Object Classification

Trying to figure out how to detect objects in images and video streams.

I wanted to create a service that if given an image OR capuring frames from a video stream our system would be able to detect material objects and/or people. After research I fell into a couple of python libraries that would help me achieve the system's goal:

• cvlib cvlib is a simple, high level, easy to use, open source Computer Vision library for Python.
• opencv-python Unofficial pre-built CPU-only OpenCV packages for Python.
• TensorFlow An end-to-end open source machine learning platform
• Keras Deep learning for humans.

... and look into https://www.tensorflow.org/hub/tutorials/tf2_image_retraining

BUT the biggest find I've made to leading to a solution is COCO (Common Objects in Context)

Features

• All I know is that I've fully typed with annotations and checked with mypy, PEP561 compatible

Installation

Using my machine's Conda Environment I've Included in our repository is our "environment.yml" With this file in the repository, you can create the new environment by running:

conda env create
source activate objects

Example

Showcasing how the project can be used:

# Still work in Progress

Todo Checklist

A helpful checklist to gauge how your README is coming on what I would like to finish:

• Double check that the model I found actually works.
• Use click cli to walk through images in a folder. Click Blog
• Use marshmallow so I don't have to write lots of checking code when passing around data state.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT