Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
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Updated
Aug 29, 2024 - Python
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Pytorch implementation of convolutional neural network visualization techniques
An implementation of Grad-CAM with keras
[ICCV 2017] Torch code for Grad-CAM
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)
pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...
tensorflow implementation of Grad-CAM (CNN visualization)
Implementation of Grad CAM in tensorflow
Official implementation of Score-CAM in PyTorch
A generalized gradient-based CNN visualization technique
Neural network visualization toolkit for tf.keras
TensorFlow implementations of visualization of convolutional neural networks, such as Grad-Class Activation Mapping and guided back propagation
InterpretDL: Interpretation of Deep Learning Models,基于『飞桨』的模型可解释性算法库。
📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.
[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.
COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807
🌈 📷 Gradient-weighted Class Activation Mapping (Grad-CAM) Demo
Visualizations for understanding the regressed wheel steering angle for self driving cars
In this part, I've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
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