[ DevCourseWeb ] Yolo v3 - Robust Deep Learning Object Detection in 1 hour (Updated 05 - 2020)

[ DevCourseWeb.com ] Yolo v3 - Robust Deep Learning Object Detection in 1 hour (Updated 05/2020)

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Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | VTT | Size: 2.20 GB | Duration: 2h 18m
What you'll 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.

Requirements
Have prior experience in Python using Anaconda.
A PC/Laptop with CUDA-enabled NVIDIA graphics Card for training - We use Ubuntu for training.
Create a Free Account with Supervisely.
Be Familiar with Computer Vision or AI.
Description
Learn how we implemented YOLO V3 Deep Learning Object Detection Models From Training to Inference - Step-by-Step

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,

Use Winrar to Extract. And use a shorter path when extracting, such as C: drive

ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)

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