bellingcat / bellingcat/ShadowFinder

Way to compare multiple shadows at different times

Open
#20 3 comments 0 reactions 0 assignees View on GitHub
enhancement
Dominant language
Python
Stars
604
Forks
53
Avg merge
3m
Merged PRs (30d)
3

Description

By comparing multiple images of a location separated in time, it is possible to partially disambiguate the location by overlaying the resulting rings.

It would be good if the Shadow Finder tool had some way of supporting this type of search.

Any PR to close this issue should consider the most user-friendly way to support this change in the existing Notebook or in a new Notebook.

At a minimum it should support shadow measurements for two times, but supporting an arbitrary number of inputs would be interesting!

## An Example

Here is an example made by running the tool twice and overlaying (lighten only) the resulting output:

![image](https://github.com/bellingcat/ShadowFinder/assets/54807169/5e4b57ba-eb01-4736-937d-62ef21f34fc5)

Similarly, overlaying (darken only) shows only the matching locations:

![image](https://github.com/bellingcat/ShadowFinder/assets/54807169/f8038bbf-e333-44a4-a861-34ba13293a57)

This works in both UTC and Local modes, though with local times the locations are less intuitive:

![image](https://github.com/bellingcat/ShadowFinder/assets/54807169/a7b5eb05-70af-4d00-b554-e478630e7d85)

Contributor guide

Open the contributing guide

Research direction

Start by locating the existing Shadow Finder Notebook and tracing how one shadow measurement produces its output ring. Decide whether the comparison belongs there or in a new Notebook, then define how multiple time inputs and overlays should work. Done means at least two measurements can be compared, with arbitrary inputs supported if the chosen design allows it.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
data-visualization
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
30/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.