YOLO Object Detection | YoloV1 Explanation and Implementation Tutorial
This video is on YOLO object detection, specifically yolov1 object detection algorithm.
In this tutorial we try to understand how the YOLO algorithm works, from its real-time object detection capabilities to its approach of bounding box predictions. We will also go through YOLOv1 implementation from scratch in PyTorch. By the end of this video you would be able to get a complete explanation of YOLOv1 paper, how Yolo algorithm works, different parts of multi part loss used for training yolo and and how to train and implement YOLOv1 for object detection.
⏱️ Timestamps:
00:00 Intro
00:37 One Stage vs Two Stage Object Detection
02:05 Yolo Object Detection Algorithm
04:09 Yolo Bounding Box Prediction
06:22 Grid Cell Predictions
09:43 Yolo Architecture Explained
12:25 Yolo Algorithm Loss Function
22:08 Defining Targets for Yolo Predictions
25:06 Yolo Training Summary
27:37 Yolov1 Implementation from Scratch
35:27 Yolov1 Model Implementation
37:53 Yolo Object Detection Loss Implementation
47:02 Yolov1 Training and Inference Code
49:53 Yolo Object Detection Results
📖 Resources:
Yolo Paper - https://tinyurl.com/exai-yolov1-paper
Github Implementation Link - https://tinyurl.com/exai-yolov1-imple...
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