GTSRB
affnet
| GTSRB | affnet | |
|---|---|---|
| 1 | 1 | |
| 108 | 261 | |
| - | - | |
| 10.0 | 0.0 | |
| almost 2 years ago | almost 2 years ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
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GTSRB
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Need help with a project!!
https://github.com/vamsiramakrishnan/TrafficSignRecognition https://github.com/surmenok/GTSRB/blob/master/german-traffic-signs.ipynb https://github.com/alessiamarcolini/deepstreet https://github.com/JamesLuoau/Traffic-Sign-Recognition-with-Deep-Learning-CNN https://github.com/wolfapple/traffic-sign-recognition https://github.com/hellojialee/Traffic_Sign_Recognition_Efficient_CNN
affnet
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Determine whether an image, from a given sequence of images, has changed considerably
Maybe you can try using an object detector, with the classes you are interested in and then processing the detections with another network to say if the objects are the same or not. Maybe you can try things like https://github.com/ducha-aiki/affnet
What are some alternatives?
SkinDeep - Get Deinked!!
hardnet - Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"
TrafficSignRecognition - A Deep Neural Network to do traffic sign recognition
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
deepstreet - Traffic Sign Recognition - Fine tuning VGG16 + GTSRB
Text2Poster-ICASSP-22 - Official implementation of the ICASSP-2022 paper "Text2Poster: Laying Out Stylized Texts on Retrieved Images"
Super-Cars-VS-SUVs - This is a deep neural network that looks at an images of cars and then classify them as suv and supercars
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Traffic_Sign_Recognition_Efficient_CNNs - A repository for the paper "Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild"
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
glasses - High-quality Neural Networks for Computer Vision 😎
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).