All Projects → openvinotoolkit → Training_extensions

openvinotoolkit / Training_extensions

Licence: apache-2.0
Trainable models and NN optimization tools

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Training extensions

Rectlabel Support
RectLabel - An image annotation tool to label images for bounding box object detection and segmentation.
Stars: ✭ 338 (-60.56%)
Mutual labels:  ssd, segmentation, detection
Model Quantization
Collections of model quantization algorithms
Stars: ✭ 118 (-86.23%)
Mutual labels:  segmentation, quantization, detection
Awesome Gan For Medical Imaging
Awesome GAN for Medical Imaging
Stars: ✭ 1,814 (+111.67%)
Mutual labels:  segmentation, super-resolution, detection
Jacinto Ai Devkit
Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models
Stars: ✭ 49 (-94.28%)
Mutual labels:  segmentation, quantization, detection
shinTB
Textboxes : Image Text Detection Model : python package (tensorflow)
Stars: ✭ 90 (-89.5%)
Mutual labels:  detection, ssd, text-detection
Fastmaskrcnn
Mask RCNN in TensorFlow
Stars: ✭ 3,069 (+258.11%)
Mutual labels:  segmentation, detection
Cvpods
All-in-one Toolbox for Computer Vision Research.
Stars: ✭ 277 (-67.68%)
Mutual labels:  segmentation, detection
Chineseaddress ocr
Photographing Chinese-Address OCR implemented using CTPN+CTC+Address Correction. 拍照文档中文地址文字识别。
Stars: ✭ 309 (-63.94%)
Mutual labels:  text-detection, text-recognition
Megreader
A research project for text detection and recognition using PyTorch 1.2.
Stars: ✭ 332 (-61.26%)
Mutual labels:  text-detection, text-recognition
Awesome Ocr Resources
A collection of resources (including the papers and datasets) of OCR (Optical Character Recognition).
Stars: ✭ 335 (-60.91%)
Mutual labels:  text-detection, text-recognition
Medicaldetectiontoolkit
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
Stars: ✭ 917 (+7%)
Mutual labels:  segmentation, detection
Holy Edge
Holistically-Nested Edge Detection
Stars: ✭ 277 (-67.68%)
Mutual labels:  segmentation, detection
Realtime Action Detection
This repository host the code for real-time action detection paper
Stars: ✭ 271 (-68.38%)
Mutual labels:  ssd, detection
Awesome Iccv
ICCV2019最新录用情况
Stars: ✭ 305 (-64.41%)
Mutual labels:  segmentation, detection
Detectron.pytorch
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
Stars: ✭ 2,805 (+227.3%)
Mutual labels:  segmentation, detection
Sipmask
SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation (ECCV2020)
Stars: ✭ 255 (-70.25%)
Mutual labels:  segmentation, detection
Multi Human Parsing
🔥🔥Official Repository for Multi-Human-Parsing (MHP)🔥🔥
Stars: ✭ 507 (-40.84%)
Mutual labels:  segmentation, detection
Pvt
Stars: ✭ 379 (-55.78%)
Mutual labels:  segmentation, detection
Total Text Dataset
Total Text Dataset. It consists of 1555 images with more than 3 different text orientations: Horizontal, Multi-Oriented, and Curved, one of a kind.
Stars: ✭ 580 (-32.32%)
Mutual labels:  text-detection, text-recognition
Tensorflow Face Detection
A mobilenet SSD based face detector, powered by tensorflow object detection api, trained by WIDERFACE dataset.
Stars: ✭ 711 (-17.04%)
Mutual labels:  ssd, detection

OpenVINO™ Training Extensions

OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.

Quick Start Guide

Prerequisites

Setup OpenVINO™ Training Extensions

  1. Clone repository in the working directory by running the following:

    git clone https://github.com/openvinotoolkit/training_extensions.git
    export OTE_DIR=`pwd`/training_extensions
    
  2. Clone Open Model Zoo repository to run demos:

    git clone https://github.com/openvinotoolkit/open_model_zoo --branch develop
    export OMZ_DIR=`pwd`/open_model_zoo
    
  3. Install prerequisites by running the following:

    sudo apt-get install python3-pip virtualenv
    
  4. Create and activate virtual environment:

    cd training_extensions
    virtualenv venv
    source venv/bin/activate
    
  5. Install ote package:

    pip3 install -e ote/
    

Models

After installation, you are ready to train your own models, evaluate and use them for prediction.

Misc

Models that were previously developed can be found here.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].