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mpg

mrlabeler

A wonderful annotation tool of objection detection

ms-snsd

The Microsoft Scalable Noisy Speech Dataset (MS-SNSD) is a noisy speech dataset that can scale to arbitrary sizes depending on the number of speakers, noise types, and Speech to Noise Ratio (SNR) levels desired.

mucgec

MuCGEC中文纠错数据集及文本纠错SOTA模型开源；Code & Data for our NAACL 2022 Paper "MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction"

nas-projects

Several neural architecture search (NAS) algorithms implemented in PyTorch.

netron

Visualizer for neural network, deep learning and machine learning models

new-pac

科学/自由上网，免费ss/ssr/v2ray/goflyway账号，搭建教程

news

基于Django前后端分离开发-新闻管理系统

nni

An open source AutoML toolkit for neural architecture search, model compression and hyper-parameter tuning.

nnunet

od-annotation

目标检测数据集标注工具

oolworkshop.github.io

paddledetection

paddleseg

A high performance semantic segmentation toolkit based on PaddlePaddle. (『飞桨』图像分割库）

paperaweek

Paper a Week Website

pas-ogb

CIKM 2021: Pooling Architecture Search for Graph Classification

pca-gm

Code for ICCV 2019 oral paper: Learning Combinatorial Embedding Networks for Deep Graph Matching

pixel_level_land_classification

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

pixelannotationtool

Annotate quickly images.

plant-disease-diagnostics-using-uav-and-android-app

Plant diseases causes many significant damages and losses in crops around the world. Some suitable measures on disease identification should be introduced to prevent damages and minimize losses. Early Detection of Disease helps in increasing the crop productivity as well as in minimizing expense. Technical approaches using machine learning and computer vision are actively researched to achieve intelligence farming by early detection on plant disease. The accuracy of object detection and recognition systems has been drastically improved by the recent development in Deep Neural Networks. By using these systems and implementation of computer vision and machine learning techniques, plant diseases can be detected. Here we have used transfer learning based approach to diagnose diseases of different plants using its images captured by camera devices either drone or smartphone. Our goal is to build a market oriented product for Plant Disease Detection, a smartphone app compatible with both smartphone camera and drone camera. The target group of the user is those who request a quick diagnosis on common leaf disease at any time of the day i.e. Farmers, agricultural industries, agricultural consultants and Government Agencies & Departments.

plat

practicalai

📚 A practical approach to machine learning.

practicalai-cn

AI实战-practicalAI 中文版

prodigy-recipes

🍳 Recipes for the Prodigy, our fully scriptable annotation tool

pseudolabeling

Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"

pyprobml

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

pytorch-metric-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

pytorch-polygon-rnn

Pytorch implementation of Polygon-RNN(http://www.cs.toronto.edu/polyrnn/poly_cvpr17/)

pytorch-project-template

A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.

pytorch-semseg

Semantic Segmentation Architectures Implemented in PyTorch