First Steps with the Example Notebooks¶
This tutorial introduces the project through the example notebooks shipped in examples/.
Recommended order¶
- Start with
examples/package_usage.ipynb - Continue with
examples/Mining.ipynb
Notebook 1: examples/package_usage.ipynb¶
Use this notebook as the quickest hands-on entry point.
What it covers:
- importing
gefolki - downloading the example datasets
- calling
gefolki.mining(...)on a reference and secondary image pair - running
gefolki.demo()with the bundled example scenes
Why start here:
- it shows the smallest working Python surface of the library
- it exercises both the mining workflow and the built-in demo
- it is the closest thing in the repository to a quickstart notebook
Notebook 2: examples/Mining.ipynb¶
Use this notebook after the package-usage quickstart.
What it covers:
- loading the reference and secondary images explicitly
- visualizing the input data
- downsampling for the coarse search stage
- applying the rank-based matching criterion
- refining the search in the reference crop
- visualizing the extracted match
Why it matters:
- it explains what
gefolki.mining(...)is doing internally - it is useful when you need to tune
rankorfdecimation - it provides a more inspectable workflow than the one-line API call
Suggested learning path¶
After working through these notebooks:
- use the Python API reference to map notebook code to the supported interfaces
- use the CLI reference if you want to run the mining workflow from the command line
- use the Explanation section for upstream conceptual background and parameter rationale