Machine Learning Object Detection Tutorial Using YOLO (Free)
OctoML CLI 🔎
https://bit.ly/OctomlYOLO
YOLOv5 Model Deployment Tutorial 🔎
https://github.com/octoml/octoml-cli-...
YOLOv5 Object Detection Model Deployment to Docker Desktop (Full tutorial)
Object Detection is a highly popular use case of the famous YOLO computer vision model. It is widely used in many industries and its popularity is continuing to grow. In this video we will be deploying the YOLOv5 machine learning model and pass input images and videos into it. In the end we will be able to get output videos and images with object detection bounding boxes.
This follow-along tutorial is designed to help you quickly get YOLOv5 computer vision models deployed to your local computer for inference. Below you’ll be introduced to the OctoML CLI, a free command line utility that packages machine learning models into deployable Docker containers with NVIDIA Triton Inference Server. When you’re ready to deploy to production, OctoML CLI can also be used to accelerate and deploy YOLOv5 to over 100 instance types in AWS, Azure and GCP.
🔑 TIMESTAMPS
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00:00 - Intro
00:55 - Download Docker
03:52 - YOLOv5 Model
07:35 - OctoML CLI
11:26 - Recap
12:17 - Model Inference
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Watch video Machine Learning Object Detection Tutorial Using YOLO (Free) online without registration, duration hours minute second in high quality. This video was added by user Smitha Kolan - Machine Learning Engineer 02 November 2022, don't forget to share it with your friends and acquaintances, it has been viewed on our site 5,54 once and liked it 14 people.