https://github.com/humansignal/smartfew

SmartFew is your swiss knife for semi-supervised structuring of unlabeled data using Few Shot Learning.
https://github.com/humansignal/smartfew

few-shot few-shot-learning few-shot-recognition machine-learning meta-learning one-shot-learning one-shot-segmentation zero-shot zero-shot-learing zero-shot-learning

Last synced: about 1 year ago
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SmartFew is your swiss knife for semi-supervised structuring of unlabeled data using Few Shot Learning.

• Host: GitHub
• URL: https://github.com/humansignal/smartfew
• Owner: HumanSignal
• Created: 2019-10-21T12:33:54.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-05-22T22:31:01.000Z (about 3 years ago)
• Last Synced: 2023-07-25T05:23:51.460Z (almost 3 years ago)
• Topics: few-shot, few-shot-learning, few-shot-recognition, machine-learning, meta-learning, one-shot-learning, one-shot-segmentation, zero-shot, zero-shot-learing, zero-shot-learning
• Language: Python
• Homepage:
• Size: 1.88 MB
• Stars: 3
• Watchers: 7
• Forks: 3
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

          
# SmartFew

SmartFew is your swiss knife for semi-supervised structuring of unlabeled data. 

#### Install

```bash

pip3 install -e .

```

#### How it works:

1. Prepare the file with image URLs _image_urls.txt_, e.g.

    ```text

    https://myhost.com/image1.jpg

    https://myhost.com/image2.jpg

    ...

    ```

2. Run server

    ```bash

    cd server && python start.py --input image_urls.txt

    ```

3. Go to `http://localhost:14321/` in your browser and start selecting relevant images. 

![Image selection process](https://data.heartex.net/misc/images/static/smartfew-min.png)

Then press **Submit** to continue with a new trial.

The underlying process starts to learn your selection, and you are expecting to see more and more relevant results in your consequent trials.

The algorithm is powered by [Few Shot learning](https://msiam.github.io/Few-Shot-Learning/), that gives an opportunity to learn very fast and quickly adapts to unseen tasks.