hCaptcha Challenger

? Gracefully face hCaptcha challenge with Yolov5(ONNX) embedded solution.



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.


  • Python 3.7+
  • google-chrome


  1. Clone the project code in the way you like.

  2. Execute the following command in the project root directory.

    # hcaptcha-challenger
    pip install -r ./requirements.txt
  3. Download Project Dependencies.

    The implementation includes downloading the YOLOv5 target detection model and detecting google-chrome in the current environment.

    If google-chrome is missing please follow the prompts to download the latest version of the client, if google-chrome is present you need to make sure it is up to date.

    Now you need to execute the cd command to access the /src directory of project and execute the following command to download the project dependencies.

    # hcaptcha-challenger/src
    python main.py install
  4. Start the test program.

    Check if chromedriver is compatible with google-chrome.

    # hcaptcha-challenger/src
    python main.py test
  5. Start the demo program.

    If the previous test passed perfectly, now is the perfect time to run the demo!

    # hcaptcha-challenger/src
    python main.py demo
  6. Have a good time.

    Enjoy it and port it to your project.


  1. You can download yolov5 onnx models of different sizes by specifying the model parameter in the install command.

    • Download yolov5s6 by default when no parameters are specified.

    • The models that can be chosen are yolov5n6yolov5m6yolov5s6.

    # hcaptcha-challenger/src
    python main.py install --model=yolov5n6
  2. You can run different yolo models by specifying the model parameter to compare the performance difference between them.

    • Similarly, when the model parameter is not specified, the yolov5s6 model is used by default.

    • Note that you should use install to download the missing models before running the demo.

    # hcaptcha-challenger/src
    python main.py demo --model=yolov5n6
  3. Comparison of programs.

    The following table shows the average solving time of the hCAPTCHA challenge for 30 rounds (one round for every 9 challenge images) of mixed categories processed by onnx models of different sizes.

    model(onnx) avg_time(s) size(MB)
    yolov5n6 0.71 12.4
    yolov5s6 1.422 48.2
    yolov5m6 3.05 136
    • Use of the YOLOv5n6(onnx) embedded scheme to obtain solution speeds close to the limit.

    • Use of the YOLOv5s6(onnx) embedded solution, which allows for an optimal balance between stability, power consumption, and solution efficiency.


Install Google Chrome on Ubuntu 18.04+

  1. Downloading Google Chrome

    wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
  2. Installing Google Chrome

    sudo apt install ./google-chrome-stable_current_amd64.deb

Install Google Chrome on CentOS 7/8

  1. Start by opening your terminal and downloading the latest Google Chrome .rpm package with the following wget command :

    wget https://dl.google.com/linux/direct/google-chrome-stable_current_x86_64.rpm
  2. Once the file is downloaded, install Google Chrome on your CentOS 7 system by typing:

    sudo yum localinstall google-chrome-stable_current_x86_64.rpm

Install Google Chrome on Windows / MacOs

Just go to Google Chrome official website to download and install.


View Github