문제
코드 입력 시,
'camvidPixelLabelIDs'은(는) Train and Deploy Fully Convolutional Networks for Semantic Segmentation에 사용되었습니다.
오류 발생
해결 방법
코드 맨 하단에 지원함수 추가
function labelIDs = camvidPixelLabelIDs() % Return the label IDs corresponding to each class. % % The CamVid dataset has 32 classes. Group them into 11 classes following % the original SegNet training methodology [1]. % % The 11 classes are: % "Sky" "Building", "Pole", "Road", "Pavement", "Tree", "SignSymbol", % "Fence", "Car", "Pedestrian", and "Bicyclist". % % CamVid pixel label IDs are provided as RGB color values. Group them into % 11 classes and return them as a cell array of M-by-3 matrices. The % original CamVid class names are listed alongside each RGB value. Note % that the Other/Void class are excluded below. labelIDs = { ... % "Sky" [ 128 128 128; ... % "Sky" ] % "Building" [ 000 128 064; ... % "Bridge" 128 000 000; ... % "Building" 064 192 000; ... % "Wall" 064 000 064; ... % "Tunnel" 192 000 128; ... % "Archway" ] % "Pole" [ 192 192 128; ... % "Column_Pole" 000 000 064; ... % "TrafficCone" ] % Road [ 128 064 128; ... % "Road" 128 000 192; ... % "LaneMkgsDriv" 192 000 064; ... % "LaneMkgsNonDriv" ] % "Pavement" [ 000 000 192; ... % "Sidewalk" 064 192 128; ... % "ParkingBlock" 128 128 192; ... % "RoadShoulder" ] % "Tree" [ 128 128 000; ... % "Tree" 192 192 000; ... % "VegetationMisc" ] % "SignSymbol" [ 192 128 128; ... % "SignSymbol" 128 128 064; ... % "Misc_Text" 000 064 064; ... % "TrafficLight" ] % "Fence" [ 064 064 128; ... % "Fence" ] % "Car" [ 064 000 128; ... % "Car" 064 128 192; ... % "SUVPickupTruck" 192 128 192; ... % "Truck_Bus" 192 064 128; ... % "Train" 128 064 064; ... % "OtherMoving" ] % "Pedestrian" [ 064 064 000; ... % "Pedestrian" 192 128 064; ... % "Child" 064 000 192; ... % "CartLuggagePram" 064 128 064; ... % "Animal" ] % "Bicyclist" [ 000 128 192; ... % "Bicyclist" 192 000 192; ... % "MotorcycleScooter" ] }; end |
