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YOLO v3 - Robust Deep Learning Object Detection in 1 Hour [Video]

More Information
Learn
  • Learn the State of the Art in Object Detection using Yolo V3.
  • Discover the Object Detection Workflow that saves you time and money.
  • The quickest way to gather images and annotate your dataset.
  • Secret tip to multiply your data using Data Augmentation.
  • How to use AI to label your dataset for you.
  • Find out how to train your own custom YoloV3 from scratch.
  • Step-by-step instructions on how to Execute, Annotate, Train and Deploy Custom Yolo V3 models.
About

When we first got started in Deep Learning particularly in Computer Vision, we were really excited at the possibilities of this technology to help people. The only problem is that if you are just getting started learning about AI Object Detection, you may encounter some of the following common obstacles along the way:
Labeling dataset is quite tedious and cumbersome,
Annotation formats between various object detection models are quite different.
Labels may get corrupt with free annotation tools,
Unclear instructions on how to train models - causes a lot of wasted time during trial and error.
Duplicate images are a headache to manage.
This got us searching for a better way to manage the object detection workflow, that will not only help us better manage the object detection process but will also improve our time to market.
Amongst the possible solutions we arrived at using Supervisely which is free Object Detection Workflow Tool, that can help you:
Use AI to annotate your dataset,
Annotation for one dataset can be used for other models (No need for any conversion) - Yolo, SSD, FR-CNN, Inception etc,
Robust and Fast Annotation and Data Augmentation,
Supervisely handles duplicate images.
You can Train your AI Models Online (for free) from anywhere in the world, once you've set up your Deep Learning Cluster.
So as you can see, that the features mentioned above can save you a tremendous amount of time.
All the code and supporting files for this course are available at: https://github.com/PacktPublishing/YOLO-v3---Robust-Deep-Learning-Object-Detection-in-1-Hour

Style and Approach

In this course, the author shows you how to use this workflow by training your own custom YoloV3 as well as how to deploy your models using PyTorch. So essentially, we've structured this training to reduce debugging, speed up your time to market and get you results sooner.

Features
  • Learn the State of the Art in Object Detection using Yolo V3 pre-trained model,
  • Discover the Object Detection Workflow that saves you time and money,
  • The quickest way to gather images and annotate your dataset while avoiding duplicates,
  • Secret tip to multiply your data using Data Augmentation,
  • How to use AI to label your dataset for you,
  • Find out how to train your own custom YoloV3 from scratch,
  • Step-by-step instructions on how to Execute, Collect Images, Annotate, Train and Deploy Custom Yolo V3 models,
Course Length 57 minutes
ISBN 9781838558789
Date Of Publication 17 Dec 2018

Authors

Ritesh Kanjee

Augmented Startups, have over 8 years experience in printed circuit board (PCB) design as well in image processing and embedded control. Author Ritesh Kanjee has completed his Masters Degree in Electronic Engineering and published two papers on the IEEE Database with one called "Vision-based adaptive Cruise Control using Pattern Matching" and the other called "A Three-Step Vehicle Detection Framework for Range Estimation Using a Single Camera" (on Google Scholar). His work was implemented in LabVIEW. He works as an embedded electronic engineer in Defence research and has experience in FPGA design with programming in both VHDL and Verilog. Ritesh also has expertise in augmented reality and machine learning in which he shall be introducing new technologies through the video platform.