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asana_github_test's Introduction

Hi there, my name is Ankit Chaurasia! 👋

  • 🔭 Read more about me at ankitchaurasia.info
  • 💡 Open source advocate.
  • 🔎 Apache-Airflow contributors.
  • 💻 Senior Software Engineer at Astronomer.
  • 🚴: My favourite sport is Cycling.

Contact Me

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🔧 Skills

Postgres MySQL MongoDB Redis SQLite Snowflake DuckDB

Apache Airflow Docker FastAPI Django

Amazon AWS Google Cloud Microsoft Azure

Python C++

Visual Studio Code PyCharm

CircleCI GitHub Actions

asana_github_test's People

Contributors

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asana_github_test's Issues

Automation of generation of masks

Issue:
Current generation of mask is wrong as the resultant mask for both left and right contains all 8 petals.

Solution and Implementation:
1. Calculate the centre of generated mask and create another black image with same resolution.
2. Divide the generated image into 4 half so that each half is a square. Make one of the square complete white.
3. Rotate this white square over he given mask so that the square fills the maximum white.
4. Once the petals area is detected divide it into 2 halfs.
5. Add first half to left mask and second half to right mask

Software Design and design pattern

Issue:
We currently have just the activity diagram.

Solution:

  1. First Decide upon best design pattern which suits this workflow.
  2. Create the UML class diagram

Reference Doc

Creation a reference document for the Calibration software and re-calibration software. Include all the steps and complete workflow.

Optimization of modules

Once the code is stable and each step in the workflow is working completely fine:

  1. Optimise each step for better time and space complexity.
  2. Improve the current algorithms

Automation of re-calibrate map step and making it as separate software

Issues:

  1. The re-calibration step in current workflow is not automated. By this I mean, the current workflow assumes user to select the desired corner points in the ideal calibration image and again selected the corner points on the input image. These corner points should be automatically be detected in both ideal calibration image and input calibration image.
  2. Ideally, re-calibration should be separate from calibration code base because these two are two different software. Moreover, the input to the re-calibration are the initial yaml file, ideal calibration image and the clicked image for re-calibration.

Design doc

Creation a design document for the Calibration software and re-calibration software. Include all the steps UML-class diagrams and complete workflow.

Automation of aligning views and generating panorama

Current Issue:
In the current workflow, first we project ichecker image and mark all the corners, then project the resultant image generated from generateDewrapingFiles step and again mark all the corners corresponding to each corner in ichecker image.

Solution and Implementation:

  1. Use corner Detection in ichecker image and create a vector corresponding to corners detected.
  2. Calculate the translation of the corners in resultant images manually and translate the coordinates obtained above by the ratio obtained.
  3. Use this as the final vector.

┆Attachments: marked.jpg | ichecker.png | ichecker_marked.jpg

Makes the steps parallel for better time complexity and efficiency

Issues:
In current workflow, there are various steps which can be run simultaneously using multi-thread. Current implementation is using iterative approach. Following steps in the workflow need to have code segments running with multi-threads:

  1. Generation of mask for left and right view (step-2)
  2. Generation of de-wraping files (step-3)
  3. Aligning views and generation of panorama (step-4)
  4. Generation of panorama and creation of final mapping matrix (step-5)

Class diagram/ UML

Creation of class diagram for complete workflow. Include all the steps in the process.

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