Readme.MD

README.md

@@ -11,4 +11,117 @@ license: mit
 short_description: FaceForgeAI_ZeroGPU
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🎨 FaceForge AI – ZeroGPU Gradio Edition  
+[![Hugging Face Space](https://img.shields.io/badge/🤗%20Open%20in-Hugging%20Face%20Space-yellow)](https://huggingface.co/spaces/VcRlAgent/FaceForgeAI_ZeroGPU)
+
+**Author:** Vijay S. Chaudhari
+**Runtime:** Hugging Face Spaces (ZeroGPU) 🚀  
+ 
+---
+
+## 🧠 Overview  
+**FaceForge AI** transforms your uploaded photo into professional-quality images powered by open-source generative AI:  
+- 🪄 **Background Remover** – clean gradient background for profile photos  
+- 🛂 **Passport Photo** – compliant 600×600 white-background image  (Requires picture with frontal face)
+- 🎭 **Stylized AI Avatar** – realistic yet personalized stylization  
+
+This edition is optimized for **ZeroGPU Spaces** — efficient, on-demand GPU execution using CPU offload and attention slicing for lightweight inference.
+
+---
+
+## ⚙️ Key Features  
+✅ **Three Modes**
+- **Background Remover** – removes background and enhances clarity  
+- **Passport** – white background, standard size  
+- **Avatar** – realistic stylization via Stable Diffusion Img2Img  
+
+✅ **User Control for Avatar Generation**
+- Preset prompt styles + custom text input  
+- Adjustable `strength` & `guidance_scale` sliders  
+
+---
+
+## 🧩 Tech Stack  
+
+| Component | Purpose |
+|------------|----------|
+| **Python 3.10+** | Core runtime |
+| **Gradio 4.x** | Web UI framework |
+| **Stable Diffusion v1.5** | Img2Img stylization |
+| **GFPGAN 1.3.8** | Facial restoration |
+| **Real-ESRGAN 0.3.0** | Super-resolution |
+| **Rembg 2.x** | Background removal |
+| **Pillow / OpenCV / Torch** | Image processing + GPU acceleration |
+
+---
+
+## 🖥️ UI Preview  
+
+| Upload → Choose → Generate |  
+|-----------------------------|  
+| ![FaceForge AI UI Preview](assets/faceforge_ui_demo.png) |  
+
+> _Example UI layout with independent buttons for Background Remover, Passport, and Avatar generation._
+
+---
+
+## 🧰 Installation  
+
+### 1️⃣ Clone Repository
+```bash
+git clone https://github.com/agentofAI/FaceForgeAI.git
+cd FaceForgeAI_ZeroGPU
+
+### 2️⃣ Install Dependencies
+
+pip install -r requirements.txt
+
+### 3️⃣ Run Locally
+python app.py
+
+Open the local Gradio URL (typically http://127.0.0.1:7860) in your browser.
+
+---
+
+Avatar Prompt Presets
+Style Label	            Prompt
+🎬 Cinematic Portrait	highly detailed, digital portrait, professional lighting, cinematic style, artistic AI avatar
+🎨 Stylized Realism	    stylized yet realistic portrait, balanced lighting, subtle gradient background, sharp 
+                        focus on face
+🏢 Studio Professional	studio portrait, even lighting, neutral background, realistic skin, confident pose
+🤵 Natural Headshot	    realistic professional headshot, soft studio lighting, neutral background, crisp details, 
+                        natural skin tone
+
+---
+
+## 🧾 Model Credits
+| Model                     | Source / License                                                                                              |
+| ------------------------- | ------------------------------------------------------------------------------------------------------------- |
+| **Stable Diffusion v1.5** | [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) (CompVis / Runway ML) |
+| **GFPGAN v1.3**           | [TencentARC/GFPGAN](https://github.com/TencentARC/GFPGAN) (MIT License)                                       |
+| **Real-ESRGAN x2Plus**    | [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) (BSD License)                                   |
+| **Rembg**                 | [danielgatis/rembg](https://github.com/danielgatis/rembg)                                                     |
+| **Gradio**                | [gradio-app/gradio](https://github.com/gradio-app/gradio)                                                     |
+
+---
+
+## 🧠 Project Structure
+faceforge-ai/
+│
+├── app.py                # Main application
+├── requirements.txt      # Dependencies
+├── assets/               # Optional screenshots and samples
+└── README.md             # Documentation
+
+---
+
+## 📜 License
+
+This project is for educational and demonstration purposes.
+Each model used retains its original open-source license.
+
+---
+## 👨‍💻 Author
+
+Vijay S. Chaudhari
+🔗 LinkedIn Profile

app copy.py

@@ -1,226 +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
-from diffusers import StableDiffusionImg2ImgPipeline
-import io
-
-
-import torchvision
-print("Printing Torch and TorchVision versions:")
-print(torch.__version__)
-print(torchvision.__version__)
-
-# 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
-    )
-    
-    # Stable Diffusion Img2Img pipeline (public model)
-    sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
-        "runwayml/stable-diffusion-v1-5",
-        torch_dtype=torch.float16
-    ).to(device)
-
-    # Optimize for ZeroGPU memory
-    sd_pipe.enable_attention_slicing()
-    sd_pipe.enable_model_cpu_offload()
-
-    return face_enhancer, sd_pipe
-
-# Load models globally
-face_enhancer, sd_pipe = 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)
-    
-    # Resize for SD (512x512)
-    img_resized = img_enhanced.convert("RGB").resize((512, 512))
-
-    # Stylize with SD prompt
-    #prompt = "highly detailed, digital portrait, professional lighting, cinematic style, artistic AI avatar"
-    #prompt = "stylized yet realistic portrait, balanced lighting, subtle gradient background, sharp focus on face"
-    #prompt = "studio portrait, even lighting, neutral background, realistic skin, confident pose"
-    prompt = "realistic professional headshot, soft studio lighting, neutral background, crisp details, natural skin tone"
-    
-
-
-    with torch.autocast("cuda"):
-        result = sd_pipe(prompt=prompt, image=img_resized, strength=0.4, guidance_scale=5.0)
-
-    avatar = result.images[0]
-    
-    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()

app.py.bak

@@ -1,204 +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
-
-
-import torchvision
-print("Printing Torch and TorchVision versions:")
-print(torch.__version__)
-print(torchvision.__version__)
-
-# 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()