Metadata-Version: 2.1
Name: deepsea-ai
Version: 1.2.0
Summary: DeepSeaAI is a Python package to simplify processing deep sea video in AWS from a command line.
Home-page: https://github.com/mbari-org/deepsea-ai
License: GPL3
Author: Danelle Cline
Author-email: dcline@mbari.org
Requires-Python: >=3.8,<4.0
Classifier: Development Status :: 1 - Planning
Classifier: Environment :: Console
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Dist: awscli (>=1.25.71,<2.0.0)
Requires-Dist: boto3 (>=1.24.70,<2.0.0)
Requires-Dist: click (>=8.1.3,<9.0.0)
Requires-Dist: requests (>=2.26.0,<3.0.0)
Requires-Dist: sagemaker (>=2.102.0,<3.0.0)
Requires-Dist: tqdm (>=4.41.0,<5.0.0)
Project-URL: Repository, https://github.com/mbari-org/deepsea-ai
Description-Content-Type: text/markdown

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[![semantic-release](https://img.shields.io/badge/%20%20%F0%9F%93%A6%F0%9F%9A%80-semantic--release-e10079.svg)](https://github.com/semantic-release/semantic-release)
![license-GPL](https://img.shields.io/badge/license-GPL-blue)
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DeepSea-AI is a Python package to simplify processing deep sea video in [AWS](https://aws.amazon.com) 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](http://github.com/ultralytics/yolov5) object detection models*
 - *Running [YOLOv5](http://github.com/ultralytics/yolov5) detection and tracking pipelines* on video using either:
   - [DeepSort](https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch)
   - [StrongSort](https://github.com/mikel-brostrom/Yolov5_StrongSORT_OSNet) 
 

**Authors**: Danelle Cline, [dcline@mbari.org](mailto:dcline@mbari.org), Duane Edgington, [duane@mbari.org](mailto:duane@mbari.org)

----
 
## Requirements
 
* [An AWS account](https://aws.amazon.com)
* [Python 3.8 or later](https://python.org/downloads/) 


**After you have setup your AWS account, confirm your AWS Account by listing your s3 buckets**

```
$ aws --version
$ aws s3 ls 
```

## Installing

Install and update using [pip](https://pip.pypa.io/en/stable/getting-started/):

```shell
$ pip install -U deepsea-ai
```

For more details, see the [official documentation](http://docs.mbari.org/deepsea-ai/install).

----


## Commands

* [`deepsea-ai train --help` - Train a YOLOv5 model and save the model to a bucket](https://docs.mbari.org/deepsea-ai/commands/train/)
* [`deepsea-ai process --help` - Process one or more videos and save the results to  a bucket](https://docs.mbari.org/deepsea-ai/commands/process/)
* [`deepsea-ai ecsprocess --help` - Process one or more videos using the Elastic Container Service and save the results to  a bucket](https://docs.mbari.org/deepsea-ai/commands/process/)
* [`deepsea-ai split --help` - Split your training data; required before the train command.](https://docs.mbari.org/deepsea-ai/data/) 
* `deepsea-ai -h` - Print help message and exit.
