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danelleclinedanellecline
committedFeb 26, 2025
chore: updating recipes
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‎README.md

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@@ -71,60 +71,59 @@ Recipes are available to run the pipelines. To see the available recipes, run t
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```shell
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just list
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```
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# Available Recipes
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| Recipe | Description |
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|---------------------------------|-------------|
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| list | List recipes |
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| install | Setup the environment |
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| cp-env | Copy the default .env file to the project |
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| update_trackers | Update the environment. Run after checking out code changes |
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| update-env | Update environment |
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| cp-core | Copy core dev code to the project on doris |
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| cp-dev-ptvr | Copy planktivore dev code to the project on doris |
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| cp-dev-uav | Copy UAV dev code to the project on doris |
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| cp-dev-bio | Copy bio dev code to the project on doris |
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| cp-dev-i2map | Copy i2map dev code to the project on doris |
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| plot-tsne-vss project='uav' | Generate a t-SNE plot of the VSS database |
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| optimize-vss project='uav' | Optimize the VSS database |
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| calc-acc-vss project='uav' | Calculate the accuracy of the VSS database |
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| reset-vss-all | Reset the VSS database, removing all data (caution!) |
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| reset-vss project='uav' | Reset the VSS database before initializing or creating it |
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| remove-vss project='uav' | Remove an entry from the VSS database |
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| init-vss project='uav' | Initialize the VSS database for a project |
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| load-vss project='uav' | Load computed exemplars into the VSS database |
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| load-cfe-isiis-videos | Load CFE ISIIS mission videos |
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| load-ptvr-images images='tmp/roi' | Load planktivore ROI images |
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| cluster-ptvr-images images='tmp/roi' | Cluster planktivore ROI images |
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| load-ptvr-clusters clusters='tmp/roi/cluster.csv' | Load planktivore ROI clusters |
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| cluster-uav | Cluster UAV mission data |
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| detect-uav | Detect UAV mission data |
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| detect-uav-test | Detect UAV mission data (test mode) |
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| load-uav-images | Load UAV mission images |
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| load-uav type="cluster" | Load UAV detections/clusters |
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| fix-uav-metadata | Fix UAV metadata (lat/lon/alt) |
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| compute-saliency project='uav' | Compute saliency for VOC data and update Trackers in Tator |
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| crop project='uav' | Crop detections from VOC formatted downloads |
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| download-crop project='uav' | Download and crop with defaults for a project |
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| download project='uav' | Download only |
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| predict-vss project='uav' | Predict images using the VSS database |
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| run-ctenoA-test | Run strided inference on a single video |
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| run-ctenoA-prod | Run strided inference on a collection of videos in a TSV file |
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| run-mega-inference | Run mega strided inference on a single video |
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| run-mega-track-bio-video | Run mega tracking on a single bio project video |
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| run-m | Run mega tracking on a single bio project video |
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| run-mega-track-bio-dive | Run mega tracking on an entire dive for the bio project |
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| run-mega-track-i2map-video | Run mega tracking on an i2MAP video |
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| run-mega-track-test-1min | Test mega tracking on a single video (1 min) |
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| run-mega-track-test-fastapiyv5 | Test mega tracking with FastAPI |
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| cluster-i2mapbulk | Run inference and cluster on i2MAP bulk data |
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| init-i2map-vss | Initialize VSS with combined i2MAP training data |
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| load-i2mapbulk data='data' | Load i2MAP bulk data |
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| download-i2mapbulk-unlabeled | Download unlabeled i2MAP bulk data |
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| gen-cfe-data | Generate training data for the CFE project |
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| gen-i2map-data | Generate training data for the i2MAP project |
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| gen-i2mapbulk-data | Generate training data for the i2MAP bulk server |
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| gen-uav-data | Generate training data for the UAV project |
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| gen-stats-csv project='UAV' | Generate training data stats |
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| Recipe | Description |
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|---------------------------------------------|-------------|
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| `list` | List recipes |
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| `install` | Setup the environment |
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| `cp-env` | Copy the default `.env` file to the project |
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| `update_trackers` | Update the environment after code changes |
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| `update-env` | Update environment |
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| `cp-core` | Copy core dev code to the project on Doris |
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| `cp-dev-ptvr` | Copy planktivore dev code to the project on Doris |
