README.md

---
title: 4K Upscaler
emoji: 🐠
colorFrom: blue
colorTo: red
sdk: docker
pinned: false
license: apache-2.0
---



🎬 4K Upscaler
AI-Powered Image & Video Upscaling to Ultra HD Quality
Transform your images and videos to stunning 4K resolution using advanced neural upscaling techniques powered by PyTorch and GPU acceleration.
🚀 What It Does
This application uses sophisticated neural network interpolation and enhancement algorithms to upscale images and videos to 4K resolution (4x the original size) while maintaining and improving visual quality. Unlike simple resizing, it employs:

Progressive Neural Upscaling: Multi-stage bicubic interpolation with anti-aliasing
AI-Enhanced Sharpening: Custom convolution kernels for detail enhancement
Adaptive Contrast Optimization: Automatic brightness and contrast adjustment
GPU-Accelerated Processing: CUDA optimization for fast processing
Intelligent Smoothing: Noise reduction while preserving important details

✨ Features
🎨 Smart Image Processing

Upscale images from any resolution to 4K (3840x2160 or equivalent 4x scaling)
Advanced sharpening algorithms that enhance details without artifacts
Automatic contrast and brightness optimization
Support for PNG, JPG, JPEG, and GIF formats

🎬 Professional Video Enhancement

Frame-by-frame 4K upscaling for videos
Maintains original frame rate and aspect ratio
Batch processing for efficiency
Support for MP4, AVI, MOV, and MKV formats

⚡ Performance & Efficiency

GPU Acceleration: Automatic CUDA detection and optimization
CPU Fallback: Seamless fallback when GPU unavailable
Memory Management: Smart memory allocation and cleanup
Progressive Processing: Handles large files without memory overflow

🧹 Automatic Storage Management

Auto-Cleanup: Files automatically deleted after 1 hour
Background Scheduler: Cleanup runs every 10 minutes
Storage Statistics: Real-time monitoring of disk usage
Manual Controls: Force cleanup and cache clearing

📊 Real-Time Monitoring

Live processing logs with timestamps
GPU memory usage tracking
Processing progress indicators
System performance metrics

🛠️ Technical Specifications
AI Processing Pipeline

Input Normalization: Convert to floating-point tensors
Progressive Upscaling: 2x → 4x scaling stages
Neural Enhancement: Custom sharpening kernels
Quality Optimization: Adaptive contrast and smoothing
Output Conversion: High-quality image/video encoding

System Requirements

GPU: NVIDIA GPU with CUDA support (recommended)
Memory: 4GB+ RAM, 2GB+ GPU VRAM for large files
Storage: Automatic cleanup manages disk space
Formats: Images (PNG, JPG, GIF), Videos (MP4, AVI, MOV, MKV)

🎯 Use Cases

Content Creation: Enhance low-resolution footage for professional projects
Archive Restoration: Upscale old photos and videos to modern standards
Social Media: Create high-quality content from mobile captures
Gaming: Enhance screenshots and recordings
Research: Improve visual data quality for analysis
Personal: Transform family photos and memories to 4K

🚀 Quick Start

Upload: Drag and drop your image or video file
Process: AI automatically detects file type and starts 4K upscaling
Monitor: Watch real-time progress in the processing logs
Download: Get your enhanced 4K file when processing completes

The application automatically handles GPU detection, memory management, and file cleanup - no configuration needed!
📈 Performance

Images: Typical 1080p → 4K upscaling in 10-30 seconds (GPU)
Videos: Processing speed depends on length and GPU capability
Quality: Advanced algorithms preserve and enhance detail quality
Efficiency: Optimized memory usage prevents system overload

🔧 API Endpoints

POST /api/upload - Upload and process files
GET /api/processing-status - Check processing progress
GET /api/download/<filename> - Download processed files
GET /api/system - System and GPU information
POST /api/cleanup-now - Manual storage cleanup
GET /api/storage-stats - Detailed storage statistics

🧹 Storage Management
Files are automatically managed to prevent storage overflow:

Auto-deletion: Files removed after 1 hour
Regular cleanup: Runs every 10 minutes
Smart monitoring: Tracks storage usage and cleanup statistics
Manual controls: Force cleanup when needed

👨‍💻 Created By
Angel E. Pariente
This project combines cutting-edge neural network techniques with practical engineering to make professional-quality 4K upscaling accessible to everyone.
📄 License
Licensed under the Apache License 2.0 - see the license for details.
🌟 Technology Stack

Backend: Python, Flask, PyTorch
Computer Vision: OpenCV, PIL
GPU Computing: CUDA, cuDNN
Container: Docker
Scheduling: Background task automation