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🥂 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.

License: GNU General Public License v3.0

Python 97.76% HTML 0.33% Jupyter Notebook 1.92%

hcaptcha-challenger's Introduction

hCaptcha Challenger

🚀 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.

Introduction

Does not rely on any Tampermonkey script.

Does not use any third-party anti-captcha services.

Just implement some interfaces to make AI vs AI possible.

Challenge Type	Pluggable Resource
`image_label_binary`	ResNet ONNX classification #challenge
`image_label_area_select: point`	YOLOv8 ONNX detection #588
`image_label_area_select: bounding box`	YOLOv8 ONNX segmentation #592
`image_label_multiple_choice`	ViT ONNX zero-shot motion #917

Advanced Task	Pluggable Resource
`Rank.Strategy`	#nested-model-zoo
`self-supervised challenge`	#CLIP-ViT

Tasks	Resource
`ci: sentinel`
`ci: collector`
`datasets: VCS, annoate`	#roboflow, #model-factory
`model: ResNet - train / val`
`model: YOLOv8 - train / val`
`model: upload, upgrade`	#objects, #modelhub
`datasets: public, archive`	#roboflow-universe, #captcha-datasets

I would like to express my sincere gratitude to all the contributors.

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