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| `cp-dev-uav` | Copy UAV dev code to the project on Doris |
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| `cp-dev-bio` | Copy bio dev code to the project on Doris |
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| `cp-dev-i2map` | Copy i2map dev code to the project on Doris |
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| `plot-tsne-vss project='uav'` | Generate a t-SNE plot of the VSS database |
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| `optimize-vss project='uav' *more_args=""` | Optimize the VSS database |
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| `calc-acc-vss project='uav'` | Calculate the accuracy of the VSS database |
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| `reset-vss-all` | Reset the VSS database (remove all data) |
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| `reset-vss project='uav'` | Reset the VSS database for a specific project |
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| `remove-vss project='uav' *more_args=""` | Remove an entry from the VSS database |
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| `init-vss project='uav' *more_args=""` | Initialize the VSS database for a project |
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| `load-vss project='uav'` | Load computed exemplars into the VSS database |
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| `load-cfe-isiis-videos *more_args=""` | Load CFE ISII mission videos |
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| `load-ptvr-images images='tmp/roi' *more_args=""` | Load planktivore ROI images |
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| `cluster-ptvr-images images='tmp/roi' *more_args=""` | Cluster planktivore ROI images |
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| `load-ptvr-clusters clusters='tmp/roi/cluster.csv' *more_args=""` | Load planktivore ROI clusters |
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| `rescale-ptvr-images` | Rescale planktivore ROI images |
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| `cluster-uav *more_args=""` | Cluster UAV missions |
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| `detect-uav *more_args=""` | Detect UAV missions |
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| `detect-uav-test` | Detect UAV mission data (test mode) |
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| `load-uav-images` | Load UAV mission images |
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| `load-uav type="cluster"` | Load UAV detections/clusters |
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| `fix-uav-metadata` | Fix UAV metadata (lat/lon/alt) |
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| `compute-saliency project='uav' *more_args=""` | Compute saliency for VOC data and update the Tator database |
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| `crop project='uav' *more_args=""` | Crop detections from VOC downloads |
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| `download-crop project='uav' *more_args=""` | Download and crop for a project |
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| `download project='uav'` | Download only |
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| `predict-vss project='uav' image_dir='/tmp/download' *more_args=""` | Predict images using the VSS database |
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| `run-ctenoA-test` | Run strided inference on a single video |
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| `run-ctenoA-prod` | Run strided inference on a collection of videos |
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| `run-mega-inference` | Run mega strided inference on a single video |
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| `run-mega-track-bio-video video='/mnt/M3/...' gpu_id='0'` | Run tracking on a bio project video |
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| `run-mega-track-bio-dive dive='/mnt/M3/...' gpu_id='0'` | Run tracking on an entire dive for the bio project |
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| `run-mega-track-i2map-video video='/mnt/M3/...' gpu_id='0'` | Run tracking on an i2map project video |
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| `run-mega-track-test-1min` | Test the tracking pipeline on a single video |
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| `run-mega-track-test-fastapiyv5` | Run tracking pipeline with FastAPI |
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| `cluster-i2mapbulk` | Run inference and cluster on i2MAP bulk data |
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| `cluster-ptvr-swp roi_dir='...' save_dir='...'` | Run sweep for planktivore data |
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| `load-i2mapbulk data='data'` | Load i2MAP bulk data |
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| `download-i2mapbulk-unlabeled` | Download unlabeled i2MAP bulk data |
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| `gen-cfe-data` | Generate training data for the CFE project |
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| `gen-i2map-data` | Generate training data for the i2map project |
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| `gen-i2mapbulk-data` | Generate i2map training data from the bulk server |
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| `gen-uav-data` | Generate training data for the UAV project |
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| `gen-stats-csv project='UAV' data='/mnt/.../'` | Generate training data statistics |
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--
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‎justfile

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@@ -49,6 +49,7 @@ cp-dev-bio:
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cp ./aipipeline/projects/bio/core/*.py /Volumes/dcline/code/aipipeline/aipipeline/projects/bio/core
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cp ./aipipeline/projects/bio/config/* /Volumes/dcline/code/aipipeline/aipipeline/projects/bio/config/
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cp ./aipipeline/projects/bio/model/*.py /Volumes/dcline/code/aipipeline/aipipeline/projects/bio/model/
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cp ./deps/biotrack/biotrack/*.py /Volumes/dcline/code/aipipeline/deps/biotrack/biotrack/
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# Copy i2map dev code to the project on doris
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cp-dev-i2map:
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cluster-ptvr-images images='tmp/roi' *more_args="":
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#!/usr/bin/env bash
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export PROJECT_DIR=./aipipeline/projects/planktivore
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time sdcat cluster roi --config-ini $PROJECT_DIR/config/sdcat.ini --roi-dir {{images}} {{more_args}}
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time sdcat cluster roi --config-ini $PROJECT_DIR/config/sdcat.ini --device cuda:1 --roi-dir {{images}} {{more_args}}
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# Load planktivore ROI clusters
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load-ptvr-clusters clusters='tmp/roi/cluster.csv' *more_args="":
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#!/usr/bin/env bash
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run-ctenoA-test:
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#!/usr/bin/env bash
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export PYTHONPATH=.
