https://github.com/arogozhnikov/iview5d
Extremely simplistic viewer of small ndimensional patches for jupyter notebook. Powered by einops
Science Score: 13.0%
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○Scientific vocabulary similarity
Low similarity (9.0%) to scientific vocabulary
Repository
Extremely simplistic viewer of small ndimensional patches for jupyter notebook. Powered by einops
Basic Info
- Host: GitHub
- Owner: arogozhnikov
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 41.1 MB
Statistics
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
iview5d (stack viewer)
Extremely simplistic viewer of small ndimensional patches for jupyter notebooks. Powered by einops transformation
Installation
Right from github
pip install git+https://git@github.com/arogozhnikov/iview5d.git
Usage (viewing)
- Move your cursor over the image - as you move a cursor, element of a stack that is shown, changes.
- Main usage - collect multiple parameters/layers, where 'side-to-side' is not an option
Usage (code)
First arument is tensor or list of tensors (from any framework) Second argument corresponds to einops transformation pattern.
Output should have 4 or 5 dimensions in the following order
- x-controllable (changed by moving a mouse over the image)
- y-controllable (changed by moving a mouse over the image)
- height
- width
- (optional) color
Code below outputs a viewer in jupyter:
python
from iview5d import iview5d
iview5d(
stack,
'batch z channel h w -> batch z h w channel',
zoom=0.5,
)
Axes will be used as: - batch -> move cursor along x - z -> move cursor along y - h w channel - shown image (at each position of cursor)
Video
See how it looks in action: video
Try it out (demonstration)
nbviewer link, move cursor over all images
Warning
No additional features are planned for this project, it is designed to be small and convenient. If you need fully-powered stack viewer - find a corresponding project
Owner
- Name: Alex Rogozhnikov
- Login: arogozhnikov
- Kind: user
- Location: San Francisco
- Company: Aperture Science
- Website: https://arogozhnikov.github.io
- Repositories: 9
- Profile: https://github.com/arogozhnikov
ML + Science, einops, scientific tools
GitHub Events
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Last Year
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Last synced: about 1 year ago
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- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
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Dependencies
- einops >=0.3
- matplotlib *
- numpy *
- pillow *