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hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks that can classify images, detect objects, and interpret spatial relationships. The framework includes support for multiple types of captcha challenges such as object selection, drag-and-drop puzzles, and image labeling tasks. It implements an agent-style workflow where the system interprets the challenge prompt, selects the appropriate vision model, and generates the required interaction automatically.
Features
- Computer vision models for solving image-based captcha challenges
- Support for tasks such as image classification, drag-and-drop, and object selection
- Agent-based workflow that interprets captcha prompts and selects strategies
- Integration with multiple vision models including ResNet, YOLO, and CLIP
- Self-supervised challenge solving without third-party captcha services
- Modular architecture allowing custom models and challenge strategies
Project Samples
