Deep learning for image segmentation using Tensorflow 2
Train and evaluate Mask RCNN instance segmentation model | Train locally and on google ai platform for custom datasets
Bullstrack
Deep learning for image segmentation using Tensorflow 2 udemy course
Train and evaluate Mask RCNN instance segmentation model | Train locally and on google ai platform for custom datasets
What you'll learn:
Mastering Image Segmentation with PyTorch
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implement multi-class semantic segmentation with PyTorch on a real-world dataset
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get familiar with different architectures like UNet, FPN
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understand the theoretical background, e.g. on upsampling, loss functions, evaluation metrics
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perform data preparation to reshape inputs to the appropriate format
Requirements:
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Basic Python knowledge
Description:
This course is about using deep learning to perform image segmentation with Tensorflow 2. It will show you a step by step guide on how to build powerful deep learning driven image segmentation tasks in computer vision.
The course will show you how to use Mask RCNN deep learning model in order to perform image segmentation. Mask RCNN is one of the widely used neural networks for image segmentation tasks.
The course will help you answer these questions:
1/ What is image segmentation?
2/ What are the different types of segmentation in computer vision?
3/ How do you prepare a custom dataset for training Mask RCNN model?
4/ What tools are used for annotating a dataset for image segmentation?
5/ How do you transform your images and annotations to tfrecords format?
6/ How do you use Tensorflow 2 object detection API for training Mask RCNN model?
7/ How do you use Tensorflow 2 object detection API for evaluating Mask RCNN model?
8/ How to run the training of Mask RCNN model on your local machine?
9/ How to create an account on google cloud platform (GCP)
10/ How to setup a project on google cloud platform (GCP)
11/ How to run the training of Mask RCNN model on google ai platform?
12/ How do you export a SavedModel from your training checkpoints?
13/ How do you use your SavedModel to perform image segmentation on new images?
14/ How do you use Mask RCNN to build a powerful image segmentation model for segmenting different parts of a damaged car (door, hood, lamps, ...). Which is by the way the course project!
And a lot more!
My strategy with this course is to enable you to build powerful AI solutions for image segmentation in computer vision.
Who this course is for:
- Students
- DIY makers
- AI Hobbyists
- Machine learning enthusiats
- Machine learning engineers
- Computer vision enthusiasts
- Computer vision engineers
- Data scientists
- Master in python programming language(Zero to hero)
- Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4
- TypeScript from Scratch: Go from zero to hero in TypeScript
- Google Sheets for Data Analysis and Workflow Automation
Course Details:
- 4.5 hours on-demand video
- 1 article
- 2 downloadable resources
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Deep learning for image segmentation using Tensorflow 2 udemy free download
Train and evaluate Mask RCNN instance segmentation model | Train locally and on google ai platform for custom datasets
Demo Link: https://www.udemy.com/course/deep-learning-for-image-segmentation-using-tensorflow-2/
