-    background-image: linear-gradient(
-        rgba(0, 209, 255, 0.05),
-        rgba(0, 209, 255, 0.05)
-    ),
-    repeating-linear-gradient(
-        45deg,
-        rgba(161, 0, 255, 0.1),
-        rgba(161, 0, 255, 0.1) 2px,
-        transparent 2px,
-        transparent 20px
-    );
-}
-
-.container:hover {
-    transform: translateY(-5px);
-    box-shadow: 0 0 40px rgba(0, 209, 255, 0.5), 0 0 40px rgba(161, 0, 255, 0.5);
-}
-
-/* Responsive adjustments */
-@media (max-width: 768px) {
-    .container {
-        margin: 15px;
-        padding: 20px;
-    }
-    h1 {
-        font-size: 1.5rem; /* Further reduced from 2rem */
-    }
-    .tagline {
-        font-size: 1rem;
-        margin-top: 15px;
-    }
-}
-
-/* Image inputs - Holographic effect */
-.gr-image img {
-    border: 3px solid transparent;
-    border-image: linear-gradient(45deg, #00D1FF, #A100FF) 1;
-    border-radius: 15px;
-    box-shadow: 0 0 15px rgba(0, 209, 255, 0.3);
-    transition: all 0.4s ease;
-    max-width: 100%;
-    height: auto;
-}
-
-.gr-image img:hover {
-    box-shadow: 0 0 25px rgba(0, 209, 255, 0.5);
-    transform: scale(1.05);
-}
-
-/* Output image block - Distinct styling */
-.output-image-block {
-    background: rgba(20, 20, 40, 0.95);
-    border: 3px solid transparent;
-    border-image: linear-gradient(45deg, #00D1FF, #A100FF) 1;
-    border-radius: 15px;
-    padding: 20px;
-    margin: 20px 0;
-    box-shadow: 0 0 20px rgba(0, 209, 255, 0.3), 0 0 20px rgba(161, 0, 255, 0.3);
-}
-
-/* Labels - Fixed for clarity */
-label, .gr-number label, .gr-image label, .gr-textbox label {
-    color: #00D1FF !important; /* Neon blue for AI theme */
-    background: transparent !important;
-    box-shadow: none !important;
-    opacity: 1 !important;
-    text-shadow: 0 0 3px rgba(0, 0, 0, 0.5); /* Dark shadow for contrast on white */
-    font-family: 'Neuropol', sans-serif;
-    font-weight: 400;
-    font-size: 1.3rem;
-    margin-bottom: 12px;
-}
-
-/* Fix placeholder text ("Drop IMAGE Here") */
-.gr-image .prose,
-.gr-image input::placeholder,
-.gr-image input::-webkit-input-placeholder,
-.gr-image input::-moz-placeholder,
-.gr-image input:-ms-input-placeholder,
-.gr-image input:-moz-placeholder {
-    color: #00D1FF !important; /* Neon blue for visibility */
-    opacity: 1 !important;
-    text-shadow: 0 0 3px rgba(0, 0, 0, 0.5); /* Dark shadow for contrast */
-    font-family: 'Fira Code', monospace;
-    font-size: 1rem;
-}
-
-/* Number inputs */
-.gr-number {
-    background: transparent !important;
-    border: 2px solid transparent;
-    border-image: linear-gradient(45deg, #00D1FF, #A100FF) 1;
-    border-radius: 10px;
-    padding: 15px;
-    box-shadow: none !important;
-    opacity: 1 !important;
-    transition: border-image 0.4s ease;
-}
-
-.gr-number:hover {
-    border-image: linear-gradient(45deg, #A100FF, #00D1FF) 1;
-}
-
-.gr-number input {
-    background: #1A1A3B;
-    color: #E0E7FF !important;
-    border: 1px solid #00D1FF;
-    border-radius: 8px;
-    padding: 10px;
-    font-family: 'Fira Code', monospace;
-    font-size: 1rem;
-    text-shadow: none;
-    box-shadow: none;
-    opacity: 1 !important;
-    transition: border-color 0.4s ease;
-}
-
-.gr-number input:focus {
