import torch from torchvision import models from torchvision.models import ResNet50_Weights from pytorch_grad_cam import ( GradCAM, HiResCAM, ScoreCAM, GradCAMPlusPlus, AblationCAM, XGradCAM, EigenCAM, EigenGradCAM, @@ -18,8 +19,8 @@ def get_args(): parser = argparse.ArgumentParser() ...
《Grad-CAM:Visual Explanations from Deep Networks via Gradient-based Localization》这篇论文基于梯度为其可解释性做了一些工作,它可以显著描述哪块图片区域对识别起了至关重要的作用,以热度图的方式可视化神经网络的注意力。本博客主要是基于pytorch的简单工程复现。原文见这里,本代码基于这里。 1importtorch2importto...
Pytorch - TypeError: 'torch.Size' object cannot be interpreted as an integer 39 Pytorch RuntimeError: Expected tensor for argument #1 'indices' to have scalar type Long; but got CUDAType instead 22 PyTorch - Getting the 'TypeError: pic should be PIL Image or ndarray. Got <class 'nu...
A2, and A3 are weighted to make the final heatmap. In CAM, we weight these feature maps using weights taken out of the last fully-connected layer of the network. In Grad-CAM, we weight the feature maps using “alpha values” that are calculated based on gradients. Therefore, Grad-CAM ...
torchcam chore: Updated license from MIT to Apache2.0 (#70) 4年前 .coveragerc feat: Added GradCAM and GradCAM++ implementations (#1) 5年前 .flake8 feat: Added GradCAM and GradCAM++ implementations (#1) 5年前 .gitignore chore: Added conda upload job (#3) ...
A PyTorch implementation of Grad-CAM based on ICCV 2017 paper "Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization" - leftthomas/GradCAM
get_distribution('grad_cam').version if digit_version(grad_cam_v) >= digit_version('1.3.7'): from pytorch_grad_cam.utils.model_targets import \ ClassifierOutputTarget targets = [ClassifierOutputTarget(c) for c in args.target_category] else: targets = args.target_category # calculate cam ...
PyTorch 1.13.1Cuda Toolkit 11.6Ubuntu 18.04 Install the required packages:conda create -n drawingspinup python=3.8 conda activate drawingspinup pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116 pip install ...
after adding above function inside "cam.py" change model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True, pretrained=True, autoshape=False)tomodel = attempt_load(r'D:\Remi\YOLOv5-GradCAM\pytorch-grad-cam\yolov5\runs\train\exp5\weights\best.pt') ...
conda create --name gauhuman python=3.8 conda activate gauhuman conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia pip install submodules/diff-gaussian-rasterization pip install submodules/simple-knn pip install --upgrade https://github....