CDCGAN Generator and ResNet34 Classifier for QuickDraw! dataset from Google
airplane | bicycle | butterfly | cake | camera |
---|---|---|---|---|
chair | clock | diamond | The_Effiel_Tower | tree |
---|---|---|---|---|
Model: ResNet34
Train | Test | |
---|---|---|
Loss | ||
Accuracy | 99% | 96% |
- Prepare training data
cd Classification python download_data.py -c categories.txt -r Data python ./DataUtils/prepare_data.py -root Data -msc 10000 -v 0.2
- Start Training
python Classifier.py -e 40 -bs 64 -lr 0.1 -m resnet34
- Evaluation
python Evaluation.py -i ***.npy
Model: DCGAN / DCCGAN
Discriminator Loss | Generator Loss | Result | |
---|---|---|---|
airplane | |||
camera |
- Prepare training data
cd Generation python download_data.py -c categories.txt -r Data
- Start Training
- DCGAN
python dcgan.py -o airplane -e 40 -log 1 -lr 5e-5
- DCCGAN
python dccgan.py -c 30 -s 50000 -e 4 -log 1 -bs 64
- DCGAN
- Evaluation
- DCGAN
python Evaluation.py -r models/airplane -m DCGAN
- DCCGAN
python Evaluation.py -r Trained_models -m DCCGAN -c 30
- DCGAN
Thanks these guys.