-    border-color: #A100FF;
-    outline: none;
-}
-
-.gr-number .prose {
-    color: #ffffff !important; /* White for clarity */
-    background: transparent !important;
-    box-shadow: none !important;
-    opacity: 1 !important;
-    text-shadow: 0 0 2px rgba(255, 255, 255, 0.2);
-    font-size: 0.9rem;
-    font-family: 'Fira Code', monospace;
-}
-
-/* Button - AI-themed with data stream effect */
-.neon-button {
-    background: linear-gradient(45deg, #00D1FF, #A100FF);
-    color: #ffffff !important; /* White text for clarity */
-    border: none;
-    border-radius: 12px;
-    padding: 15px 35px;
-    font-size: 1.2rem;
-    font-family: 'Neuropol', sans-serif;
-    font-weight: 400;
-    text-transform: uppercase;
-    box-shadow: 0 0 20px rgba(0, 209, 255, 0.5), 0 0 20px rgba(161, 0, 255, 0.5);
-    transition: all 0.4s ease;
-    letter-spacing: 3px;
-    margin: 25px 0;
-    position: relative;
-    overflow: hidden;
-    opacity: 1 !important;
-    text-shadow: 0 0 3px rgba(255, 255, 255, 0.3);
-    animation: buttonGlow 2s ease-in-out infinite;
-}
-
-.neon-button::before {
-    content: '';
-    position: absolute;
-    top: 0;
-    left: -100%;
-    width: 50%;
-    height: 100%;
-    background: linear-gradient(
-        90deg,
-        transparent,
-        rgba(255, 255, 255, 0.4),
-        transparent
-    );
-    animation: dataStream 3s linear infinite;
-}
-
-.neon-button::after {
-    content: '';
-    position: absolute;
-    top: 0;
-    left: -100%;
-    width: 100%;
-    height: 100%;
-    background: rgba(255, 255, 255, 0.3);
-    transition: left 0.4s ease;
-}
-
-.neon-button:hover::after {
-    left: 100%;
-}
-
-.neon-button:hover {
-    box-shadow: 0 0 30px rgba(0, 209, 255, 0.7), 0 0 30px rgba(161, 0, 255, 0.7);
-    transform: translateY(-3px);
-}
-
-@keyframes buttonGlow {
-    0% { box-shadow: 0 0 20px rgba(0, 209, 255, 0.5), 0 0 20px rgba(161, 0, 255, 0.5); }
-    50% { box-shadow: 0 0 30px rgba(0, 209, 255, 0.7), 0 0 30px rgba(161, 0, 255, 0.7); }
-    100% { box-shadow: 0 0 20px rgba(0, 209, 255, 0.5), 0 0 20px rgba(161, 0, 255, 0.5); }
-}
-
-@keyframes dataStream {
-    0% { left: -100%; }
-    100% { left: 100%; }
-}
-
-/* Spinner */
-.spinner {
-    color: #ffffff !important; /* White for clarity */
-    text-shadow: 0 0 3px rgba(255, 255, 255, 0.3);
-    font-family: 'Fira Code', monospace;
-    font-size: 1rem;
-    margin: 20px 0;
-    opacity: 1 !important;
-}
-
-.spinner::before {
-    content: '🤖 ';
-    vertical-align: middle;
-}
-
-/* Error messages */
-.gr-textbox {
-    background: #1A1A3B;
-    color: #FF6B6B !important; /* Bright red for visibility */
-    border: 2px solid #FF6B6B;
-    border-radius: 10px;
-    box-shadow: 0 0 10px rgba(255, 107, 107, 0.4);
-    font-family: 'Fira Code', monospace;
-    padding: 12px;
-    font-size: 0.95rem;
-    opacity: 1 !important;
-    text-shadow: none;
-}
-
-/* Placeholder text in error textbox */
-.gr-textbox::placeholder {
-    color: #E0E7FF !important;
-    opacity: 1 !important;
-    text-shadow: none;
-}
-
-/* Footer - Refactored for clarity with AI accents */
-.footer {
-    color: #FFFFFF !important;
-    font-size: 1.1rem !important;
-    font-family: 'Fira Code', monospace !important;
