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Updated
Jun 6, 2021 - Python
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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》)
Best Practices, code samples, and documentation for Computer Vision.
cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集,极市团队整理
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
Hi! I've noticed the doc references postgres for setting up data storage (https://labelstud.io/guide/storedata.html). However, I was wondering whether it's possible to switch to other databases such as MySQL for the same task. If so, more or less how'd the process be? I'm trying to set up label-studio and the environment I'm using only allows MySQL DBs.
Thanks!
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
It would be convenient for the annotators to hav
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
There are many links in Kinetics that have expired. As as result, everyone might not be using the same Kinetics dataset. As a reference, the statistics of the Kinetics dataset used in PySlowFast can be found here, https://github.com/facebookresearch/video-nonlocal-net/blob/master/DATASET.md. However, I cannot seem to find similar information for gluoncv. Will you guys be sharing the statistics and
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
When running TabularPredictor.fit(), I encounter a BrokenPipeError for some reason.
What is causing this?
Could it be due to OOM error?
Fitting model: XGBoost ...
-34.1179 = Validation root_mean_squared_error score
10.58s = Training runtime
0.03s = Validation runtime
Fitting model: NeuralNetMXNet ...
-34.2849 = Validation root_mean_squared_error score
43.63s =
Differentiable architecture search for convolutional and recurrent networks
A library for transfer learning by reusing parts of TensorFlow models.
Let's add official support for all sklearn metrics to our Metric API.
Sklearn
Deep Learning API and Server in C++14 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
Nudity detection with JavaScript and HTMLCanvas
Sandbox for training deep learning networks
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)
Implementation of EfficientNet model. Keras and TensorFlow Keras.
A curated list of deep learning image classification papers and codes
Labelbox is the fastest way to annotate data to build and ship computer vision applications.
with video_demo.py about 20% speed compared to your 1.0 repo. but thanks much for sharing!
Official Implementation of 'Fast AutoAugment' in PyTorch.
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
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."
I'm using this project to train my segmentation model. I find that the mask has a right-down offset to the image. Because the opencv resize_nearest is wrong. Please refer the opencv project issue:
https://github.com/opencv/opencv/issues/9096
https://github.com/opencv/opencv/issues/10146
The code of opencv is:
` for( x = 0; x < dsize.width; x++ )
{
int sx = cv