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HouseCADDesignObjectDetection

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object_detection
Eval Results
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ metrics:
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+ - precision
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+ base_model:
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+ - Ultralytics/YOLO11s
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+ tags:
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+ - object_detection
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+ model-index:
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+ - name: Object Detection Model
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+ results:
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+ - task:
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+ type: object-detection
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+ dataset:
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+ name: Custom Object Dataset
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+ type: object-detection
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+ metrics:
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+ - name: Box(P)
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+ type: precision
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+ value: 0.904
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+ - name: R
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+ type: recall
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+ value: 0.87
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+ - name: mAP50
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+ type: mAP
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+ value: 0.918
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+ - name: mAP50-95
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+ type: mAP
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+ value: 0.671
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+ details:
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+ - class:
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+ name: all
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+ images: 92
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+ instances: 2568
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+ metrics:
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+ - Box(P): 0.904
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+ - R: 0.87
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+ - mAP50: 0.918
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+ - mAP50-95: 0.671
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+ - class:
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+ name: range
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+ images: 82
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+ instances: 82
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+ metrics:
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+ - Box(P): 0.928
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+ - R: 0.938
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+ - mAP50: 0.957
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+ - mAP50-95: 0.701
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+ - class:
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+ name: entry_door
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+ images: 92
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+ instances: 821
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+ metrics:
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+ - Box(P): 0.941
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+ - R: 0.944
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+ - mAP50: 0.966
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+ - mAP50-95: 0.704
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+ - class:
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+ name: kitchen_sink
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+ images: 80
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+ instances: 91
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+ metrics:
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+ - Box(P): 0.863
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+ - R: 0.828
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+ - mAP50: 0.917
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+ - mAP50-95: 0.662
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+ - class:
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+ name: bathroom_sink
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+ images: 89
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+ instances: 240
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+ metrics:
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+ - Box(P): 0.909
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+ - R: 0.85
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+ - mAP50: 0.929
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+ - mAP50-95: 0.64
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+ - class:
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+ name: toilet
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+ images: 90
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+ instances: 188
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+ metrics:
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+ - Box(P): 0.927
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+ - R: 0.904
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+ - mAP50: 0.96
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+ - mAP50-95: 0.667
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+ - class:
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+ name: double_folding_door
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+ images: 19
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+ instances: 37
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+ metrics:
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+ - Box(P): 0.867
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+ - R: 0.702
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+ - mAP50: 0.828
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+ - mAP50-95: 0.594
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+ - class:
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+ name: window
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+ images: 88
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+ instances: 669
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+ metrics:
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+ - Box(P): 0.871
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+ - R: 0.9
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+ - mAP50: 0.905
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+ - mAP50-95: 0.582
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+ - class:
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+ name: shower
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+ images: 61
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+ instances: 70
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+ metrics:
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+ - Box(P): 0.907
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+ - R: 0.957
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+ - mAP50: 0.947
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+ - mAP50-95: 0.778
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+ - class:
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+ name: bathtub
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+ images: 71
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+ instances: 103
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+ metrics:
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+ - Box(P): 0.947
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+ - R: 0.874
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+ - mAP50: 0.933
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+ - mAP50-95: 0.793
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+ - class:
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+ name: single_folding_door
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+ images: 55
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+ instances: 144
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+ metrics:
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+ - Box(P): 0.877
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+ - R: 0.839
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+ - mAP50: 0.9
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+ - mAP50-95: 0.647
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+ - class:
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+ name: dishwasher
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+ images: 49
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+ instances: 54
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+ metrics:
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+ - Box(P): 0.912
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+ - R: 0.833
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+ - mAP50: 0.863
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+ - mAP50-95: 0.568
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+ - class:
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+ name: refrigerator
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+ images: 66
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+ instances: 69
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+ metrics:
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+ - Box(P): 0.901
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+ - R: 0.87
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+ - mAP50: 0.916
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+ - mAP50-95: 0.712
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+ source:
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+ name: Custom Object Detection Results
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+ url: https://example.com/custom-object-detection-results
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+ ---