spaceml-org / active-labeler Goto Github PK

Section 1: Active Labeler

• The first line in quotes, it has no context. If it's supposed to be a tagline, put it in a separate sentence to make that evident. Something even better would be to have it as a part of the image (at the bottom of it).
• Involve Ricardo to check if we can improve the color scheme of the image and the text.
• Get rid of the title that is separately mentioned at the top of the README. (match the other repos like Image Similarity Search or Chrome extension).
• Check the other repos for formats to include the "Published by" line and the buttons.

Section 2: What is Active Learning?

• Since the topic talks about explaining the concept, spend a couple more lines on explaining what active learning is and why we need it rather than directly jumping into the strategies.
• Graphs or images highlighting the data being picked can be included for the different strategies but I don't feel too strongly about it. But some links can be referred to each strategy for introduction or wiki pages.

Section 4: Setup

• For the directory structure, this can be used:

Dataset/
└── Unlabeled
    ├── Image1.png
    ├── Image2.png
    └── Image3.png

The tree command in linux gives this kind of output.

Section 5: How to use

• Include a question mark at the end of the title.
• Include the colab hyperlink as a button as well on top.

Section 6: Mandatory Arguments

• In the first line, instead of "main pipeline", write "main.py file".
• If possible, include a diagram highlighting what exactly is "Pipeline" in "Pipeline config" and what is model training in "Model config".
• Also include hyperlinks to the pipeline_config.yml and model_config.yaml either in the title or in the first line of each sub-section.
• Stick to a single extension format. Either yaml or yml.
• Consider getting rid of -- from each parameter because that is not how the parameters are fed into the config files.
• There are some spelling errors. Just go over it once again.

Section 7: Where can I find the trained model?

• I couldn't find where the path to model is specified. Just check the reference once again.

Section 8: Citation

• The author section is missing. (keeping consistent with the other repos)

Hello, thank you for open-sourcing this project. I would like to suggest adding the following method to the library:
"Similarity Search for Efficient Active Learning and Search of Rare Concepts" Link: https://arxiv.org/abs/2007.00077
It seems that it can it well in this library, it is also possible to combine that with other methods. Sincerely, Kamer

• Update .gitignore to follow the python template.
• Update requirements.txt using the following command within your virtual env:
  conda env export requirements.txt
  Would be better to create a new virtual environment for this so that unnecessary packages are not included in the requirements.txt files.
  Make sure to include the commented dali requirements for CUDA10 and CUDA11 after regenerating the requirements.txt as it will be overwritten.

--- EDIT ---

• for .gitignore use this link instead.

All points correspond to Active-Labeler/ActiveLabeler-main/tsne.py:

• The documentation format is not consistent with the other files.
• Get rid of unused imports, if any.
• There is a big chunk of commented code in the beginning. That can be removed if not necessary.