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Stereoscopic rectification using multi-pose image sets from a single camera. Independent research project

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jnickg/jnickg-stereo

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Overview

This repositroy defines the stereo project, and the rectifi app. It is the home of jnickg's experiments and investigations into stereoscopy.

The live project can be found at rectifi.jnickg.net

Algorithms

Algorithm code lives in ./rectifi/algorithm. The primary algorithm for stereo rectification is stereo.py

Run Locally

Note: For those interested in simply running the stereoscopic rectification algorithm, the easiest way is to run Unit Tests as shown below. Sample input images are provided for testing purposes. To change the files used in the test, replace the files in ./rectifi/test/res/stereo with files of your choosing (be sure to include calibration-pattern images!).

Requirements

  • Python 3 and pip
  • Linux systems may require extra apt files. See Aptfile for more info.

Setup

  1. git clone git@github.com:jnickg/jnickg-stereo.git (or download ZIP file)
  2. cd jnickg-stereo
  3. pip install -r requirements.txt ← install necessary Python packages
  4. python manage.py collectstatic --noinput ← collect static files to be served by local web instance

Running Web Instance Locally

Note: In general, see Procfile (linux) and Procfile.windows (windows) for commands to run either the web instance, or the worker instance. Below shows only how to run the web instance.

  • Windows: python manage.py runserver 0.0.0.0:5000
  • Linux: gunicorn stereo.wsgi --log-file -

Running Unit Tests

Note: By default, test output files are dumped to the result of tempfile.gettempdir(). Look for the actual location in test logs, with the message MOVED TEST ARTIFACTS TO:. The output directory can also be easily customized by changing the value of CONFIG_OUTPUT_DUMP_DIR in test_algorithm.py

  • Windows: python manage.py test
  • Linux: python3 manage.py test

Support

Contact jnickg with questions, requests, etc.

Track him down by visiting his website

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Stereoscopic rectification using multi-pose image sets from a single camera. Independent research project

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