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Create an advanced object detection system with YOLOv7 and Python. Learn dataset preparation, model training, and real-time detection on images and video streams.
Intermediate-level. Certificate included.
Startups
Microsoft
NVIDIA
By the end of this course, you'll have the skills to land your first computer vision job or freelance clients.
Learn how AI identifies and locates multiple objects within images or video frames..
Use Python with OpenCV and object detection models like YOLO or SSD for accurate results.
Build a real-time system that detects and labels objects from a live webcam or CCTV feed.
Log detected objects, counts, and timestamps into a structured database for analysis.
Design an intuitive GUI to display live detections and object information.
Finish the course and receive a verified certificate of success.
Muhammad Yaqoob is the founder of Tentosoft Pvt Ltd and a seasoned Computer Vision expert. With 10+ years of experience and over 5,000+ students taught globally, he brings deep industry knowledge and a passion for practical, hands-on learning.
8 weeks of comprehensive training with 50+ lessons and 10+ hours of content
Object Detection introduces how computers can visually identify objects in images or video. YOLOv7 is a state-of-the-art algorithm built to detect these objects with high speed and accuracy.
Course Overview and Features
Detect objects in images/videos.
High speed and accuracy.
Use in CCTV and safety
Test and deploy models.
Setting up Python and its development tools is the foundation of building AI applications. This ensures the environment is ready to run and develop object detection models.
Installing Python
VS Code Setup for Python Development
This section outlines the project goals and use cases, helping you understand the real-world application and structure of the object detection solution.
Object Detection Project Overview
Learn real use cases
Focus on real scenarios
Build a practical system
This part introduces important Python libraries and files used to load and run object detection models efficiently, especially for YOLOv7.
Understanding Key Packages for Object Detection
Learn key Python libs
Process detections fast
Boost code efficiency
YOLOv7-tiny is a lightweight object detection model optimized for speed and performance on edge devices. This section explains the structure and purpose of the model's weight files, helping you understand how pre-trained knowledge is used to detect objects efficiently in real-time.
Detailed Explanation of the YOLOv7-tiny.pt File
Fast and lightweigh
Speed with good accuracy
You'll learn how to use YOLOv7 with live video input to detect objects instantly, simulating real-time surveillance or detection systems.
Implementing YOLOv7-tiny for Live Video Analysis
Detect from live videos
Fast and smooth results
Is This Course Right for You?
Kickstart your AI journey with structured, hands-on learning.
Build a portfolio that recuriters can't ignore.
Add powerful AI/CV features to your apps and software.
Upskill for higher-paying, future-ready tech roles.
Build Smarter, more intelligent applications.
Transition into AI even with zero background.
One-time payment for lifetime access to all course materials and updates
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Highly recommended for small teams who seek to upgrade their time & perform.
₹ 6720 inclusive of GST ₹ 13999
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This certificate is given to Jacqueline Thompson for her achievement in the field of education and proves that she is competent in her field.
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