pytorch-grad-cam
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jacobgil
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Thank you for publishing this software package, it is very useful for the community. However, when I perform multiple loss calculations, the memory will continue to grow and will not...
when i choose AblationCAM in YOLOv5 notebook，it will promt this issue, this is my part code about YOLOBoxScoreTarget `def __init__(self, labels, bounding_boxes, iou_threshold=0.5): self.labels = labels self.bounding_boxes = bounding_boxes self.iou_threshold...
Hi, I'm working on the attention mechanism for face recognition models, I'm using the ir model as a backbone, but I don't know much about the details of the implementation...
Using the SwinForImageClassification model using the code given below: ``` class ModelOutputTarget: def __init__(self): pass def __call__(self, model_output): return torch.sigmoid(model_output) image_processor = AutoImageProcessor.from_pretrained("microsoft/swin-base-patch4-window7-224-in22k") target_layers = [model.swin.encoder.layers[-1].blocks[1].layernorm_before] input_tensor = image_processor(img,return_tensors="pt") #print(input_tensor['pixel_values'])...
This PR marks some optional arguments as optional, and makes some numpy types more specific. `numpy.typing.NDArray` requires numpy >= 1.21, so I'm not sure if it can be used here...
I am trying to use GradCam on my model that takes more than one input arguments. I tried to pass *input_tensor instead of input_tensor since I have a list of...
Corrected the targets type to int as we are providing the class labels of the images for which we want to generate the cams instead of a list of neural...
Hi, Thanks for the Repo I am trying to use GradCAM on the X3D model from the tutorial below. https://pytorch.org/hub/facebookresearch_pytorchvideo_x3d/#define-input-transform However, I am getting the error below. Which I guess...
Hi, I'm trying to use GradCAM in an autoencoder to visualize the feature map of each layers from the encoder and decoder, I successfully got the image from encoder, but...
