deepsea-ai 1.8.2

DeepSeaAI is a Python package to simplify processing deep sea video in AWS from a command line.

DeepSeaAI is a Python package to simplify processing deep sea video in AWS from a command line.

It includes reasonable defaults that have been optimized for deep sea video. The goal is to simplify running these algorithms in AWS.

DeepSea-AI currently supports:

• Training YOLOv5 object detection models
• Processing video with YOLOv5 detection and tracking pipelines using either:
  • DeepSort tracking
  • StrongSort tracking

Install

Setup an AWS account.

After you have setup your AWS account, configure it using the awscli tool, and confirm your AWS Account by listing your s3 buckets

pip install awscli
aws configure
aws --version
aws s3 ls 

Install and update using pip in a Python>=3.8.0 environment:

pip install -U deepsea-ai

Setup your AWS account for use with this module with

deepsea-ai setup

Tutorials

• FathomNet ✨ Recommended first step to learn more about how to train a YOLOv5 object detection model using freely available FathomNet data

The best way to use the tutorials is with Anaconda.

Create the Anaconda environment

This will create an environment called deepsea-ai-notebooks and make that available in your local jupyter notebook as the kernel named deepsea-ai-notebooks

conda env create 
conda activate deepsea-ai-notebooks
pip install ipykernel
python -m ipykernel install --user --name=deepsea-ai-notebooks

Launch jupyter

cd docs/notebooks
jupyter notebook

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Commands

• deepsea-ai setup --help - Setup the AWS environment. Must run this once before any other commands.
• deepsea-ai train --help - Train a YOLOv5 model and save the model to a bucket
• deepsea-ai process --help - Process one or more videos and save the results to a bucket
• deepsea-ai ecsprocess --help - Process one or more videos using the Elastic Container Service and save the results to a bucket
• deepsea-ai split --help - Split your training data. This is required before the train command.
• deepsea-ai -h - Print help message and exit.

Source code is available at github.com/mbari-org/deepsea-ai.

For more details, see the official documentation.