ibeis 2.0.0

IBEIS - Image Analysis

I.B.E.I.S. = Image Based Ecological Information System

Program Description

IBEIS program for the storage and management of images and derived data for use in computer vision algorithms. It aims to compute who an animal is, what species an animal is, and where an animal is with the ultimate goal being to ask important why biological questions. This This repo Image Analysis image analysis module of IBEIS. It is both a python module and standalone program.

Currently the system is build around and SQLite database, a PyQt4 GUI, and matplotlib visualizations. Algorithms employed are: random forest species detection and localization, hessian-affine keypoint detection, SIFT keypoint description, LNBNN identification using approximate nearest neighbors. Algorithms in development are SMK (selective match kernel) for identification and deep neural networks for detection and localization.

The core of IBEIS is the IBEISController class. It provides an API into IBEIS data management and algorithms. The IBEIS API Documentation can be found here: http://erotemic.github.io/ibeis

The IBEIS GUI (graphical user interface) is built on top of the API. We are also experimenting with a new web frontend that bypasses the older GUI code.

## Self Installing Executables:

Unfortunately we have not released self-installing-executables for IBEIS yet. We plan to release these “soon”.

However there are old HotSpotter (the software which IBEIS is based on) binaries available. These can be downloaded from: http://cs.rpi.edu/hotspotter/

Visual Demo

Match Scoring

Spatial Verification

python -m vtool.spatial_verification --test-spatially_verify_kpts --show

Name Scoring

python -m ibeis.algo.hots.chip_match show_single_namematch --qaid 1 --show

Identification Ranking

python -m ibeis.algo.hots.chip_match show_ranked_matches --show --qaid 86

Inference

# broken
# python -m ibeis.algo.preproc.preproc_encounter compute_encounter_groups --show

Internal Modules

In the interest of modular code we are actively developing several different modules.

Erotemic’s IBEIS Image Analysis module dependencies

• https://github.com/WildbookOrg/utool docs: http://erotemic.github.io/utool

• https://github.com/WildbookOrg/plottool docs: http://erotemic.github.io/plottool

• https://github.com/WildbookOrg/vtool docs: http://erotemic.github.io/vtool

• https://github.com/WildbookOrg/hesaff docs: http://erotemic.github.io/hesaff

• https://github.com/WildbookOrg/guitool docs: http://erotemic.github.io/guitool

bluemellophone’s IBEIS Image Analysis modules

• https://github.com/WildbookOrg/detecttools

• https://github.com/WildbookOrg/pyrf docs: http://bluemellophone.github.io/pyrf

The IBEIS module itself:

• https://github.com/WildbookOrg/ibeis

IBEIS Development Environment Setup

NOTE: this section is outdated.

# The following install script install ibeis and all dependencies.
# If it doesnt you can look at the older instructions which follow
# and try to figure it out. After running this you should have a code
# directory with all of the above repos.

# NOTE: IBEIS DEPENDS ON PYTHON 2.7. Unfortunately we are having problems moving to 3.

# Navigate to your code directory
export CODE_DIR=~/code
mkdir $CODE_DIR
cd $CODE_DIR

# Clone IBEIS
git clone https://github.com/WildbookOrg/ibeis.git
cd ibeis

# Generate the prereq install script (does not install anything)
#
./_scripts/bootstrap.py
or
./super_setup.py --bootstrap

# Ensure all python dependencies have been installed
pip install -r requirements.txt
pip install -r optional-requirements.txt

# Run the prereq install script (installs prereq libraries)
./_scripts/__install_prereqs__.sh

# Python repositories come with a standard setup.py script to help you install them
# Because IBEIS has several python repos, we created a super_setup script to help
# you run the same command accross all IBIES repositories.

# Use super_setup.py to pull the latest and greatest from all the respos.
# This will clone any dependency repos that do not exist.
./super_setup.py pull

# Ensure you are using WildMe repos
./super_setup.py move-wildme

# Switch to current development branch
./super_setup.py checkout next

# Run super_setup to build and install ibeis modules in development mode
# (the build flag builds any c++ files, and the develop flag installs a
#  python module as a symbolic link to python's site-packages)
./super_setup.py build develop

# Usually this needs to be run twice because super_setup often needs to
# configure itself on the first run. (Either running it twice wont hurt)
./super_setup.py build develop

# Optional: set a workdir and download a test dataset
./dev.py --set-workdir ~/data/work --preload-exit
./dev.py -t mtest
./dev.py -t nauts
./reset_dbs.py


# make sure everyhing is set up correctly
./assert_modules.sh

Running Tests

The new way of running tests is with xdoctest, or using the “run_doctests.sh” script.

