A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
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May 26, 2022 - Python
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A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
A PyTorch Implementation of Single Shot MultiBox Detector
A treasure chest for visual recognition powered by PaddlePaddle
Code examples for new APIs of iOS 10.
ICCV2021/2019/2017 论文/代码/解读/直播合集,极市团队整理
An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)
A modern, web-based photo management server. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, face recognition, location awareness, color analysis and other ML algorithms.
Notes for Fastai Deep Learning Course
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and compatible with Google Cloud ML Engine.
Descriptive Deep Learning
Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).
Deep Learning Computer Vision Algorithms for Real-World Use
Convolutional Neural Networks with Alternately Updated Clique (to appear in CVPR 2018)
基于u-net,cv2以及cnn的中文车牌定位,矫正和端到端识别软件,其中unet和cv2用于车牌定位和矫正,cnn进行车牌识别,unet和cnn都是基于tensorflow的keras实现
Experiments with Mobile
Implementation for <Large-Margin Softmax Loss for Convolutional Neural Networks> in ICML'16.
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)
Streaming over lightweight data transformations
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Computer Vision and Image Recognition algorithms for R users
tensorflowJS implementation of EfficientNet
Materials for GWU DNSC 6279 and DNSC 6290.
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Hi, I've created a simple katacoda scenario of "how to install Milvus 2.0 Standalone with docker-compose". Here is my github link: https://github.com/jaelgu/katacoda
Can we have a Katacoda scenario for each Bootcamp solution?