Baru Validator v2.0.0 - The Hybrid Geo-Score Update 🚀
We are proud to announce version 2.0.0 of the Baru Validator! This is
the biggest update to the tool since its creation. It introduces a
groundbreaking validation methodology for Remote Sensing that
cross-references traditional statistical metrics with the spatial
realism of classifications, actively combating overfitting in Machine
Learning algorithms.

🎉 New Features
New Hybrid Module (Geo-Score): Added the "Hybrid Evaluation" tab. The
plugin now evaluates the spatial realism (Spatial Conformity) of
models by crossing the Target-Class F1-Score with the generated
geometry (total predicted area, average canopy patch size, and number
of fragments).

Automatic Overfitting Detection: The algorithm now severely penalizes
models that overestimate the target or generate unrealistic continuous
patches. This reveals the crucial difference between a model that
simply "memorized" the validation data (Illusory Accuracy) and a model
that actually generalized well across the real landscape.

Interactive Hybrid Dashboard (HTML): Generates a brand new comparative
HTML report that ranks models based on their Final Hybrid Score. It
includes equilibrium charts (Statistical vs. Spatial) and automated
analytical conclusions pointing out the best cartographic model.

⚡ Enhancements
Universal Support for Rasters and Vectors: The Geo-Score module now
natively accepts image files (.tif/.tiff via GDAL/SciPy in-memory
processing) in addition to vectors (.shp, .gpkg), eliminating the need
for prior vectorization to analyze spatial patches.

Target-Class Focus: The hybrid engine no longer relies on Global
Accuracy (OA/Kappa) as its primary weight. It now uses RegEx to
extract the exact F1-Score of the specific class of interest,
preventing the "background" accuracy from masking the final score.

Dynamic HTML Parsing: The Master Dashboard engine has been rewritten
to extract data (Global Metrics, Recall, Precision, and F1 per class)
directly from the source code of any Baru Validator report, whether
it's legacy HTML or enveloped in JSON.

🐛 Bug Fixes
Individual HTML Export Fix: Resolved a critical bug where metrics
(Kappa, F1-Score, OA) appeared as 0.0000 in individual reports due to
an internal dictionary misalignment (results['metrics']).

Zero Division Handling: Fixed the Recall and Precision calculations
when the algorithm fails to detect any correct sample of the target
class (i.e., 100% false negatives), preventing the plugin from
crashing.

Dashboard Variables Fix: Corrected a naming mismatch (acc_html vs
acc_path) that prevented the generation of the Consolidated Master
Dashboard (V12).

Strict indentation alignment (IndentationError) fixed in core class
imports to ensure full compatibility with QGIS >= 3.0.0.

💡 Tip for users: After updating, we highly recommend running the new
"Hybrid Evaluation (Geo-Score)" module on your old Random Forest,
Extra Trees, or CatBoost tests. Baru Validator 2.0.0 will surprise you
by showing how models with a 100% statistical F1-Score can completely
fail in the real world!

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