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- Evaluating OD Models using Tensorboard
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Classroom Contents
Tensorflow Object Detection with Python - Full Course with 3 Projects
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- 1 - Start
- 2 - SECTION 1: Installation and Setup
- 3 - Cloning the Baseline Code from GitHub
- 4 - Creating a Virtual Environment
- 5 - SECTION 2: Collecting Images and Labelling
- 6 - Collecting Images Using Your Webcam
- 7 - Labelling Images for Object Detection using LabelImg
- 8 - SECTION 3: Training Tensorflow Object Detection Models
- 9 - Tensorflow Model Zoo
- 10 - Installing Tensorflow Object Detection for Python
- 11 - Installing CUDA and cuDNN
- 12 - Using Tensorflow Model Zoo models
- 13 - Creating and Updating a Label Map
- 14 - Creating TF Records
- 15 - Training Tensorflow Object Detection Models for Python
- 16 - Evaluating OD Models Precision and Recall
- 17 - Evaluating OD Models using Tensorboard
- 18 - SECTION 4: Detecting Objects from Images and Webcams
- 19 - Detecting Objects in Images
- 20 - Detecting Objects in Real Time using a Webcam
- 21 - SECTION 5: Freezing TFOD and Converting to TFJS and TFLite
- 22 - Freezing the Tensorflow Graph
- 23 - Converting Object Detection Models to Tensorflow Js
- 24 - Converting Object Detection Models to TFLite
- 25 - SECTION 6: Performance Tuning to Improve Precision and Recall
- 26 - SECTION 7: Training Object Detection Models on Colab
- 27 - SECTION 8: Object Detection Projects with Python
- 28 - Project 1: Detecting Object Defects with a Microscope
- 29 - Project 2: Web Direction Detection using Tensorflow JS
- 30 - Project 3: Sentiment Detection on a Raspberry Pi Using TFLite
