Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Trained on over 15000 images and still getting lackluster results #361

Open
avaseghi opened this issue Aug 7, 2019 · 1 comment
Open

Comments

@avaseghi
Copy link

avaseghi commented Aug 7, 2019

I'm training the model on over 15000 images but it's still outputting final test images like the one below:

train_00006000

I'm running the following command:

python main.py --data_dir dataset --dataset food --input_height 128 --output_height 128 --train

What can I do to get better results??

@WasabiThumb
Copy link
Contributor

First, ensure the uniformity of your dataset. Dataset "food" likely contains many different images, different kinds of food, etc. If that were the case, I would expect results like this. DCgan figured out background separation, a plate, and a subject.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants