Tool for attention visualization in ResNets inner layers.
The models used are the torchvision pretrained ones
(see this link
for further details)
A modified ResNet class, called ResNetAT, is available
at resnet_at.py, along with the functions to initialize
the different ResNet architectures. ResNetAT's forward
method is defined sucht that the inner layers' outputs
are available as model's outputs.
Python 3.6
| Pypi Package | Version |
|---|---|
| matplotlib | 3.3.2 |
| numpy | 1.19.4 |
| Pillow | 8.0.1 |
| torch | 1.7.0 |
| torchvision | 0.8.1 |
| Summary | ||||
|---|---|---|---|---|
| ResNet18 | ResNet34 | ResNet50 | ResNet101 | ResNet152 |
 |
 |
 |
 |
 |
| ResNeXt50_32x4d | ResNeXt101_32x8d | WideResNet50_2 | WideResNet101_2 | |
.png) |
.png) |
 |
 |
ResNet18↑
ResNet34↑
ResNet50↑
ResNet101↑
ResNet152↑
ResNeXt50_32x4d↑
ResNeXt101_32x8d↑
WideResNet50_2↑
WideResNet101_2↑