FastestDet
pytorch-grad-cam
| FastestDet | pytorch-grad-cam | |
|---|---|---|
| 1 | 5 | |
| 713 | 9,570 | |
| - | - | |
| 0.0 | 5.0 | |
| about 1 year ago | 1 day ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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FastestDet
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FastestDet: a new ultra real-time anchor free target detection algorithm designed for ARM CPU, with only 250K parameters,
The time consumption in the table is measured by ncnn. The test platform is RK3568 ARM CPU. Compared with Yolo-fastest, the time consumption of fastestdet single core is reduced by 50%, and the index of map0.5 is 3.4% higher than Yolo-fastest. In fact, due to the increase of input resolution, the calculation amount of FastestDet is nearly twice that of Yolo-fastest. However, thanks to the minimalist network structure and the reduction of memory access, the actual test time on multiple platforms is greatly reduced, especially on single core or weak performance platforms, and the speed is increased by 50%+
pytorch-grad-cam
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Exploring GradCam and More with FiftyOne
For the two examples we will be looking at, we will be using pytorch_grad_cam, an incredible open source package that makes working with GradCam very easy. There are excellent other tutorials to check out on the repo as well.
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Which layers are doing image segmentation on AutoEncoders/U-NET?
https://github.com/jacobgil/pytorch-grad-cam.
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[D] Algorithm for view prediction?
I know I would like to use grad-CAM https://github.com/jacobgil/pytorch-grad-cam
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[P] Adapting Class Activation Maps for Object Detection and Semantic Segmentation
https://github.com/jacobgil/pytorch-grad-cam is a project that has a comprehensive collection of Pixel Attribution Methods for PyTorch (like the package name grad-cam that was the original algorithm implemented).
- [Project] Recent Class Activation Map Methods for CNNs and Vision Transformers
What are some alternatives?
PaddleViT - :robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
Transformer-Explainability - [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
ssd_keras - A Keras port of Single Shot MultiBox Detector
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
tf-keras-vis - Neural network visualization toolkit for tf.keras
Transformer-MM-Explainability - [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.