-    background: rgba(20, 20, 40, 0.95);
-    border: 2px solid transparent;
-    border-image: linear-gradient(45deg, #00D1FF, #A100FF) 1;
-    border-radius: 20px;
-    padding: 25px;
-    margin: 50px 0 30px;
-    text-align: center;
-    line-height: 1.75;
-    text-shadow: 0 0 6px rgba(255, 255, 255, 0.4);
-    box-shadow: 0 0 25px rgba(0, 209, 255, 0.4), 0 0 25px rgba(161, 0, 255, 0.4);
-    opacity: 1 !important;
-}
-
-.footer a {
-    color: #A100FF !important;
-    font-weight: bold;
-    text-decoration: underline;
-    text-shadow: 0 0 4px rgba(161, 0, 255, 0.6);
-    opacity: 1 !important;
-}
-
-.footer a:hover {
-    color: #00D1FF !important;
-    text-shadow: 0 0 6px rgba(0, 209, 255, 0.7);
-}
-
-/* Light mode adjustments for Hugging Face Spaces */
-@media (prefers-color-scheme: light) {
-    body, .gradio-container {
-        background: linear-gradient(135deg, #E0E7FF 0%, #C3D7E8 100%); /* Light gradient */
-    }
-    body::before {
-        background: repeating-linear-gradient(
-            45deg,
-            rgba(0, 209, 255, 0.15),
-            rgba(0, 209, 255, 0.15) 2px,
-            transparent 2px,
-            transparent 50px
-        );
-    }
-    body::after {
-        background: radial-gradient(
-            circle at 20% 30%,
-            rgba(0, 209, 255, 0.3) 0%,
-            transparent 10%
-        ),
-        radial-gradient(
-            circle at 80% 70%,
-            rgba(161, 0, 255, 0.3) 0%,
-            transparent 10%
-        );
-    }
-    .container {
-        background: rgba(255, 255, 255, 0.9);
-        box-shadow: 0 0 30px rgba(0, 209, 255, 0.2), 0 0 30px rgba(161, 0, 255, 0.2);
-    }
-    .output-image-block {
-        background: rgba(240, 240, 255, 0.95);
-        box-shadow: 0 0 20px rgba(0, 209, 255, 0.2), 0 0 20px rgba(161, 0, 255, 0.2);
-    }
-    .footer {
-        background: rgba(240, 240, 255, 0.95);
-        box-shadow: 0 0 25px rgba(0, 209, 255, 0.3), 0 0 25px rgba(161, 0, 255, 0.3);
-    }
-    .gr-number input {
-        background: #E0E7FF;
-        color: #1A1A3B !important;
-    }
-    .gr-textbox {
-        background: #E0E7FF;
-        color: #FF6B6B !important;
-    }
-    /* Ensure labels remain legible in light mode */
-    label, .gr-number label, .gr-image label, .gr-textbox label {
-        color: #00D1FF !important;
-        text-shadow: 0 0 3px rgba(0, 0, 0, 0.5); /* Dark shadow for contrast */
-    }
-    .gr-image .prose,
-    .gr-image input::placeholder,
-    .gr-image input::-webkit-input-placeholder,
-    .gr-image input::-moz-placeholder,
-    .gr-image input:-ms-input-placeholder,
-    .gr-image input:-moz-placeholder {
-        color: #00D1FF !important;
-        text-shadow: 0 0 3px rgba(0, 0, 0, 0.5);
-    }
-    /* Darken tagline in light mode */
-    .tagline {
-        color: #6B7280 !important; /* Darker gray for light mode */
-        text-shadow: 0 0 4px rgba(107, 114, 128, 0.3); /* Adjusted shadow */
-    }
-}
-"""
-
-with gr.Blocks(css=custom_css) as demo:
-    with gr.Column(elem_classes="container"):
-        gr.HTML("""
-        <div class='header'>
-            <h1>InsightWhispersAI Face Swap</h1>
-            <p class='tagline'>Dive into the Future with AI-Driven Face Swaps</p>
-        </div>
-        """)
