Price:4.00 USD | Size: 4.07 GB | Duration : 4.40 + Hours | ★★★★★  4.5 
 
Complete package of YOLOv4 specialized course
 
Modules
001-Introduction
002-How to Excel in this Course
003-YOLOv4 Theory
004-Installation of YOLOv4 Dependencies such as CUDA Python OpenCV
005-YOLOv4 Object Detection on Image and Video
006-YOLOv4 Darknet Explanation with Code and Webcam Implementation
007-Social Distancing Monitoring App
008-Social Distancing Monitoring Coaching Session
009-Count Parked Cars
010-DeepSORT Intuition How DeepSORT Object Tracking Works
011-Robust Tracking with YOLOv4 and DeepSORT
012-Evolution of YOLOv1 to YOLOv3
013-YOLOv5 Chess Piece Detection
014-Bernie Sanders Detector
015-Introduction to Data Annotation
016-YOLOv4 Format for Image Labelling
017-YOLOv4 Labelling Tools
018-Web Scaping Data
019-Annotating Images with LabelImg
020-Labelling on Video Using LabelImg
021-Labelling on Video Using Darklabel
022-Label Objects on this Video
023-Annotation Summary
024-Data Annotation Key Takeaway
025-Introduction How to Create Custom Dataset
026-Toolkit for Downloading Image Datasets
027-Downloading Images from Specific Classes
028-Converting Downloaded Files to YOLOv4 format
029-Data Augmentation Using Rotational Transform
030-Summary Key Takeaways for Custom Datasets
031-Introduction to Training YOLOV4 with Darknet Framework
032-Step 1 Configuring the Files for Training
033-Step 2 Creating the obj names File
034-Step 3 Dataset Placement for Training
035-Step 4 Train Test Metafiles
036-Step 5 Training YOLOv4
037-Trained YOLOv4 Execution on Image and Video for Mask Detection
038-Activity Train on Your Own Dataset
039-When to Stop Training
040-Summary Key Takeaways
041-Introduction to Object Detection with PyQt
042-Installing PyQt
043-GUI Layout Using PyQt Designer
044-Integrating PyQt with YOLOv4
045-Code Explanation
046-Adding GUI Widgets Counting Objects
047-Adding Widgets Slider Threshold
048-Adding Widgets Class Filter Using Checkbox Widget
049-Adding Widgets Real Time Live Plot Graph Widget
050-Social Distancing in PyQt Activity
051-Conclusion