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+# Semantic Detection Training Data
+
+# Source
+- Aerial imagery from reconnaissance winged UAVs at 600–1000m altitude
+- ViewPro A40 camera, 1080p resolution, various zoom levels
+- Extracted from video frames and still images
+
+# Target Classes
+- Footpaths / trails (linear features on snow, mud, forest floor)
+- Fresh footpaths (distinct edges, undisturbed surroundings, recent track marks)
+- Stale footpaths (partially covered by snow/vegetation, faded edges)
+- Concealed structures: branch pile hideouts, dugout entrances, squared/circular openings
+- Tree rows (potential concealment lines)
+- Open clearings connected to paths (FPV launch points)
+
+# YOLO Primitive Classes (new)
+- Black entrances to hideouts (various sizes)
+- Piles of tree branches
+- Footpaths
+- Roads
+- Trees, tree blocks
+
+# Annotation Format
+- Managed by existing annotation tooling in separate repository
+- Expected: bounding boxes and/or segmentation masks depending on model architecture
+- Footpaths may require polyline or segmentation annotation rather than bounding boxes
+
+# Seasonal Coverage Required
+- Winter: snow-covered terrain (footpaths as dark lines on white)
+- Spring: mud season (footpaths as compressed/disturbed soil)
+- Summer: full vegetation (paths through grass/undergrowth)
+- Autumn: mixed leaf cover, partial snow
+
+# Volume
+- Target: hundreds to thousands of annotated images
+- Available effort: 1.5 months, 5 hours/day
+- Potential for annotation process automation
+
+# Reference Examples
+- semantic01.png — footpath leading to branch-pile hideout in winter forest
+- semantic02.png — footpath to FPV launch clearing, branch mass at forest edge
+- semantic03.png — footpath to squared hideout structure
+- semantic04.png — footpath terminating at tree-branch concealment