Example usage

(Note: This list is far from complete)

#--------------------
# Main Commands
#--------------------
python main.py <optional-arguments> [--help]
python dev.py <optional-arguments> [--help]
# main is the standard entry point to the program
# dev is a more advanced developer entry point

# ** NEW 7-23-2015 **: the following commands are now equivalent and do not
# have to be specified from the ibeis source dir if ibeis is installed
python -m ibeis <optional-arguments> [--help]
python -m ibeis.dev <optional-arguments> [--help]

# Useful flags.
# Read code comments in dev.py for more info.
# Careful some commands don't work. Most do.
# --cmd          # shows ipython prompt with useful variables populated
# -w, --wait     # waits (useful for showing plots)
# --gui          # starts the gui as well (dev.py does not show gui by default, main does)
# --web          # runs the program as a web server
# --quiet        # turns off most prints
# --verbose      # turns on verbosity
# --very-verbose # turns on extra verbosity
# --debug2       # runs extra checks
# --debug-print  # shows where print statments occur
# -t [test]


#--------------------
# PSA: Workdirs:
#--------------------
# IBEIS uses the idea of a work directory for databases.
# Use --set-workdir <path> to set your own, or a gui will popup and ask you about it
./main.py --set-workdir /raid/work --preload-exit
./main.py --set-logdir /raid/logs/ibeis --preload-exit

./dev.py --set-workdir ~/data/work --preload-exit

# use --db to specify a database in your WorkDir
# --setdb makes that directory your default directory
python dev.py --db <dbname> --setdb

# Or just use the absolute path
python dev.py --dbdir <full-dbpath>


#--------------------
# Examples:
# Here are are some example commands
#--------------------
# Run the queries for each roi with groundtruth in the PZ_MTEST database
# using the best known configuration of parameters
python dev.py --db PZ_MTEST --allgt -t best
python dev.py --db PZ_MTEST --allgt -t score


# View work dir
python dev.py --vwd --prequit

# List known databases
python dev.py -t list_dbs


# Dump/Print contents of params.args as a dict
python dev.py --prequit --dump-argv

# Dump Current SQL Schema to stdout
python dev.py --dump-schema --postquit


#------------------
# Convert a hotspotter database to IBEIS
#------------------

# NEW: You can simply open a hotspotter database and it will be converted to IBEIS
python -m ibeis convert_hsdb_to_ibeis --dbdir <path_to_hsdb>

# This script will exlicitly conver the hsdb
python -m ibeis convert_hsdb_to_ibeis --hsdir <path_to_hsdb> --dbdir <path_to_newdb>

#---------
# Ingest examples
#---------
# Ingest raw images
python -m ibeis.dbio.ingest_database --db JAG_Kieryn

#---------
# Run Tests
#---------
./run_tests.py

#----------------
# Test Commands
#----------------
# Set a default DB First
./dev.py --setdb --dbdir /path/to/your/DBDIR
./dev.py --setdb --db YOURDB
./dev.py --setdb --db PZ_MTEST
./dev.py --setdb --db PZ_FlankHack

# List all available tests
./dev.py -t help
# Minimal Database Statistics
./dev.py --allgt -t info
# Richer Database statistics
./dev.py --allgt -t dbinfo
# Print algorithm configurations
./dev.py -t printcfg
# Print database tables
./dev.py -t tables
# Print only the image table
./dev.py -t imgtbl
# View data directory in explorer/finder/nautilus
./dev.py -t vdd

# List all IBEIS databases
python -m ibeis list_dbs
# Delete cache
python -m ibeis delete_cache --db testdb1


# Show a single annotations
python -m ibeis.viz.viz_chip show_chip --db PZ_MTEST --aid 1 --show
# Show annotations 1, 3, 5, and 11
python -m ibeis.viz.viz_chip show_many_chips --db PZ_MTEST --aids=1,3,5,11 --show


# Database Stats for all our important datasets:
./dev.py --allgt -t dbinfo --db PZ_MTEST | grep -F "[dbinfo]"

# Some mass editing of metadata
./dev.py --db PZ_FlankHack --edit-notes
./dev.py --db GZ_Siva --edit-notes
./dev.py --db GIR_Tanya --edit-notes
./dev.py --allgt -t dbinfo --db GZ_ALL --set-all-species zebra_grevys

# Current Experiments:

# Main experiments
python -m ibeis --tf draw_annot_scoresep --db PZ_MTEST -a default -t best --show
python -m ibeis.dev -e draw_rank_cdf --db PZ_MTEST --show -a timectrl
# Show disagreement cases
ibeis --tf draw_match_cases --db PZ_MTEST -a default:size=20 \
    -t default:K=[1,4] \
    --filt :disagree=True,index=0:4 --show

