A PyTorch Implementation for Sketch Classification Networks.
- Optimizer
- Adam
TU-Berlin sketch dataset
Model | input_size |
---|---|
(raw size)* | 1111 * 1111 |
AlexNet | 224 * 224 |
SketchANet | 225 * 225 |
ResNet18 | 224 * 224 |
ResNet34 | 224 * 224 |
ResNet50 | 224 * 224 |
DenseNet121 | 224 * 224 |
Inception_v3 | 299 * 299 |
Model | lr | clip_grad_norm(max_norm) | learning rate decay | weight_decay |
---|---|---|---|---|
AlexNet(pretrained) | 2e-4 | -- | 20 | 0.0005 |
AlexNet(scratch) | 2e-5 | 0.5 - 100.0 | 30 | 0.0005 |
SketchANet(DogsCats)* | 2e-5 | 0.5 - 1.0 | 30 | 0.0005 |
SketchANet(scratch) | 2e-5 | 0.5 - 100.0 | 800 | 0.0001 - 0.0003 |
ResNet18(pretrained) | 2e-4 | -- | 20 | 0.0005 |
ResNet34(pretrained) | 2e-4 | -- | 20 | 0.0001 |
ResNet50(pretrained) | 2e-4 | -- | 20 | 0.0005 |
DenseNet121(pretrained) | 2e-4 | -- | 20 | 0.0005 |
Inception_v3(pretrained) | 2e-4 | -- | 30 | 0.0005 |
- *This is for test Model.
Model | Prec@1 | Prec@5 |
---|---|---|
AlexNet(pretrained) | 93.4455 | 99.787 |
AlexNet(scratch) | 99.3024 | 99.988 |
SketchANet(scratch) | 86.3166 | 98.667 |
ResNet18(pretrained) | 96.9899 | 99.954 |
ResNet34(pretrained) | 97.1048 | 99.954 |
ResNet50(pretrained) | 98.3049 | 99.988 |
DenseNet121(pretrained) | 91.4301 | 99.596 |
Inception_v3(pretrained) | 91.8802 | 99.706 |
Model | Prec@1 | Prec@5 |
---|---|---|
Human | 73.1 | -- |
AlexNeti | 68.6 | -- |
AlexNetii | 77.29 | -- |
GoogLeNetii | 80.85 | -- |
AlexNet(pretrained) | 70.850 | 90.050 |
AlexNet(scratch) | 53.850 | 78.000 |
SketchANet(scratch) | 68.700 | 88.900 |
ResNet18(pretrained) | 77.800 | 94.650 |
ResNet34(pretrained) | 79.100 | 95.050 |
ResNet50(pretrained) | 78.300 | 95.300 |
DenseNet121(pretrained) | 77.550 | 93.500 |
Inception_v3(pretrained) | 76.550 | 93.750 |
-
- Sketch-a-Net that Beats Humans
- The Sketchy Database: Learning to Retrieve Badly Drawn Bunnies
DPN, ShuffleNetG2, SENet18
- GetImageMean_Std
Get image dataset mean and standard deviation.
- SplitDataset
Split image dataset according to the train and val record txt file.
- ListAllImageName
Get all image name in dataset.