Pytorch Implementation of rpautrat/SuperPoint

python export detections_repeatability.py python compute_repeatability.py (NOTE: You have to edit *.yaml files to run corresponding tasks, especially for the following items model name: superpoint # magicpoint … data: name: coco #synthetic image_train_path: [‘./data/mp_coco_v2/images/train2017’,] #several data sets can be list here label_train_path: [‘./data/mp_coco_v2/labels/train2017/’,] image_test_path: ‘./data/mp_coco_v2/images/test2017/’ label_test_path: ‘./data/mp_coco_v2/labels/test2017/’    

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LayoutTransformer: Layout Generation and Completion with Self-attention

arXiv | BibTeX | Project Page This repo contains code for single GPU training of LayoutTransformer from LayoutTransformer: Layout Generation and Completion with Self-attention. This code was rewritten from scratch using a cleaner GPT codebase. Some of the details such as training hyperparameters might differ from the arxiv version of the paper. How To Use This Code Start a new conda environment conda env create -f environment.yml conda activate layout or update an existing environment conda env    

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Open source Optical Character Recognition based on PyTorch

GeneralOCR is open source Optical Character Recognition based on PyTorch. It makes a fidelity and useful tool to implement SOTA models on OCR domain. You can use them to infer and train the model with your customized dataset. The solution architecture of this project is re-implemented from facebook Detectron and openmm-cv. Refer to the guideline of gen_ocr installation Configuration Model text detection Supported Algorithms: Text Detection Table 1: Text detection algorithms, papers and parameters configuration in SDK. Model text recognition […]

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The Official PyTorch Implementation of DiscoBox

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilibili) DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision.Shiyi Lan, Zhiding Yu, Chris Choy, Subhashree Radhakrishnan, Guilin Liu, Yuke Zhu, Larry Davis, Anima AnandkumarInternational Conference on Computer Vision (ICCV) 2021 This repository contains the official Pytorch implementation of training & evaluation code and pretrained models for DiscoBox.DiscoBox is a    

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Unofficial PyTorch implementation of MobileViT

Overview This is a PyTorch implementation of MobileViT specified in “MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer“, arXiv 2021. Usage import torch from mobilevit import mobilevit_xxs net = mobilevit_xxs() img = torch.randn(1, 3, 256, 256) out = net(img) Credits Code adapted from MobileNetV2 and ViT. GitHub https://github.com/chinhsuanwu/mobilevit-pytorch    

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WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

Authors official PyTorch implementation of the WarpedGANSpace: Finding non-linear RBF paths in GAN latent space (ICCV 2021). If you use this code for your research, please cite our paper. Overview In this work, we try to discover non-linear interpretable paths in GAN latent space. For doing so, we model non-linear paths using RBF-based warping functions, which by warping the latent space, endow it with vector fields (their gradients). We use the latter to traverse the latent space across the paths […]

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NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch

Paper: https://arxiv.org/abs/2102.06171.pdf Original code: https://github.com/deepmind/deepmind-research/tree/master/nfnets Do star this repository if it helps your work! Note: See this comment for a generic implementation for any optimizer as a temporary reference for anyone who needs it. Install from PyPi: pip3 install nfnets-pytorch or install the latest code using: pip3 install git+https://github.com/vballoli/nfnets-pytorch WSConv2d Use WSConv2d and WSConvTranspose2d like any other torch.nn.Conv2d or torch.nn.ConvTranspose2d modules. import torch from torch import nn from nfnets import WSConv2d conv = nn.Conv2d(3,6,3) w_conv = WSConv2d(

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LSTM and QRNN Language Model Toolkit for PyTorch

This repository contains the code used for two Salesforce Research papers: The model comes with instructions to train: word level language models over the Penn Treebank (PTB), WikiText-2 (WT2), and WikiText-103 (WT103) datasets character level language models over the Penn Treebank (PTBC) and Hutter Prize dataset (enwik8) The model can be composed of an LSTM or a Quasi-Recurrent Neural Network (QRNN) which is two or more times faster than the cuDNN LSTM in this setup while achieving equivalent or better […]

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