clean up

src/app.py.bkp

@@ -1,198 +0,0 @@
-# ==========================================
-# FaceForge AI – ZeroGPU Gradio Version
-# Author: Vijay S. Chaudhari | 2025
-# ==========================================
-
-import gradio as gr
-import spaces
-import torch
-import cv2
-import numpy as np
-from PIL import Image, ImageEnhance, ImageOps
-from rembg import remove
-import io
-
-# GPU libraries
-from gfpgan import GFPGANer
-from basicsr.archs.rrdbnet_arch import RRDBNet
-from realesrgan import RealESRGANer
-
-# ------------------------------------------
-# Model Loading (Outside GPU decorator)
-# ------------------------------------------
-
-def load_models():
-    """Load models once at startup"""
-    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-    
-    # RealESRGAN upsampler
-    model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
-    upsampler = RealESRGANer(
-        scale=2,
-        model_path='https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth',
-        model=model,
-        tile=400,
-        tile_pad=10,
-        pre_pad=0,
-        half=True,
-        device=device
-    )
-    
-    # GFPGAN enhancer
-    face_enhancer = GFPGANer(
-        model_path='https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth',
-        upscale=2,
-        arch='clean',
-        channel_multiplier=2,
-        bg_upsampler=upsampler,
-        device=device
-    )
-    
-    return face_enhancer
-
-# Load models globally
-face_enhancer = load_models()
-
-# ------------------------------------------
-# GPU-Accelerated Functions
-# ------------------------------------------
-
-@spaces.GPU
-def enhance_face(img: Image.Image) -> Image.Image:
-    """Enhance face using GFPGAN (GPU)"""
-    img_cv = cv2.cvtColor(np.array(img.convert('RGB')), cv2.COLOR_RGB2BGR)
-    
-    with torch.no_grad():
-        _, _, restored_img = face_enhancer.enhance(
-            img_cv,
-            has_aligned=False,
-            only_center_face=False,
-            paste_back=True,
-            weight=0.5
-        )
-    
-    restored_img = cv2.cvtColor(restored_img, cv2.COLOR_BGR2RGB)
-    return Image.fromarray(restored_img)
-
-# ------------------------------------------
-# Image Processing Functions
-# ------------------------------------------
-
-def enhance_image(img: Image.Image) -> Image.Image:
-    """Basic enhancement"""
-    img = ImageEnhance.Contrast(img).enhance(1.15)
-    img = ImageEnhance.Sharpness(img).enhance(1.1)
-    return img
-
-@spaces.GPU
-def create_headshot(img: Image.Image) -> Image.Image:
-    """Professional headshot with gradient background"""
-    # Enhance face
-    img_enhanced = enhance_face(img)
-    
-    # Remove background
-    img_no_bg = remove(img_enhanced)
-    
-    # Gradient background
-    bg = Image.new("RGB", img_no_bg.size, (200, 210, 230))
-    if img_no_bg.mode == 'RGBA':
-        bg.paste(img_no_bg, mask=img_no_bg.split()[3])
-    
-    return enhance_image(bg)
-
-@spaces.GPU
-def create_passport(img: Image.Image) -> Image.Image:
-    """Passport photo with white background"""
-    # Enhance face
-    img_enhanced = enhance_face(img)
-    
-    # Remove background
-    img_no_bg = remove(img_enhanced)
-    
-    # White background (600x600)
-    bg = Image.new("RGB", (600, 600), (255, 255, 255))
-    img_no_bg.thumbnail((550, 550), Image.Resampling.LANCZOS)
-    offset = ((600 - img_no_bg.width) // 2, (600 - img_no_bg.height) // 2)
-    
-    if img_no_bg.mode == 'RGBA':
-        bg.paste(img_no_bg, offset, mask=img_no_bg.split()[3])
-    
-    return bg
-
-@spaces.GPU
-def create_avatar(img: Image.Image) -> Image.Image:
-    """Stylized AI avatar"""
-    # Enhance face
-    img_enhanced = enhance_face(img)
-    
-    # Stylize
-    avatar = ImageOps.posterize(img_enhanced, bits=4)
-    avatar = ImageEnhance.Color(avatar).enhance(1.8)
-    avatar = ImageEnhance.Contrast(avatar).enhance(1.2)
-    
-    return avatar
-
-@spaces.GPU
-def process_all(img: Image.Image):
-    """Process all three types at once"""
-    headshot = create_headshot(img)
-    passport = create_passport(img)
-    avatar = create_avatar(img)
-    return headshot, passport, avatar
-
-# ------------------------------------------
-# Gradio Interface
-# ------------------------------------------
-
-with gr.Blocks(theme=gr.themes.Soft(), title="FaceForge AI") as demo:
-    gr.Markdown(
-        """
-        # 🎨 FaceForge AI
-        ### GPU-Accelerated Professional Headshot & Avatar Generator
-        Upload your photo and generate professional headshots, passport photos, and AI avatars instantly!
-        """
-    )
-    
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(type="pil", label="📷 Upload Your Photo")
-            process_btn = gr.Button("✨ Generate All Images", variant="primary", size="lg")
-        
-        with gr.Column():
-            gr.Markdown("### Results")
-    
-    with gr.Row():
-        output_headshot = gr.Image(label="💼 Professional Headshot", type="pil")
-        output_passport = gr.Image(label="🛂 Passport Photo", type="pil")
-        output_avatar = gr.Image(label="🎭 AI Avatar", type="pil")
-    
-    # Process button
-    process_btn.click(
-        fn=process_all,
-        inputs=input_image,
-        outputs=[output_headshot, output_passport, output_avatar]
-    )
-    
-    # Examples
-    gr.Examples(
-        examples=[],  # Add example image paths if available
-        inputs=input_image
-    )
-    
-    gr.Markdown(
-        """
-        ---
-        ### Features
-        - 💼 **Professional Headshots**: Perfect for LinkedIn and business profiles
-        - 🛂 **Passport Photos**: Standard 600x600px with white background
-        - 🎭 **AI Avatars**: Stylized versions for social media
-        - ⚡ **GPU-Accelerated**: Fast processing with GFPGAN enhancement
-        
-        © 2025 Vijay S. Chaudhari | Powered by ZeroGPU 🚀
-        """
-    )
-
-# Launch
-if __name__ == "__main__":
-    demo.queue(max_size=20)
-    demo.launch()