-        with gr.Row():
-            with gr.Column():
-                source_input = gr.Image(label="Source Image (Face to Swap)", type="pil", height=300)
-                source_face_idx = gr.Number(precision=0, value=1, label='Source Face Position', info='Select face from left, starting at 1')
-            with gr.Column():
-                target_input = gr.Image(label="Target Image (Body to Swap Onto)", type="pil", height=300)
-                target_face_idx = gr.Number(precision=0, value=1, label='Target Face Position', info='Select face to replace from left, starting at 1')
-        run_btn = gr.Button("🚀 Launch Face Swap", elem_classes="neon-button")
-        spinner = gr.Markdown("<span class='spinner'>🌌 Processing... (10-30 seconds)</span>", visible=False)
-        with gr.Row(elem_classes="output-image-block"):
-            result_image = gr.Image(label="Swapped Result", height=400)
-        error_output = gr.Textbox(label="Status / Error Messages", interactive=False, placeholder="Status will appear here...")
-        gr.HTML("""
-        <div class='footer'>
-            <p>Powered by <a href='https://insightwhispersai.com'>InsightWhispersAI</a> | Built with xAI Technology 🤖</p>
-            <p><strong>Pro Tip:</strong> Use high-resolution, well-lit images for optimal results. Processing takes 10-30 seconds.</p>
-        </div>
-        """)
-        run_btn.click(
-            fn=lambda *args: (gr.update(visible=True), *swap_faces(*args)),
-            inputs=[source_input, source_face_idx, target_input, target_face_idx],
-            outputs=[spinner, result_image, error_output, spinner]
-        )
-
-demo.launch()
+        src = preprocess_image(src_img)
+        dst = preprocess_image(dst_img)
+
+        src_faces = app.get(src)
+        dst_faces = app.get(dst)
+
+        if not src_faces or not dst_faces:
+            raise ValueError("No faces detected in one of the images.")
+
+        src_face = src_faces[0]
+        dst_face = dst_faces[0]
+
+        swapped_img = swapper.get(dst, dst_face, src_face, paste_back=True)
+
+        if blur_strength > 0:
+            swapped_img = cv2.GaussianBlur(swapped_img, (blur_strength, blur_strength), 0)
+
+        if sharpen:
+            swapped_img = sharpen_image(swapped_img)
+
+        result = cv2.cvtColor(swapped_img, cv2.COLOR_RGB2BGR)
+        return result
+    except Exception as e:
+        print(f"Error: {str(e)}")
+        return np.zeros((640, 640, 3), dtype=np.uint8)
+
+title = "🧠 Futuristic Face Swapper with inswapper_128"
+description = (
+    "Upload a source face and a target image. The AI swaps the face using inswapper_128.onnx "
+    "for clean, smooth results. Adjust blur strength or enable sharpening for enhanced output."
+)
+
+demo = gr.Interface(
+    fn=swap_faces,
+    inputs=[
+        gr.Image(label="Source Face", type="numpy"),
+        gr.Image(label="Target Image", type="numpy"),
+        gr.Slider(label="Blur Strength", minimum=0, maximum=5, step=1, value=3),
+        gr.Checkbox(label="Enable Sharpening", value=False)
+    ],
+    outputs=gr.Image(label="Face Swapped Output"),
+    title=title,
+    description=description,
+    flagging_mode="never"
+)
+
+if __name__ == "__main__":
+    demo.queue().launch()