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/vss_init.py \
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/run_strided_track.py \
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--config ./aipipeline/projects/bio/config/config.yml \
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--class_name "Ctenophora sp. A" \
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--endpoint-url "http://localhost:8001/predict" \
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run-ctenoA-prod:
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#!/usr/bin/env bash
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export PYTHONPATH=.
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/vss_init.py \
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/cluster.py \
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--config ./aipipeline/projects/bio/config/config.yml \
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--class_name "Ctenophora sp. A" \
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--endpoint-url "http://fastap-fasta-0riu3xafmhua-337062127.us-west-2.elb.amazonaws.com/predict" \
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run-mega-inference:
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#!/usr/bin/env bash
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export PYTHONPATH=.
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/vss_init.py \
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/cluster.py \
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--config ./aipipeline/projects/bio/config/config.yml \
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--class_name "animal" \
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--class-remap "{\"animal\":\"marine organism\"}" \
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/bio/process.py \
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--config ./aipipeline/projects/bio/config/config.yml \
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--max-frames-tracked 200 --min-score-det 0.1 --min-score-track 0.1 --batch-size 15 --min-frames 10 --version delme \
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--vits-model /Volumes/DeepSea-AI/models/i2MAP/mbari-i2map-vits-b-16ntnr-20250130/ \
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--det-model /Volumes/DeepSea-AI/models/megadet --skip-load \
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--vits-model /mnt/DeepSea-AI/models/i2MAP/mbari-i2map-vits-b-16ntnr-20250130/ \
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--det-model /mnt/DeepSea-AI/models/megadet --skip-load \
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--stride 1 --video {{video}} --max-seconds 10 --flush --gpu-id {{gpu_id}}
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# Run the mega strided tracking pipeline on a single video for the bio project for 30 seconds
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find "{{dive}}" -name '*.m*' ! -name "._*.m*" -type f | xargs -P 1 -n 1 -I {} bash -c 'process_file "{}"'
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# Run the mega strided tracking pipeline on a single video for the i2map project
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# --det-model /mnt/DeepSea-AI/models/FathomNet/megalodon/ \
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#run-mega-track-i2map-video video='/mnt/M3/master/i2MAP/2019/02/20190204/i2MAP_20190205T102700Z_200m_F031_17.mov' gpu_id='0':
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run-mega-track-i2map-video video='/mnt/M3/master/i2MAP/2024/11/20241119/i2MAP_20241119T165914Z_200m_F031_4.mov' gpu_id='0':
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#!/usr/bin/env bash
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export PYTHONPATH=.:deps/biotrack:.
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time python3 aipipeline/projects/bio/process.py \
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--det-model /mnt/DeepSea-AI/models/megadetrg-yolov5 \
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--config ./aipipeline/projects/i2map/config/config.yml \
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--det-model /mnt/DeepSea-AI/models/FathomNet/megalodon/ \
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--vits-model /mnt/DeepSea-AI/models/i2MAP/mbari-i2map-vits-b-8-20250216\
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--max-frames-tracked 200 --min-score-det 0.02 --min-score-track 0.1 --min-frames 8 --version metadetrt-vits-track-ft \
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--stride 1 --skip-load --batch-size 16 --create-video \
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--stride 1 --skip-load --batch-size 16 --create-video --max-seconds 1 \
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--video {{video}} --gpu-id {{gpu_id}}
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# Run the mega strided tracking pipeline on a single video to test the pipeline
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export PYTHONPATH=.:/Users/dcline/Dropbox/code/biotrack:.
