refactor: Renamed ISSCAM into ISCAM (#30)

* refactor: Renamed IS-CAM now that paper is published

* refactor: Reflected changes on CAM naming

* docs: Updated documentation and README

* fix: Fixed import of ISCAM

README.md

@@ -94,6 +94,7 @@ This project is developed and maintained by the repo owner, but the implementati
 - [Smooth Grad-CAM++](https://arxiv.org/abs/1908.01224): SmoothGrad mechanism coupled with GradCAM.
 - [Score-CAM](https://arxiv.org/abs/1910.01279): score-weighting of class activation for better interpretability.
 - [SS-CAM](https://arxiv.org/abs/2006.14255): SmoothGrad mechanism coupled with Score-CAM.
+- [IS-CAM](https://arxiv.org/abs/2010.03023): integration-based variant of Score-CAM.
 
 
 

docs/source/cams.rst

@@ -16,7 +16,7 @@ Methods related to activation-based class activation maps.
 
 .. autoclass:: SSCAM
 
-.. autoclass:: ISSCAM
+.. autoclass:: ISCAM
 
 
 Grad-CAM

scripts/cam_example.py

@@ -15,7 +15,7 @@
 from torchvision import models
 from torchvision.transforms.functional import normalize, resize, to_tensor, to_pil_image
 
-from torchcam.cams import CAM, GradCAM, GradCAMpp, SmoothGradCAMpp, ScoreCAM, SSCAM, ISSCAM
+from torchcam.cams import CAM, GradCAM, GradCAMpp, SmoothGradCAMpp, ScoreCAM, SSCAM, ISCAM
 from torchcam.utils import overlay_mask
 
 VGG_CONFIG = {_vgg: dict(input_layer='features', conv_layer='features')
@@ -59,7 +59,7 @@ def main(args):
  cam_extractors = [CAM(model, conv_layer, fc_layer), GradCAM(model, conv_layer),
  GradCAMpp(model, conv_layer), SmoothGradCAMpp(model, conv_layer, input_layer),
  ScoreCAM(model, conv_layer, input_layer), SSCAM(model, conv_layer, input_layer),
- ISSCAM(model, conv_layer, input_layer)]
+ ISCAM(model, conv_layer, input_layer)]
 
  # Don't trigger all hooks
  for extractor in cam_extractors:

test/test_cams.py

@@ -123,7 +123,7 @@ def test_smooth_gradcampp(self):
  self._test_extractor(extractor, model)
 
 
-for cam_extractor in ['CAM', 'ScoreCAM', 'SSCAM', 'ISSCAM']:
+for cam_extractor in ['CAM', 'ScoreCAM', 'SSCAM', 'ISCAM']:
  def do_test(self, cam_extractor=cam_extractor):
  self._test_cam(cam_extractor)
  self._test_cam_arbitrary_layer(cam_extractor)

torchcam/cams/cam.py

@@ -5,7 +5,7 @@
 import torch.nn.functional as F
 from typing import Optional, List
 
-__all__ = ['CAM', 'ScoreCAM', 'SSCAM', 'ISSCAM']
+__all__ = ['CAM', 'ScoreCAM', 'SSCAM', 'ISCAM']
 
 
 class _CAM:
@@ -370,9 +370,9 @@ def __repr__(self) -> str:
  return f"{self.__class__.__name__}(batch_size={self.bs}, num_samples={self.num_samples}, std={self.std})"
 
 
-class ISSCAM(ScoreCAM):
- """Implements a variant of Score-CAM, based on Rakshit Naidu's `work
- <https://github.com/r0cketr1kky/ISS-CAM_resources>`_.
+class ISCAM(ScoreCAM):
+ """Implements a class activation map extractor as described in `"IS-CAM: Integrated Score-CAM for axiomatic-based
+ explanations" <https://arxiv.org/pdf/2010.03023.pdf>`_.
 
  The localization map is computed as follows:
 
@@ -402,7 +402,7 @@ class ISSCAM(ScoreCAM):
  >>> from torchvision.models import resnet18
  >>> from torchcam.cams import ISSCAM
  >>> model = resnet18(pretrained=True).eval()
- >>> cam = ISSCAM(model, 'layer4', 'conv1')
+ >>> cam = ISCAM(model, 'layer4', 'conv1')
  >>> with torch.no_grad(): out = model(input_tensor)
  >>> cam(class_idx=100)