In this video you’ll learn how to do just that. We’ll take a pre-trained deep learning Tensorflow Object Detection Model and store the detections that are made so they can be referenced in the future. You’ll be able to leverage previously written detection code and can begin to save the history with just a few Python tweaks.
In this video, you’ll learn :
- Capture detection history from a real time object detection model
- How Tensorflow Object Detection scores are captured and transformed
- How to display detection history per frame to the screen
Chapters:
0:00 - Start
1:25 - Getting the Starter Code
2:45 - Testing Baseline Code Detections
3:38 - Importing New Dependencies
4:04 - Setting Up a History Array
4:35 - Understanding Detections
6:20 - Capturing Detection History
7:10 - Testing the Final Python Code
8:09 - Understanding Tensorflow Object Detection Scores
Get the code: https://youtu.be/ZTSRZt04JkY
Subscribe:https://www.youtube.com/channel/UCHXa4OpASJEwrHrLeIzw7Yg
#tensorflow #python