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time python3 aipipeline/projects/bio/predict.py \
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--config ./aipipeline/projects/bio/config/config.yml \
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--det-model /Volumes/DeepSea-AI/models/megadet \
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--vits-model /Volumes/DeepSea-AI/models/m3midwater-vit-b-16 \
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--det-model /mnt/DeepSea-AI/models/megadet \
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--vits-model /mnt/DeepSea-AI/models/m3midwater-vit-b-16 \
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--max-frames-tracked 200 --min-score-det 0.0002 --min-score-track 0.5 --min-frames 5 --version mega-vits-track-gcam \
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--stride 8 --max-seconds 60 --imshow --skip-load \
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--video aipipeline/projects/bio/data/V4361_20211006T163256Z_h265_1min.mp4
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export PYTHONPATH=.:/Users/dcline/Dropbox/code/biotrack:.
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time python3 aipipeline/projects/bio/predict.py \
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--config ./aipipeline/projects/bio/config/config.yml \
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--vits-model /Volumes/DeepSea-AI/models/m3midwater-vit-b-16 \
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--vits-model /mnt/DeepSea-AI/models/m3midwater-vit-b-16 \
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--max-frames-tracked 200 --min-score-det 0.0002 --min-score-track 0.5 --min-frames 5 --version mega-vits-track-gcam \
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--stride 15 --max-seconds 60 --imshow --skip-load \
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--endpoint-url http://FastAP-FastA-0RIu3xAfMhUa-337062127.us-west-2.elb.amazonaws.com/predict \
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#!/usr/bin/env bash
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export PYTHONPATH=.
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export MPLCONFIGDIR=/tmp
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/i2mapbulk/vss_init.py \
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time conda run -n aipipeline --no-capture-output python3 aipipeline/prediction/cluster_pipeline.py \
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--config ./aipipeline/projects/i2mapbulk/config/config_unknown.yml \
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--data aipipeline/projects/i2mapbulk/data/bydepth.txt
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384-
# Init VSS with combined i2MAP training data. Run with just init-i2map-vss
385-
init-i2map-vss:
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# Run sweep for planktivore data. Example just cluster-ptvr-swp /mnt/ML_SCRATCH/Planktivore/aidata-export-03-low-mag-square /mnt/DeepSea-AI/data/Planktivore/cluster/aidata-export-03-low-mag-square
387+
cluster-ptvt-sweep roi_dir='/mnt/ML_SCRATCH/Planktivore/aidata-export-03-low-mag-square' save_dir='/mnt/DeepSea-AI/data/Planktivore/cluster/aidata-export-03-low-mag-square':
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#!/usr/bin/env bash
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export PYTHONPATH=.
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export MPLCONFIGDIR=/tmp
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time conda run -n aipipeline --no-capture-output python3 aipipeline/projects/i2map/vss_init.py \
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--config ./aipipeline/projects/i2map/config/config.yml \
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--processed-path /mnt/ML_SCRATCH/i2map/Combined/
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for alpha in 0.8 0.9 1.0; do
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for epsilon in 0.01 0.05 0.1 0.5; do
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just --justfile {{justfile()}} cluster-ptvr-images {{roi_dir}} --save-dir {{save_dir}} --alpha $alpha --cluster-selection-epsilon $epsilon
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done
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done
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# Load i2MAP bulk data run with ENV_FILE=.env.i2map just load-i2mapbulk <path to the cluster_detections.csv file>
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load-i2mapbulk data='data':
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#!/usr/bin/env bash
@@ -421,4 +423,4 @@ gen-uav-data:
421423
gen-stats-csv project='UAV' data='/mnt/ML_SCRATCH/UAV/':
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#!/usr/bin/env bash
423425
export PYTHONPATH=.
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time conda run -n aipipeline python3 aipipeline/prediction/gen_stats.py --data {{data}} --prefix {{project}}
426+
time conda run -n aipipeline python3 aipipeline/prediction/gen_stats.py --data {{data}} --prefix {{project}}

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