Yolov7 Object Detection Course
Published 9/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.55 GB | Duration: 2h 40m
YOLOv7 Object Detection Inference & Training

What you'll learn
Fundamentals of YOLOv7
Training YOLOv7 in Custom Dataset
Deploying&Testing the Model in YOLOv7
Data Processing, Segmentation, Data Collection, and Essential Prerequisites in YOLOv7
Requirements
Python Programming Basics
OpenCV Programming
Description
Object-detection technology is widely used as the backend of many applications in the industry, including desktop and web applications. Also, it's a backbone for many computer vision tasks, which include object segmentation, object tracking, object classification, object counting, etc. The YOLO (You Only Look Once) model is a single-stage object detector. Image frames are featured through a backbone, features are combined and mixed in the neck, and then they are passed along to the head of the network where YOLO predicts the bounding box locations, the classes of the bounding boxes, and the objectness of the bounding boxes. With its amazing characteristics, YOLOv7 is a real-time object detector that is now transforming computer vision.In comparison to its earlier iterations, the official YOLOv7 offers incredible speed and precision. YOLOv7 weights are trained without pre-trained weights using the COCO dataset from Microsoft. With this full-stack object detection course, you will learn to code YOLOv7 from the basics, training your custom YOLOv7, multi-object tracking system, Flask integrations, various segmentation, and object detection feature to its most practical applications. You will also have access to the most delicate details of this state-of-the-art system.In this course, we will share the first two modules of our full-stack course. Module 1 - Getting Started with YOLOv7Module 2 - Training YOLOv7 on Custom Dataset This course is highly recommended to anyone interested in computer vision!
Overview
Section 1: Module 1 - Introduction to YOLOv7
Lecture 1 Lecture 1.1 Introduction to YOLOv7
Lecture 2 Lecture 1.2 YOLOv7 Research Paper
Lecture 3 Lecture 1.3 Run YOLOv7 on Ubuntu
Lecture 4 Lecture 1.4 Run YOLOv7 on Windows 10/11
Lecture 5 Lecture 1.5.1 YOLOv7 Object Detection on Images, Video & WebCam in Google Colab
Lecture 6 Lecture 1.5.2 Training YOLOv7 in Colab
Section 2: Module 2 - Training Custom YOLOv7
Lecture 7 Lecture 2.1 Training Process of YOLOv7
Lecture 8 Lecture 2.2.1 Custom Dataset PPE Detection part 1
Lecture 9 Lecture 2.2.2 Custom Dataset PPE Detection part 2
Lecture 10 Lecture 2.3.1 Data Collection Part 1
Lecture 11 Lecture 2.3.2 Data Collection Part 2
Lecture 12 Lecture 2.3.3 Data Collection Part 3
Lecture 13 Lecture 2.4 Data Annotation
Lecture 14 Lecture 2.5 Dataset Bias & Health
Lecture 15 Lecture 2.6 Data Pre-processing
Lecture 16 Lecture 2.7 Data Augmentation
Lecture 17 Lecture 2.8.1 Roboflow Train Part 1
Lecture 18 Lecture 2.8.2 Roboflow Train Part 2
Lecture 19 Lecture 2.9 Tuning Training Parameters
Lecture 20 Lecture 2.10 Deploy the Model
Lecture 21 Lecture 2.11 Testing the Model
Lecture 22 Bonus Lecture - Continue Learning YOLOv7
Everyone who is interested in Computer Vision or Machine Learning.,Want to learn the latest YOLO version,Build Deep learning App with Computer Vision
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