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Udemy - YOLOv8 Object Detection for Number Plate Recognition

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Udemy - YOLOv8 Object Detection for Number Plate Recognition (Size: 1.5 GB)
  1. Advancements in Object Detection.mp4 8.8 MB
  1. Choose a Model.mp4 16.7 MB
  1. Conclusion.mp4 27.7 MB
  1. Creating a New Streamlit App.mp4 21 MB
  1. Install Miniconda.mp4 22.8 MB
  1. Introduction.mp4 6.5 MB
  1. Number Plate Detection in Images.mp4 225.5 MB
  1. Number Plate Recognition in Images.mp4 194.1 MB
  1. What is Object Detection.mp4 18.7 MB
  1. What is YOLO.mp4 7.1 MB
  1.1 Source Code.html 102.4 B
  2. Adding Upload Feature.mp4 51.8 MB
  2. Gathering the Data.mp4 72.2 MB
  2. How YOLO works.mp4 15.9 MB
  2. Install the Required Packages.mp4 23.3 MB
  2. Number Plate Detection in Videos.mp4 80.5 MB
  2. Number Plate Recognition in Videos.mp4 51.8 MB
  2. Start Training.mp4 80.3 MB
  2.1 Source Code.html 102.4 B
  3. Install CUDA and cuDNN for GPU support.mp4 50.2 MB
  3. Integrating our Number Plate Recognition System with Streamlit.mp4 123.8 MB
  3. Labeling the Data.mp4 83.7 MB
  3. YOLO Architecture.mp4 2.6 MB
  3.1 Source Code.html 102.4 B
  4. Project Structure.mp4 34.6 MB
  4. Splitting the Data.mp4 195.3 MB
  4. YOLO Versions.mp4 17.7 MB
  4.1 Source Code.html 102.4 B
  5. Creating the YAML File.mp4 26.2 MB
  5.1 Source Code.html 102.4 B
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 53 total files

Description


YOLOv8 Object Detection for Number Plate Recognition

https://DevCourseWeb.com

Published 2/2024
Created by Yacine Rouizi
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 26 Lectures ( 2h 50m ) | Size: 1.5 GB

Collect and Label Data, Train YOLOv8 Model, Implement OCR to Recognize Text, Integrate with a Streamlit Web App

What you'll learn:
Set up your environment for object detection
Learn how to recognize number plates in images and videos using OCR
Collect and label a custom dataset for training the YOLOv8 model
Integrating the number plate recognition system with a Streamlit web application
Train the YOLOv8 model and learn how to use it to detect number plates in images and videos

Requirements:
Basic knowledge of Python programming, OpenCV, and computer vision.