Course Details
Industry Safety Detection using YOLO v7
Data Science
Created On
July 08, 2023Description
YOLO (You Only Look Once) is a real-time object detection algorithm that performs object localization and classification in a single pass. It divides the image into a grid and predicts bounding boxes and class probabilities for each grid cell.
Overview
Join our comprehensive course offering hands-on experience with real-time projects. Learn YOLO v7 for Industrial Safety and object detection, master data labeling, Docker workflow, modular coding, Flask app development, AWS basics, GitHub Actions for CICD, and deploying to production. Enhance your skills and excel in the field of computer vision and software development. Enroll now to unlock your potential.
Features
- Industry-Standard Lab Experience
- Flexible Learning Schedule
- Real-World Project Experience
- Learn at Your Own Pace
- Accessible Learning Dashboard
- Comprehensive Learning Resources
- Practical Application Tasks
What you'll learn
- Live Projects
- YOLO v7 for Industrial Safety
- YOLO v7-based Object Detection
- Labeling Data
- Docker Workflow
- Modular Training and Prediction Pipeline
- Flask Application Development
- Introduction to AWS
- Github Actions for CICD
- Deploying to Production
Prerequisites
Curriculum
- 27 modules
Introduction to YOLO v7
Course Objectives and Outcomes
Course Structure and Format
Understanding the Project Scope
Importance of Industrial Safety
Project Goals and Deliverables
Summary of the Industrial Safety Detection Project Key Achievements and Learnings
Defining the Industrial Safety Problem
Challenges in Industrial Safety
Why YOLO v7 for Industrial Safety?
Identifying Applicable Industries
Use Cases for YOLO v7 in Industrial Safety
Reviewing Existing Safety Solutions
Strengths and Weaknesses of Current Approaches
Introduction to YOLO v7 for Industrial Safety
Components of the YOLO v7 Solution
Hands-On Introduction to Notebooks
Exploring Data Preparation and Model Training
Understanding the System Architecture
Role of YOLO v7 in the Architecture
Budgeting for the Industrial Safety Project
Cost-Effective Model Deployment Strategies
Organizing Your Industrial Safety Project
Roles and Responsibilities
Data Sources and Collection Methods
Data Quality and Quantity Considerations
Ensuring Data Accuracy and Integrity
Data Preprocessing for YOLO v7
Training YOLO v7 for Object Detection
Fine-tuning for Industrial Safety Use Cases
Measuring Model Accuracy and Performance
Interpreting Evaluation Metrics
Deploying YOLO v7 Models in Real Environments
Monitoring and Maintenance
Step-by-Step Model Training
Optimization Techniques
Real-time Object Detection with YOLO v7
Handling Inference Outputs
Creating a User-Friendly Interface
Integrating YOLO v7 Results
Introduction to Cloud Services
AWS as a Hosting Platform
Identity and Access Management in AWS
Configuring Permissions
Using Amazon Elastic Container Registry
Storing and Managing Docker Images
Setting Up Amazon Elastic Compute Cloud (EC2) Instances
Configuring EC2 for the Project
Configuring a Self-hosted GitHub Runner
Enabling Continuous Integration
Containerization with Docker
Deploying YOLO v7 in Docker Containers
Summary of Key Project Achievements
Reflections on the Industrial Safety Detection Project
Supplementary Learning Materials
Assignments for Further Practice
Instructors
Skoliko Faculty
₹500.00
- 27 Modules
- 3h 5m 10s
- Data Science
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