# SMK TESTS
python dev.py -t smk2 --allgt --db PZ_MTEST --nocache-big --nocache-query --qindex 0:20
python dev.py -t smk2 --allgt --db PZ_MTEST --qindex 20:30 --va

# Feature Tuning
python dev.py -t test_feats -w --show --db PZ_MTEST --allgt --qindex 1:2

python dev.py -t featparams -w --show --db PZ_MTEST --allgt
python dev.py -t featparams_big -w --show --db PZ_MTEST --allgt

# NEW DATABASE TEST
python dev.py -t best --db seals2 --allgt

# Testing Distinctivness Parameters
python -m ibeis.algo.hots.distinctiveness_normalizer --test-get_distinctiveness --show --db GZ_ALL --aid 2
python -m ibeis.algo.hots.distinctiveness_normalizer --test-get_distinctiveness --show --db PZ_MTEST --aid 10
python -m ibeis.algo.hots.distinctiveness_normalizer --test-test_single_annot_distinctiveness_params --show --db GZ_ALL --aid 2

# 2D Gaussian Curves
python -m vtool_ibeis.patch --test-test_show_gaussian_patches2 --show

# Test Keypoint Coverage
python -m vtool_ibeis.coverage_kpts --test-gridsearch_kpts_coverage_mask --show
python -m vtool_ibeis.coverage_kpts --test-make_kpts_coverage_mask --show

# Test Grid Coverage
python -m vtool_ibeis.coverage_grid --test-gridsearch_coverage_grid_mask --show
python -m vtool_ibeis.coverage_grid --test-sparse_grid_coverage --show
python -m vtool_ibeis.coverage_grid --test-gridsearch_coverage_grid --show

# Test Spatially Constrained Scoring
python -m ibeis.algo.hots.vsone_pipeline --test-compute_query_constrained_matches --show
python -m ibeis.algo.hots.vsone_pipeline --test-gridsearch_constrained_matches --show

# Test VsMany ReRanking
python -m ibeis.algo.hots.vsone_pipeline --test-vsone_reranking --show
python -m ibeis.algo.hots.vsone_pipeline --test-vsone_reranking --show --homog

# Problem cases with the back spot
python -m ibeis.algo.hots.vsone_pipeline --test-vsone_reranking --show --homog --db GZ_ALL --qaid 425
python -m ibeis.algo.hots.vsone_pipeline --test-vsone_reranking --show --homog --db GZ_ALL --qaid 662
python dev.py -t custom:score_method=csum,prescore_method=csum --db GZ_ALL --show --va -w --qaid 425 --noqcache
# Shows vsone results with some of the competing cases
python -m ibeis.algo.hots.vsone_pipeline --test-vsone_reranking --show --homog --db GZ_ALL --qaid 662 --daid_list=425,342,678,233

# More rerank vsone tests
python -c "import utool as ut; ut.write_modscript_alias('Tbig.sh', 'dev.py', '--allgt  --db PZ_Master0')"
sh Tbig.sh -t custom:rrvsone_on=True custom
sh Tbig.sh -t custom:rrvsone_on=True custom --noqcache

#----
# Turning back on name scoring and feature scoring and restricting to rerank a subset
# This gives results that are closer to what we should actually expect
python dev.py --allgt -t custom \
    custom:rrvsone_on=True,prior_coeff=1.0,unconstrained_coeff=0.0,fs_lnbnn_min=0,fs_lnbnn_max=1 \
    custom:rrvsone_on=True,prior_coeff=0.5,unconstrained_coeff=0.5,fs_lnbnn_min=0,fs_lnbnn_max=1 \
    custom:rrvsone_on=True,prior_coeff=0.1,unconstrained_coeff=0.9,fs_lnbnn_min=0,fs_lnbnn_max=1 \
    --print-bestcfg
#----

#----
# VsOneRerank Tuning: Tune linar combination
python dev.py --allgt -t \
    custom:fg_weight=0.0 \
\
    custom:rrvsone_on=True,prior_coeff=1.0,unconstrained_coeff=0.0,fs_lnbnn_min=0.0,fs_lnbnn_max=1.0,nAnnotPerNameVsOne=200,nNameShortlistVsone=200 \
\
    custom:rrvsone_on=True,prior_coeff=.5,unconstrained_coeff=0.5,fs_lnbnn_min=0.0,fs_lnbnn_max=1.0,nAnnotPerNameVsOne=200,nNameShortlistVsone=200 \
\
  --db PZ_MTEST
#--print-confusion-stats --print-gtscore
#----

# Testing no affine invaraiance and rotation invariance
dev.py -t custom:AI=True,RI=True custom:AI=False,RI=True custom:AI=True,RI=False custom:AI=False,RI=False --db PZ_MTEST --show

Caveats / Things we are not currently doing

• We do not add or remove points from kdtrees. They are always rebuilt