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The main features of anuragranj/back2future.pytorch are: Computer Vision Models.
Open-source alternatives to anuragranj/back2future.pytorch include: cs230-stanford/cs230-code-examples — This repository provides structured code examples and project templates designed for classroom instruction in machine… aaltovision/dgc-net — A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network". aaron-xichen/pytorch-playground — Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet,… adamian98/pulse — Pulse is a generative model image upscaler and latent space image processor. It functions as a self-supervised photo… alaphao/coremlexample — An example of CoreML using a pre-trained VGG16 model. 1zb/deformable-convolution-pytorch — PyTorch implementation of Deformable Convolution.
This repository provides structured code examples and project templates designed for classroom instruction in machine learning and neural networks. It offers reference implementations of deep learning models for both computer vision and natural language processing tasks, built using PyTorch as the core framework. The codebase is organized as a modular project template with separate directories for data handling, model definitions, and training scripts, promoting reusability and clarity. It includes predefined pipelines for image classification and text processing, along with a command-line in
A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
PyTorch implementation of Deformable Convolution