This is the code I used to complete PA3(Conditional GAN) in the course “Computer Graphics Fundamentals” at Tsinghua University.
Since the final model file is over 5MB and cannot be uploaded, I put it on the following link: CGAN
Usage
Download the model file and place it in the same directory as CGAN.py. Run CGAN.py to output the sample image result.png, ensuring that the jittor framework is installed.
If you want to train the model, simply run CGAN_train.py directly. The program will automatically train and save the model file in the current directory at regular intervals.
CGAN
This is the code I used to complete PA3(Conditional GAN) in the course “Computer Graphics Fundamentals” at Tsinghua University.
Since the final model file is over 5MB and cannot be uploaded, I put it on the following link: CGAN
Usage
Download the model file and place it in the same directory as
CGAN.py. RunCGAN.pyto output the sample imageresult.png, ensuring that the jittor framework is installed.If you want to train the model, simply run
CGAN_train.pydirectly. The program will automatically train and save the model file in the current directory at regular intervals.