detections-semantic/_docs/00_problem/input_data/data_parameters.md

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