Workshop Python Image Analysis
To read beforehand
See about, goals, setting up & introduction for course topics, philosophy and goals.
Afternoon I (the basics)
- About, goals, setting up & introduction
- Working with images
- Reading, modifying and displaying images
- How computers represent numbers
- Topics
- Reading/writing/displaying images
- Images are tables with values (arrays)
- Working with arrays
- Data types
- Relating pixels to real-world units
- Topics
- Image Processing
Afternoon II (dive into image processing methods)
- Image processing (continued)
- Image Processing (part 2)
- Topics
- Applying math to images
- Segmentation of images
- Masks, labels and regions
- Convolutions
- Morphology operations
- Topics
- Image Processing (part 2)
Afternoon III (bringing it all together)
- Good coding practices
- Topics
- Importance of readable code
- Style guides
- Modularity
- Refactoring
- Not included:
- using version trackers
- online repositories (github)
- environment managers
- Topics
- Combining building blocks into a pipeline
- See also:
- Topics
- Working with (large) image sets
- How to set up a pipeline
- Image processing (part 3):
- Background correction
- Human-in-the loop, Napari package
- Machine learning fundamentals (basics)
- Topics
- Machine learning fundamentals;
- Neural networks
- Forward propagation
- Loss function, training, weights
- Some basic Pytorch concepts
- Not included:
- Activation functions
- Neural network architectures
- Machine learning fundamentals;
- Topics
- Appendix, tools & remarks
- Topics
- List of tools that might be convenient
- Topics
