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.