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MBARI Python

aipipeline is a library for running ai pipelines and monitoring the performance of the pipelines, e.g. accuracy, precision, recall, F1 score. This may include object detection, clustering, classification, and vector search algorithms. It is designed to be used for a number of projects at MBARI that require advanced workflows to process large amounts of images or video. After workflows are developed, they may be moved to the project repositories for production use. The roadmap includes adding the core functionality of some of the processing components to more broad use in the MBARI AI ecosystem.

See the MBARI Internal AI documentation for more information on the tools and services used in the pipelines.


Example plots from the t-SNE, confusion matrix and accuracy analysis of examplar data.

example tsne plots example cm_ac


Requirements

Three tools are required to run the code in this repository:

Anaconda environment

This is a package manager for python. We recommend using the Miniconda version of Anaconda. Install on Mac OS X with the following command:

brew install miniconda

or on Ubuntu with the following command:

sudo apt install miniconda

This is a containerization tool that allows you to run code in a container.

just tool.

This is a handy tool for running scripts in the project. This is easier to use than make and more clean than bash scripts. Try it out!

Install on Mac OS X with the following command:

port install just

or on Ubuntu with the following command:

sudo apt install just

Installation

Clone the repository and run the setup command.

git clone http://github.com/mbari-org/aipipeline.git
cd aipipeline
just setup

Sensitive information is stored in a .env file in the root directory of the project, so you need to create a .env file with the following contents in the root directory of the project:

TATOR_TOKEN=your_api_token
REDIS_PASSWORD=your_redis_password
ENVIRONMENT=testing or production

Usage

Recipes are available to run the pipelines. To see the available recipes, run the following command:

just list
Command Description
list List recipes
install Setup the environment
cp-env Copy the default .env file to the project
update_trackers Update the environment. Run this command after checking out any code changes
update-env Update environment
cp-core Copy core dev code to the project on doris
cp-dev-cfe Copy cfe dev code to the project on doris
cp-dev-ptvr Copy planktivore dev code to the project on doris
cp-dev-uav Copy uav dev code to the project on doris
cp-dev-bio Copy bio dev code to the project on doris
cp-dev-i2map Copy i2map dev code to the project on doris
init-labels project='uav' leaf_type_id='19' Initialize labels for quick lookup, e.g. just init-labels uav 19
plot-tsne-vss project='uav' Generate a tsne plot of the VSS database
optimize-vss project='uav' *more_args="" Optimize the VSS database
calc-acc-vss project='uav' Calculate the accuracy of the VSS database; run after download, then optimize
reset-vss-all Reset the VSS database, removing all data. Proceed with caution!!
reset-vss project='uav' Reset the VSS database, removing all data
remove-vss project='uav' *more_args="" Remove an entry from the VSS database
init-vss project='uav' *more_args="" Initialize the VSS database for a project
load-vss project='uav' Load already computed exemplars into the VSS database
load-cfe-isiis-videos missions="" Load cfe ISII mission videos
cluster-cfe-isiis-frames roi_dir=... Cluster CFE ISIIS hawaii mission frames
load-ptvr-images images='tmp/roi' *args="" Load planktivore ROI images
cluster-ptvr-images *more_args="" Cluster planktivore ROI images
load-ptvr-clusters clusters='tmp/...' *args="" Load planktivore ROI clusters
rescale-ifcb-images collection="2014" Rescale planktivore ROI images
rescale-ptvr-images collection="..." Rescale planktivore ROI images
download-rescale-ptvr-images collection="..." Download and rescale planktivore ROI images
cluster-uav *more_args="" Cluster mission in UAV project
detect-uav *more_args="" Detect mission in UAV project
detect-uav-test Detect mission data for testing
load-uav-images Load UAV mission images
load-uav type="cluster" Load UAV detections/clusters
fix-uav-metadata Fix UAV metadata lat/lon/alt
compute-saliency project='uav' *args="" Compute saliency for downloaded VOC data
crop project='uav' *more_args="" Crop detections from VOC formatted downloads
download-crop project='uav' *more_args="" Download and crop with defaults
download project='uav' Download only
cluster project='uav' *more_args="" Cluster only
predict-vss project='uav' image_dir=... Predict images using the VSS database
run-ctenoA-prod Run strided inference on videos in TSV file
run-mega-inference Run mega strided inference on single video
run-mega-stride-bio video=... Run mega strided pipeline for bio project
run-mega-track-bio video=... Run mega strided tracking pipeline for bio project
run-mega-stride-i2map video=... Run mega strided pipeline for i2map
run-mega-track-i2map video=... Run mega strided tracking pipeline for i2map
run-mega-track-test-1min Test mega strided tracking pipeline on one video
run-mega-track-test-fastapiyv5 Test mega strided pipeline with FastAPI
run-mega-track-isiis-video video=... Mega strided tracking pipeline for cfe project
cluster-i2mapbulk Run inference and cluster on i2MAP bulk data
download-cluster project="i2map" ... Download and cluster data
cluster-ptvr-sweep roi_dir=... save_dir=... Sweep clustering for planktivore data
load-i2mapbulk data='data' Load i2MAP bulk data
load-cluster project="uav" data='data' ... Load clusters for any project
download-i2mapbulk-unlabeled Download i2MAP bulk unlabeled data
replace-m3-urls Replace m3 URLs with mantis
gen-bio-data image_dir="" Generate training data for the bio project
gen-cfe-data Generate training data for the CFE project
gen-i2map-data Generate training data for the i2map project
gen-i2mapbulk-data Generate training data for the i2map project from bulk
gen-uav-data Generate training data for the UAV project
gen-stats-csv project='UAV' data=... Generate training data stats
gen-ptvr-lowmag-data Generate training data for the planktivore low mag
init-ptvr-lowmag-vss Initialize VSS for planktivore low mag data
transcode-i2map Transcode i2MAP videos from mov to mp4
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Related projects

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  • sdcat - Sliced Detection and Clustering Analysis Toolkit; a tool to detect and cluster objects in images.
  • deepsea-ai - A tool to train and run object detection and tracking on video at scale in the cloud (AWS).
  • fastapi-yolov5 - A RESTful API for running YOLOv5 object detection models on images either locally or in the cloud (AWS).
  • fastapi-vss - A RESTful API for vector similarity search using foundational models.
  • fastapi-tator - A RESTful API server for bulk operations on a Tator annotation database.

🗓️ Last updated: 2025-06-01