docs: Updated notebook ref in READMEs (#102)

* docs: Updated notebook ref in READMEs

* docs: Updated quicktour

README.md

@@ -1,7 +1,7 @@
 
 # TorchCAM: class activation explorer
 
-[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE) [![Codacy Badge](https://app.codacy.com/project/badge/Grade/25324db1064a4d52b3f44d657c430973)](https://www.codacy.com/gh/frgfm/torch-cam/dashboard?utm_source=github.com&utm_medium=referral&utm_content=frgfm/torch-cam&utm_campaign=Badge_Grade) ![Build Status](https://github.com/frgfm/torch-cam/workflows/tests/badge.svg) [![codecov](https://codecov.io/gh/frgfm/torch-cam/branch/master/graph/badge.svg)](https://codecov.io/gh/frgfm/torch-cam) [![Docs](https://img.shields.io/badge/docs-available-blue.svg)](https://frgfm.github.io/torch-cam) [![Pypi](https://img.shields.io/badge/pypi-v0.2.0-blue.svg)](https://pypi.org/project/torchcam/) [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/frgfm/torch-cam) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/frgfm/torch-cam/blob/master/notebooks/quicktour.ipynb)
+[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE) [![Codacy Badge](https://app.codacy.com/project/badge/Grade/25324db1064a4d52b3f44d657c430973)](https://www.codacy.com/gh/frgfm/torch-cam/dashboard?utm_source=github.com&utm_medium=referral&utm_content=frgfm/torch-cam&utm_campaign=Badge_Grade) ![Build Status](https://github.com/frgfm/torch-cam/workflows/tests/badge.svg) [![codecov](https://codecov.io/gh/frgfm/torch-cam/branch/master/graph/badge.svg)](https://codecov.io/gh/frgfm/torch-cam) [![Docs](https://img.shields.io/badge/docs-available-blue.svg)](https://frgfm.github.io/torch-cam) [![Pypi](https://img.shields.io/badge/pypi-v0.2.0-blue.svg)](https://pypi.org/project/torchcam/) [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/frgfm/torch-cam) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/frgfm/notebooks/blob/main/torch-cam/quicktour.ipynb)
 
 Simple way to leverage the class-specific activation of convolutional layers in PyTorch.
 

docs/source/notebooks/quicktour.rst

@@ -13,7 +13,7 @@ Latest stable release
 
 .. code-block:: python
 
- >>> !pip install torch-cam
+ >>> !pip install torchcam
 
 From source
 -----------
@@ -29,6 +29,20 @@ Now go to ``Runtime/Restart runtime`` for your changes to take effect!
 Basic usage
 ===========
 
+.. code-block:: python
+
+ >>> %matplotlib inline
+ >>> # All imports
+ >>> import matplotlib.pyplot as plt
+ >>> import torch
+ >>> from torch.nn.functional import softmax, interpolate
+ >>> from torchvision.io.image import read_image
+ >>> from torchvision.models import resnet18
+ >>> from torchvision.transforms.functional import normalize, resize, to_pil_image
+ >>> 
+ >>> from torchcam.cams import SmoothGradCAMpp, LayerCAM
+ >>> from torchcam.utils import overlay_mask
+
 .. code-block:: python
 
  >>> # Download an image
@@ -40,24 +54,13 @@ Basic usage
 .. code-block:: python
 
  >>> # Instantiate your model here
- >>> from torchvision.models import resnet18
  >>> model = resnet18(pretrained=True).eval()
 
 
 
 Illustrate your classifier capabilities
 ---------------------------------------
 
-.. code-block:: python
-
- >>> %matplotlib inline
- >>> # All imports
- >>> from torchvision.io.image import read_image
- >>> from torchvision.transforms.functional import normalize, resize, to_pil_image
- >>> import matplotlib.pyplot as plt
- >>> from torchcam.cams import SmoothGradCAMpp, LayerCAM
- >>> from torchcam.utils import overlay_mask
-
 .. code-block:: python
 
  >>> cam_extractor = SmoothGradCAMpp(model)
@@ -69,6 +72,7 @@ Illustrate your classifier capabilities
  >>> out = model(input_tensor.unsqueeze(0))
  >>> # Retrieve the CAM by passing the class index and the model output
  >>> cams = cam_extractor(out.squeeze(0).argmax().item(), out)
+ WARNING:root:no value was provided for `target_layer`, thus set to 'layer4'.
 
 .. code-block:: python
 
@@ -104,18 +108,14 @@ Advanced tricks
 Extract localization cues
 -------------------------
 
-.. code-block::python
-
- >>> import torch
- >>> from torch.nn.functional import softmax, interpolate
-
 .. code-block::python
 
  >>> # Retrieve the CAM from several layers at the same time
  >>> cam_extractor = LayerCAM(model)
  >>> # Preprocess your data and feed it to the model
  >>> out = model(input_tensor.unsqueeze(0))
  >>> print(softmax(out, dim=1).max())
+ WARNING:root:no value was provided for `target_layer`, thus set to 'layer4'.
  tensor(0.9115, grad_fn=<MaxBackward1>)
 
 
@@ -135,6 +135,11 @@ Extract localization cues
  >>> axes[1].imshow(seg); axes[1].axis('off'); axes[1].set_title(name)
  >>> plt.show()
 
+.. code-block:: python
+
+ >>> # Once you're finished, clear the hooks on your model
+ >>> cam_extractor.clear_hooks()
+
 
 Fuse CAMs from multiple layers
 ------------------------------
@@ -153,6 +158,7 @@ Fuse CAMs from multiple layers
  >>> # This time, there are several CAMs
  >>> for cam in cams:
  >>> print(cam.shape)
+ torch.Size([28, 28])
  torch.Size([14, 14])
  torch.Size([7, 7])
 
@@ -175,3 +181,8 @@ Fuse CAMs from multiple layers
  >>> # Plot the overlayed version
  >>> result = overlay_mask(to_pil_image(img), to_pil_image(fused_cam, mode='F'), alpha=0.5)
  >>> plt.imshow(result); plt.axis('off'); plt.title(" + ".join(cam_extractor.target_names)); plt.show()
+
+.. code-block:: python
+
+ >>> # Once you're finished, clear the hooks on your model
+ >>> cam_extractor.clear_hooks()

notebooks/README.md

@@ -4,5 +4,5 @@ Here are some notebooks compiled for users to better leverage the library capabi
 
 | Notebook | Description | |
 |:----------|:-------------|------:|
-| [Quicktour](https://github.com/frgfm/torch-cam/blob/master/notebooks/quicktour.ipynb) | A presentation of the main features of TorchCAM | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/frgfm/torch-cam/blob/master/notebooks/quicktour.ipynb) |
-| [Latency benchmark](https://github.com/frgfm/torch-cam/blob/master/notebooks/latency_benchmark.ipynb) | How to benchmark the latency of a CAM method | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/frgfm/torch-cam/blob/master/notebooks/latency_benchmark.ipynb) |
+| [Quicktour](https://github.com/frgfm/notebooks/blob/main/torch-cam/quicktour.ipynb) | A presentation of the main features of TorchCAM | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/frgfm/notebooks/blob/main/torch-cam/quicktour.ipynb) |
+| [Latency benchmark](https://github.com/frgfm/notebooks/blob/main/torch-cam/latency_benchmark.ipynb) | How to benchmark the latency of a CAM method | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/frgfm/notebooks/blob/main/torch-cam/latency_benchmark.ipynb) |