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Updated
Jul 7, 2022 - Python
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Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集,极市团队整理
Describe the bug
When exporting a brush annotation as a PNG, the output is not mapped by the background colors specified in (Settings > Labeling Interface). In addition, when exporting as a JSON, the background colors for the attributes are not specified anywhere, leaving the values that were selected in the interface as arbitrary and as not linked to any of the outputs.
To Reproduce
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Best Practices, code samples, and documentation for Computer Vision.
I want to access the traefik dashboard. I have cvat setup on a server with https. I modified the docker-compose.https.yml according to the comment for using the traefik dashboard. So included the lin
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
Hi,
I need to download the something-to-something and jester datasets. But the 20bn website "https://20bn.com" are not available for weeks, the error message is "503 Service Temporarily Unavailable".
I have already downloaded the video data of something-to-something v2, and I need the label dataset. For the Jester, I need both video and label data. Can someone share me the
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
Add PECOS model to TabularPredictor.
If you'd like to work on this, please respond to this GitHub issue.
It is recommended to follow the custom model tutorial for implementing the model into AutoGluon.
A treasure chest for visual recognition powered by PaddlePaddle
Resources for deep learning with satellite & aerial imagery
Currently the X argument of CleanLearning.fit() does not seem to support non-array data.
Perhaps this is due to the sklearn function check_X_y() called inside CleanLearning, which we could replace.
Or perhaps it's due to how the cross-validation is currently being implemented.
However these are both easy to improve to rid the restriction that only array data are supported.
Seems e
Differentiable architecture search for convolutional and recurrent networks
A library for transfer learning by reusing parts of TensorFlow models.
Accelerated deep learning R&D
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
Sandbox for training deep learning networks
Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
Nudity detection with JavaScript and HTMLCanvas
A curated list of deep learning image classification papers and codes
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN),图神经网络(GNN),NLP,大数据相关的发展路书(roadmap), 并附海量源码(python,pytorch)带大家消化基本知识点,突破面试,完成从新手到合格工程师的跨越,其中深度学习相关论文附有tensorflow caffe官方源码,应用部分含推荐算法和知识图谱
ICCV2021/2019/2017 论文/代码/解读/直播合集,极市团队整理
Implementation of EfficientNet model. Keras and TensorFlow Keras.
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Labelbox is the fastest way to annotate data to build and ship computer vision applications.
Add a description, image, and links to the image-classification topic page so that developers can more easily learn about it.
To associate your repository with the image-classification topic, visit your repo's landing page and select "manage topics."
Enhancement
A discussion in #614 revealed a good place for improvement - we should ensure that input image is continuous upon start of the augmentation pipeline. This could be implemented by adding
image = np.ascontiguousarray(image)to image and mask targets.A proposed place to add this call - somewhere at the beginning of
A.Compose.__call__.