Automated Colour Correction

• Tech Stack: TensorFlow · Adobe 5k Dataset · DeepLearning · OpenCv · Resnet · React
• Project URL: Github Link
• Video URL: Youtube Video Link

Automated Colour Correction

Project Description

Professional photographers often spend countless hours manually editing photos to achieve the perfect color balance. This process is not only time-consuming but also prone to inconsistencies. The need for an automated solution that can deliver consistent, high-quality color corrections is paramount. Automated Colour Correction addresses this issue by leveraging advanced AI models to automate the color correction process, thereby saving photographers valuable time and effort.

Features

• AI-Powered Color Correction: Utilizes advanced neural networks to predict and apply optimal color corrections.
• Batch Processing: Efficiently processes large batches of photos.
• Manual Adjustments: Provides options for manual tweaks to ensure every photo meets the photographer's standards.
• Downloadable Results: Allows users to download the edited photos seamlessly.

Concepts and Technologies Used

• Machine Learning Models: ResNet, Artificial Neural Networks, Regression
• Frontend Development: React
• Image Processing: OpenCV
• Dataset: Adobe 5k