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fix some typos #237

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fix some typos #237

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de8a31b
make args happy
ShoufaChen Apr 20, 2022
db7b42d
fix mean and std value
ShoufaChen Apr 20, 2022
f58e715
reverse transform for vit
ShoufaChen Apr 23, 2022
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2 changes: 1 addition & 1 deletion README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -185,7 +185,7 @@ To use with CUDA:

You can choose between:

`GradCAM` , `ScoreCAM`, `GradCAMPlusPlus`, `AblationCAM`, `XGradCAM` , `LayerCAM`, 'FullGrad' and `EigenCAM`.
`gradcam`, `gradcam++`, `scorecam`, `xgradcam`, `ablationcam`, `eigencam`, `eigengradcam`, `layercam`, `fullgrad`.

Some methods like ScoreCAM and AblationCAM require a large number of forward passes,
and have a batched implementation.
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6 changes: 3 additions & 3 deletions usage_examples/swinT_example.py
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Expand Up @@ -108,9 +108,9 @@ def reshape_transform(tensor, height=7, width=7):
rgb_img = cv2.imread(args.image_path, 1)[:, :, ::-1]
rgb_img = cv2.resize(rgb_img, (224, 224))
rgb_img = np.float32(rgb_img) / 255
input_tensor = preprocess_image(rgb_img, mean=[0.5, 0.5, 0.5],
std=[0.5, 0.5, 0.5])

input_tensor = preprocess_image(
rgb_img, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
)

# AblationCAM and ScoreCAM have batched implementations.
# You can override the internal batch size for faster computation.
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6 changes: 3 additions & 3 deletions usage_examples/vit_example.py
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Expand Up @@ -12,7 +12,6 @@
EigenGradCAM, \
LayerCAM, \
FullGrad

from pytorch_grad_cam import GuidedBackpropReLUModel
from pytorch_grad_cam.utils.image import show_cam_on_image, \
preprocess_image
Expand Down Expand Up @@ -110,8 +109,9 @@ def reshape_transform(tensor, height=14, width=14):
rgb_img = cv2.imread(args.image_path, 1)[:, :, ::-1]
rgb_img = cv2.resize(rgb_img, (224, 224))
rgb_img = np.float32(rgb_img) / 255
input_tensor = preprocess_image(rgb_img, mean=[0.5, 0.5, 0.5],
std=[0.5, 0.5, 0.5])
input_tensor = preprocess_image(
rgb_img, mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]
)

# If None, returns the map for the highest scoring category.
# Otherwise, targets the requested category.
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