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https://github.com/thebabylonai/babylog

A lightweight logger for machine learning teams to log images and predictions in production.

https://github.com/thebabylonai/babylog

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (17.3%) to scientific vocabulary

Keywords

computer-vision cvops data-science logger logging-library machine-learning ml mlops python python3
Last synced: 5 months ago · JSON representation

Repository

A lightweight logger for machine learning teams to log images and predictions in production.

Basic Info
  • Host: GitHub
  • Owner: thebabylonai
  • License: apache-2.0
  • Language: Python
  • Default Branch: master
  • Homepage: https://www.babylonai.dev
  • Size: 3.13 MB
Statistics
  • Stars: 152
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Topics
computer-vision cvops data-science logger logging-library machine-learning ml mlops python python3
Created about 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License

README.md

Welcome to Babylog

PyPI version pypi supported versions GitHub Super-Linter

Welcome to babylog, a Python library, designed to stream image and video data from edge devices to the cloud with ease. Babylog is maintained by BabylonAI, a Zurich-based YC-backed startup.

Check out the documentation here: https://babylonai.gitbook.io/babylog/

github_background

The primary goal of this library is to empower machine learning teams to log images and predictions, ensuring their computer vision models are working as intended. Without proper monitoring, small issues with a computer vision model can have dire consequences, such as a self-driving car incorrectly identifying a stop sign and causing an accident. Babylog aims to prevent such scenarios by providing the tools necessary for monitoring and debugging computer vision models.

Installation & requirements

Currently babylog only supports streaming the data to AWS. If you are using GCP or another provider please get in touch with us at founders@babylonai.dev and we'll make sure to add it into the development pipeline.

Supported python versions

The babylog Python library is compatible with Python version 3.8 and above. It is recommended to use the latest version of Python for best performance and stability. If you are using an older version of Python, you may need to upgrade your Python installation in order to use babylog. You can check your Python version by running the command python --version in your command prompt or terminal.

Installation

Like most python packages, run:

bash pip install babylog

Getting and configuring your AWS credentials

  • Open the IAM console at https://console.aws.amazon.com/iam/
  • On the navigation menu, choose Users.
  • Choose your IAM user name (not the check box).
  • Open the Security credentials tab, and then choose Create access key.
  • To see the new access key, choose Show. Your credentials resemble the following:
    • Access key ID: AKIAIOSFODNN7EXAMPLE
    • Secret access key: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY

Get your bucket name and region

You also need the name of your bucket and a slug of the region. Either create a new bucket or find the values for an existing bucket in your S3 console: https://s3.console.aws.amazon.com/s3/buckets

Screenshot 2023-01-28 at 12 42 30

Creating a config file

You can set your AWS credentials in a babylog.config.yaml file to use them with the babylog library. Here is an example of how you might structure the file:

yaml device: ip: 'DEVICE_IP' # device ip to be used for tcp streaming (e.g. '127.0.0.1') port: DEVICE_PORT # port number(int) for tcp streaming name: 'DEVICE_NAME' # device name (e.g. 'device-1b2a') group: 'GROUP_NAME' # group name (e.g. 'group-222X)' data: interval: 3000 # ms between captures max_workers: 4 # max number of threads to be used for logging S3_storage: aws_access_key_id: 'YOUR_ACCESS_KEY' aws_secret_access_key: 'YOUR_SECRET_KEY' bucket_name: 'YOUR_BUCKET_NAME' bucket_region: 'YOUR_BUCKET_REGION'

You can replace YOURACCESSKEY and YOURSECRETKEY with the actual values of your credentials. Currently you need one file per streaming device. If you want to add more granularity, please consider opening a github issue.

We recommend keeping the config files locally for security purposes. Consider adding the file to your .gitignore.

Owner

  • Name: BabylonAI, Inc.
  • Login: thebabylonai
  • Kind: organization
  • Email: founders@babylonai.dev
  • Location: Switzerland

Log image and prediction data from edge devices

GitHub Events

Total
Last Year

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 34
  • Total Committers: 3
  • Avg Commits per committer: 11.333
  • Development Distribution Score (DDS): 0.324
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Ahmad Roumie 4****7 23
Rangel Milushev 1****k 9
aroumie1997 a****e@s****h 2
Committer Domains (Top 20 + Academic)
student.ethz.ch: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 0
  • Total pull requests: 19
  • Average time to close issues: N/A
  • Average time to close pull requests: about 2 hours
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 16
  • 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
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • rangelak (11)
  • aroumie1997 (8)
Top Labels
Issue Labels
Pull Request Labels
enhancement (4) documentation (3) test (2) cleanup (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 18 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 6
  • Total maintainers: 1
pypi.org: babylog

A lightweight library for logging image and prediction data for your ML and computer vision models in production.

  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 18 Last month
Rankings
Stargazers count: 5.9%
Dependent packages count: 6.6%
Average: 19.5%
Downloads: 23.8%
Forks count: 30.5%
Dependent repos count: 30.6%
Maintainers (1)
babylonai
Last synced: 6 months ago

Dependencies

.github/workflows/linter.yml actions
  • actions/checkout v3 composite
  • github/super-linter v4 composite
.github/workflows/python-publish.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
  • pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
.github/workflows/run-python-tests.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
python/dev-requirements.txt pypi
  • freezegun * development
  • pytest * development
python/pyproject.toml pypi
  • PyYAML ==6.0
  • boto3 ==1.15.3
  • numpy ==1.24.1
  • opencv-python ==4.7.0.68
  • protobuf ==4.21.12
  • zmq ==0.0.0
python/requirements.txt pypi
  • PyYAML ==6.0
  • boto3 ==1.15.3
  • numpy ==1.24.1
  • opencv-python ==4.7.0.68
  • protobuf ==4.21.12
  • zmq ==0.0.0