zuruoke/watermark-removal
Watermark Removal
This software is a watermark removal system that uses machine learning and image inpainting to delete unwanted text or logos from images. It reconstructs missing pixels to match the original background, ensuring visual consistency through pretrained models.
The project includes a masking utility to isolate specific regions for content replacement using binary masks, bounding boxes, or brush strokes. It also features a batch processor that applies these cleaning tasks to large sets of images via a predefined file list.
The system handles image preparation by normalizing dimensions and aspect ratios into tensors to align images with their corresponding masks for neural network processing.
Features
- Image Inpainting - Uses generative neural networks to fill in missing image regions and restore the background after watermark removal.
- Binary Mask Generators - Generates binary masks to define the exact pixel-level regions where watermarks should be replaced.
- Generative Masking - Creates alpha channels and masks to isolate specific areas for AI-driven inpainting.
- Inference Optimizations - Utilizes a frozen set of learned weights to perform watermark removal without needing per-image training.
- Image Watermark Removal - Provides software to identify and delete watermarks from images while preserving visual consistency.
- AI-Driven Removers - Employs generative AI and deep learning to erase watermarks and reconstruct the background pixels.
- Batch Watermark Removal - Automates the removal of watermarks across multiple images in a sequence using pretrained models.
- Input Tensor Alignment - Normalizes image dimensions and aligns them with masks to create a single input tensor for inpainting.
- Tensor Dimension Normalizers - Standardizes image dimensions and aspect ratios into consistent tensor formats for neural network processing.
- Batch Image Processors - Provides a system to automate the removal of designated areas across multiple images.
- Batch Image Processing - Applies automated cleaning and editing tasks to large sets of images via predefined file lists.
- Image Processing Pipelines - Implements a sequential workflow for preprocessing and reconstructing multiple image files.
