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Lite Classify 1.2 can process just the area you are looking at, and adds a pixel-level pass for strips narrower than an object.
- Process This Extent Only (Tab 1): zoom to an area and work on that part alone, for a quick demo or a machine with limited memory. The whole image stays visible around it at low resolution, the source file is only read, and the extent gets its own workspace folder.
- Greenness refinement (Tab 3): after classification, re-decide two classes (such as grass and bare) pixel by pixel from Excess Green. It brings out thin green strips, and its default mode keeps patchy or dying grass whole.
- Optional DINOv3 ViT-S+/16 for Discover Classes and the classifier: use your own download from Meta. It is not included, and it stays under Meta's DINOv3 License.
- Map View (Tab 3): one Ortho / Segments / Classified selector, a segment boundaries switch that works in every view, and opacity and blend for the map layers.
- Accuracy points: Export Points to a re-importable CSV; on import, match class names, decide what happens to leftover classes, and optionally keep only points inside the processed extent; Delete Checked alongside Unassign Checked.
- Changed: class separability is now cross-validated. The earlier score could read 2.00 for nearly every pair, so values will be lower and more telling than in 1.1.
- Fixed: the minimum mapping unit sieve no longer leaves small patches at the image edge unclassified.
The manual is rebuilt on a new worked example, the 13.5 ha CAFS experimental agricultural site, with its sample data on Google Drive.
Two offline Windows installers: Setup CPU runs on any Windows 10/11 PC; Setup GPU adds NVIDIA CUDA for faster segmentation and appearance features. Installing either replaces 1.1.
User manual: https://leobarua.github.io/liteclassify/manual/