Explanation
YOLOv3 – Challenging Deep Learning Object Recognition In 1 Hour, Learn How We Implemented YOLO V3 Deep Learning Object Recognition Patterns From Training to Intervention – Step-by-Step. When we first started with deep learning specifically in computer vision, we were really excited about the potential of this technology to help people. The only problem is that if you are just starting to learn about AI Object Recognition, you may encounter some of the following challenges: Label printing is very difficult and complicated, Editing styles between types The variety of the product is very different. Signals may be corrupted by free detailed tools, Unclear instructions on how to train the models – causes a lot of time loss during trial and error. Duplicate images are a headache to manage.
This got us looking for a better way to manage the object detection workflow, that would not only help us better manage the object detection process but also improve our time to market. So as you can see, the features mentioned above can save you a lot of time. In this course, I will show you how to use the workflow by training your custom YoloV3 as well as how to deploy your models using PyTorch. So basically, we’ve designed this training to reduce red tape, speed up your time to market and get you faster results.
What will you learn?
- Learn the State of the Art in Object Detection using Yolo V3.
- Discover an object detection workflow that saves you time and money.
- The fastest way to collect and describe images for your database.
- A secret tip for boosting your data using Data Extensions.
- How to use AI to mark your data for you.
- Find out how to train your custom YoloV3 from scratch.
- Step-by-step instructions on how to Implement, Detail, Train and Enter Custom Yolo V3 models.
Who is this course for?
- This course is designed for students with Python, opencv or AI experience who want to learn how to do object detection in Yolo V3.
- For those who do not need or already have a theoretical understanding of Object Detection, CNN’s and Yolo Architecture.
- For those who are looking for the only effective way to find out about things with Yolo V3.
Specificatoin of YOLOv3 – Complex Deep Learning Object Detection in 1 hour
- Publisher: Udemy
- Teacher: Extended startup
- Language : English
- Level: Medium
- Number of courses: 20
- Duration: 2 hours and 18 minutes
YOLOv3 Content – Deep Learning Object Recognition in 1 hour
Requirements
- Previous experience with Python using Anaconda.
- PC/Laptop with CUDA-capable NVIDIA graphics card for training – We use Ubuntu for training.
- Create a free account with Monitor.
- Learn Computer Theory or AI.
Pictures
Sample Clip
Installation Guide
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Subtitle : English
Quality: 720p
Download Links
Password file: free download software
file size
2.21 GB