Complete Guide to Creating COCO Datasets
What you'll learn
- How COCO annotations work and how to parse them with Python
- How to go beyond the original 90 categories of the COCO dataset
- How to automatically generate a huge synthetic COCO dataset with instance annotations
- How to train a Mask R-CNN to detect your own custom object categories in real photos
Requirements
- Take an Intro to Deep Learning course first (perhaps from another Udemy course!)
- Have basic to intermediate Python programming skills
- Have a physical or cloud computer with GPU/CUDA compute
- Recommended: Prior experience with Anaconda & Jupyter notebooks
Description
In this course, you'll learn how to create your own COCO dataset with images containing custom object categories. You'll learn how to use the GIMP image editor and Python code to automatically generate thousands of realistic, synthetic images with minimal manual effort. I'll walk you through all of the code, which is available on GitHub, so that you can understand it at a fundamental level and modify it for your own needs.
(Important: If you only want to do manual image annotation, this course is not for you. Google "coco annotator" for a great tool you can use. This course teaches how to generate datasets automatically.)
By the end of this course, you will:
Have a full understanding of how COCO datasets work
Know how to use GIMP to create the components that go into a synthetic image dataset
Understand how to use code to generate COCO Instances Annotations in JSON format
Create your own custom training dataset with thousands of images, automatically
Train a Mask R-CNN to spot and mark the exact pixels of custom object categories
Be able to apply this knowledge to real world problems
I've saved weeks of my precious time using this method because I'm not doing the tedious task of manual image labeling, which can easily take a full 40 hour work week to create 1000 images. You should value your time too. After all, how are you going to solve the world's problems if you're busy clicking outlines on images for the next couple weeks?
Soundtrack by Silk Music
Track name: Shingo Nakamura - Hakodate
Who this course is for:
- Developers who have completed a Deep Learning course and want to solve real-world image recognition problems
- Developers looking for a deep walkthrough of creating a COCO dataset and training a Mask R-CNN
Featured review
Instructor
- 4.6 Instructor Rating
- 615 Reviews
- 2,009 Students
- 2 Courses
Hey! I’m Adam Kelly. As I see it, artificial intelligence, 3d simulations, virtual reality, and augmented reality are going to change the world in ways we can only imagine. I’m committed to learning all about them by doing practical projects that solve real world problems and sharing what I learn along the way. I have a degree in Computer Science from the University of Michigan and almost a decade of professional development experience, including as a Software Engineer at Microsoft and General Motors. Let's learn together! :)