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+
Clone the project code in the way you like.
Execute the following command in the project root directory.
# hcaptcha-challenger pip install -r ./requirements.txt
Download Project Dependencies.
The implementation includes downloading the
YOLOv5target detection model and detecting
google-chromein the current environment.
google-chromeis 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
cdcommand to access the
/srcdirectory of project and execute the following command to download the project dependencies.
# hcaptcha-challenger/src python main.py install
Start the test program.
chromedriveris compatible with
# hcaptcha-challenger/src python main.py test
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
Have a good time.
Enjoy it and port it to your project.
You can download yolov5 onnx models of different sizes by specifying the
modelparameter in the
yolov5s6by default when no parameters are specified.
The models that can be chosen are
# hcaptcha-challenger/src python main.py install --model=yolov5n6
You can run different yolo models by specifying the
modelparameter to compare the performance difference between them.
Similarly, when the
modelparameter is not specified, the
yolov5s6model is used by default.
Note that you should use
installto download the missing models before running the demo.
# hcaptcha-challenger/src python main.py demo --model=yolov5n6
Comparison of programs.
The following table shows the average solving time of the
hCAPTCHAchallenge 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+
Downloading Google Chrome
Installing Google Chrome
sudo apt install ./google-chrome-stable_current_amd64.deb
Install Google Chrome on CentOS 7/8
Start by opening your terminal and downloading the latest Google Chrome
.rpmpackage with the following wget command :
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.