TensorFlow.js Object Detection Made Easy

TensorFlow.js Object Detection Made Easy

Sascha Dittmann explains how to make Object Detection in TensorFlow.js

Contents:

  • 00:00 | Intro
  • 00:55 | Preview what I will build
  • 01:35 | Create a Custom Vision project
  • 03:01 | Upload & tag the images
  • 05:41 | Train the model
  • 06:30 | Evaluate / test the model
  • 07:42 | Export & download the model
  • 09:10 | A first look inside the web app
  • 10:32 | Integrate the model with TensorFlow.js
  • 15:45 | Check the results
  • 16:12 | Performance Optimizations
  • AI
  • Closed
  • 28 sec read

How I Read AI Papers

How I Read AI Papers

Yannic Kilcher retraces his first reading of Facebook AI’s DETR paper and explain my process of understanding it.

OUTLINE:

  • 0:00 – Introduction
  • 1:25 – Title
  • 4:10 – Authors
  • 5:55 – Affiliation
  • 7:40 – Abstract
  • 13:50 – Pictures
  • 20:30 – Introduction
  • 22:00 – Related Work
  • 24:00 – Model
  • 30:00 – Experiments
  • 41:50 – Conclusions & Abstract
  • 42:40 – Final Remarks

Original Video about DETR: https://youtu.be/T35ba_VXkMY

Learn OpenCV in 3 Hours with Python

Learn OpenCV in 3 Hours with Python

Here’s a great tutorial on how OpenCV.

Time Index:

  • Introduction to Images: 2:17
  • Installations: 4:37
  • Chapter 1: 9:09
  • Chapter 2: 17:01
  • Chapter 3: 27:31
  • Chapter 4: 34:12
  • Chapter 5: 44:59
  • Chapter 6: 50:04
  • Chapter 7: 56:14
  • Chapter 8: 1:15:37
  • Chapter 9: 1:40:31
  • Project 1: 1:46:03
  • Project 2: 2:15:45
  • Project 3: 2:56:34

Object Detection and Tracking

Object Detection and Tracking

Here’s an interesting computer vision project on GitHub.

This doc focuses on the below example graph that performs object detection and tracking. Note that object detection is using TensorFlow Lite on GPU while tracking is using CPU. For overall context on object detection and tracking, please read this Google Developers Blog . Android […]

How Computers Learn to Recognize Objects

How Computers Learn to Recognize Objects

Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible.

Today, computer vision systems do it with greater than 99 percent accuracy.

How?

Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can identify objects in images and video — from zebras to stop signs — with lightning-quick speed.

Watch this amazing live demo, where Redmon shows off this important step forward for applications like self-driving cars, robotics and even cancer detection.