ascota_core

ascota_core is the first stage of the ASCOTA pipeline.
It provides the fundamental computer vision and analysis utilities that later modules build upon.

Purpose

This package contains tools for:

• Segmentation & detection
  Identifying and isolating key elements in input images (e.g., sherds, measurement cards).
  Uses models like SAM (Segment Anything Model) together with OpenCV-based preprocessing.

• Color card classification & correction
  Detecting reference color cards, classifying patches, and applying color correction to normalize input images across lighting conditions.

• Geometric scaling & surface estimation
  Leveraging detected measurement cards to compute pixels-per-centimeter ratios and estimate the surface area of sherds/pottery fragments.

Role in the pipeline

ascota_core is the core foundational package that prepares and standardizes input images for downstream classification and analysis. It ensures that: - Sherds are properly segmented from the background. - Color profiles are normalized to a standard reference. - Geometric measurements are calibrated to real-world units (via scale cards).

Together, these ensure later classification is performed on calibrated, comparable data.

Submodules

• color: color correction to standard reference and color based clustering.
• imaging: segmentation utilities and color card detection.
• scale: scale estimation and pixel-to-centimeter conversion.
• utils: shared helpers and lower-level routines.
• mobilesam_wand: interactive point-prompt segmentation session API.