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.
Requirements
- Python 3.7+
- google-chrome
Usage
-
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
YOLOv5
target detection model and detectinggoogle-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
-
Start the test program.
Check if
chromedriver
is compatible withgoogle-chrome
.# 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.
Advanced
-
You can download yolov5 onnx models of different sizes by specifying the
model
parameter in theinstall
command.-
Download
yolov5s6
by default when no parameters are specified. -
The models that can be chosen are
yolov5n6
,yolov5m6
,yolov5s6
.
# hcaptcha-challenger/src python main.py install --model=yolov5n6
-
-
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, theyolov5s6
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
-
-
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.
-
Tour
Install Google Chrome on Ubuntu 18.04+
-
Downloading Google Chrome
wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
-
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
.rpm
package with the following wget command :wget https://dl.google.com/linux/direct/google-chrome-stable_current_x86_64.rpm
-
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.