# Batch image watermark remover

> AI-ranked search results for `batch remove text and logo from image` on awesome-repositories.com — ordered by an LLM for relevance, best match first. 116 total matches; showing the top 10.

Explore on the web: https://awesome-repositories.com/q/batch-remove-text-and-logo-from-image

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## Results

- [sanster/lama-cleaner](https://awesome-repositories.com/repository/sanster-lama-cleaner.md) (23,235 ⭐) — Lama Cleaner is an AI-powered image editing application focused on inpainting, object removal, and generative filling. It provides a suite of tools for erasing unwanted elements from photos and filling the resulting gaps using generative artificial intelligence.

The project includes specialized capabilities for image outpainting to extend borders, background removal through object segmentation, and face restoration to fix visual defects. It also features an image upscaler to increase resolution and clarity via super-resolution AI, as well as a Stable Diffusion-based editor for replacing speci
- [yaofanguk/video-subtitle-remover](https://awesome-repositories.com/repository/yaofanguk-video-subtitle-remover.md) (11,493 ⭐) — This project is a local AI inpainting tool designed to erase hard-coded subtitles and watermarks from videos and images. It functions as a content-aware media restorer that uses deep learning to reconstruct missing pixels and preserve the original resolution of the source files.

The software is distinguished by its local execution model, running inference on host hardware to process media without relying on external cloud APIs. It employs content-aware model selection, allowing the use of different generative algorithms based on media types, such as animation or live action, to optimize visua
- [zuruoke/watermark-removal](https://awesome-repositories.com/repository/zuruoke-watermark-removal.md) (4,616 ⭐) — 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
- [lxfater/inpaint-web](https://awesome-repositories.com/repository/lxfater-inpaint-web.md) (5,834 ⭐) — A free and open-source inpainting & image-upscaling tool powered by webgpu and wasm on the browser。|   基于 Webgpu 技术和 wasm 技术的免费开源 inpainting & image-upscaling 工具, 纯浏览器端实现。
- [journey-ad/gemini-watermark-remover](https://awesome-repositories.com/repository/journey-ad-gemini-watermark-remover.md) (2,841 ⭐) — This project is an AI watermark removal tool designed to restore pixels hidden by logos and masks in images and videos. It utilizes reverse alpha blending to eliminate watermarks and recover original media content.

The tool operates as a local media processor, executing all restoration algorithms on the client device or within the browser to prevent files from being uploaded to remote servers. It further functions as a browser media interceptor via extensions and userscripts to automatically replace watermarked previews and downloads with cleaned versions.

Capabilities include bulk media pro
- [thtrieu/yolotf](https://awesome-repositories.com/repository/thtrieu-yolotf.md) (6,140 ⭐) — yolotf is an object detection framework that provides tools for converting Darknet model configurations and weights into TensorFlow graphs. It includes a TensorFlow model trainer for training new detection models or fine-tuning existing weights using custom datasets.

The project features a mobile model exporter that serializes graph definitions and metadata into protobuf files for deployment on mobile devices.

The framework supports object detection inference on images and video to identify objects and export bounding box coordinates. It manages model state through weight-mapping translation
- [jwyang/faster-rcnn.pytorch](https://awesome-repositories.com/repository/jwyang-faster-rcnn-pytorch.md) (7,859 ⭐) — This project is a PyTorch object detection framework that implements the Faster R-CNN architecture. It serves as a vision model for predicting precise bounding boxes around multiple objects within images and live video feeds.

The system is optimized for multi-GPU training to reduce the time required for model convergence. It utilizes a GPU-accelerated design to handle the training and inference of complex detection networks.

The framework covers the full object detection lifecycle, including custom network training and inference for static images and real-time video streams. It includes capa
- [uminosachi/sd-webui-inpaint-anything](https://awesome-repositories.com/repository/uminosachi-sd-webui-inpaint-anything.md) (1,290 ⭐) — This project is an integrated creative interface for image manipulation that combines generative canvas expansion, object segmentation, and diffusion-based inpainting. It functions as an extension for Stable Diffusion, providing a workflow to isolate specific elements and perform targeted content modifications through prompt-guided synthesis.

The tool distinguishes itself by automating the creation of precise selection masks, allowing users to identify and isolate objects by pointing to them rather than manually drawing selections. By chaining segmentation models with generative diffusion pip
- [geekyutao/inpaint-anything](https://awesome-repositories.com/repository/geekyutao-inpaint-anything.md) (7,642 ⭐) — Inpaint-Anything is a diffusion-based image editor and inpainting tool designed to remove or replace objects in images, videos, and 3D scenes. It functions as a text-guided manipulator that uses natural language descriptions and mask-based filling to modify visual content.

The system provides specialized capabilities for multi-view 3D scene editing and video object removal. It tracks selected objects across multiple frames or perspectives to synthesize consistent backgrounds and maintain spatial coherence after an element is removed.

The tool covers a range of image manipulation tasks, inclu
- [ultralytics/yolov3](https://awesome-repositories.com/repository/ultralytics-yolov3.md) (10,571 ⭐) — This is a real-time object detection framework built on the YOLOv3 architecture, implemented in PyTorch. It provides a complete pipeline for identifying and localizing objects in images and video using a single neural network pass, combining a Darknet-53 backbone with multi-scale feature pyramids and anchor-based bounding box prediction.

The framework extends beyond basic detection to include instance segmentation, human pose estimation, and multi-object tracking across video frames. It offers a model export toolkit that converts trained models through ONNX to CoreML, TensorFlow Lite, and Ten