Object Detection Using Facebook's Detectron2

提供方
Coursera Project Network
在此指导项目中,您将:

Create an Object Detection Model using Facebook's Detectron2.

Make Inferences Using the Object Detection Model

Clock2 hours
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this 2-hour long project-based course, you will learn how to train an Object Detection Model using Facebook's Detectron2. Detectron2 is a research platform and a production library for deep learning, built by Facebook AI Research (FAIR). We will be building an Object Detection Language Identification Model to identify English and Hindi texts written which can be extended to different use cases. We will look at the entire cycle of Model Development and Evaluation in Detectron2. We will first look at how to load a dataset, visualize it and prepare it as an input to the Deep Learning Model. We will then look at how we can build a Faster R-CNN model in Detectron2 and customize it. We will then configure the parameters & hyperparameters of the model. We will then move on to training the Model and subsequently to model inference and evaluation. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培养的技能

  • Computer Vision
  • Object Detection
  • Deep Learning
  • Detectron2

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Introduction to Detectron2 & Setup

  2. Preparing and loading the Dataset

  3. Visualizing the Dataset

  4. Build and Customizing the Training Model

  5. Configuring & Training the Model

  6. Inference & Evaluation

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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