prakashjayy / medium_blogs

Reproduces ResNet-V3 with pytorch

Classification models trained on ImageNet. Keras.

OpenMMLab Image Classification Toolbox and Benchmark

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

Classification with PyTorch.

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

PyTorch implementation of CNNs for CIFAR benchmark

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)

A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.

Speech commands recognition with PyTorch

Implementation of popular deep learning networks with TensorRT network definition API

Extract video features from raw videos using multiple GPUs. We support RAFT and PWC flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, ResNet features.

ICDSS Machine Learning Workshop Series: Neural Networks

This is a code repository for pytorch c++ (or libtorch) tutorial.

Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes

Generating Pokemon cards using a mixture of StyleGAN and RNN to create beautiful & vibrant cards ready for battle!