Model: sabaridsnfuji/HouseCADDesignObjectDetection
Author: sabaridsnfuji
Tags: onnx, object_detection, license:apache-2.0, model-index, region:us
Card metadata: license: apache-2.0
metrics: precision
base_model: Ultralytics/YOLO11s
tags: object_detection
model-index: name: Object Detection Model
results: task: type: object-detection
dataset: name: Custom Object Dataset
type: object-detection
metrics: name: Box(P)
type: precision
value: 0.904
verified: no, name: R
type: recall
value: 0.87
verified: no, name: mAP50
type: mAP
value: 0.918
verified: no, name: mAP50-95
type: mAP
value: 0.671
verified: no
details: class: name: all
images: 92
instances: 2568
metrics: Box(P): 0.904, R: 0.87, mAP50: 0.918, mAP50-95: 0.671, class: name: range
images: 82
instances: 82
metrics: Box(P): 0.928, R: 0.938, mAP50: 0.957, mAP50-95: 0.701, class: name: entry_door
images: 92
instances: 821
metrics: Box(P): 0.941, R: 0.944, mAP50: 0.966, mAP50-95: 0.704, class: name: kitchen_sink
images: 80
instances: 91
metrics: Box(P): 0.863, R: 0.828, mAP50: 0.917, mAP50-95: 0.662, class: name: bathroom_sink
images: 89
instances: 240
metrics: Box(P): 0.909, R: 0.85, mAP50: 0.929, mAP50-95: 0.64, class: name: toilet
images: 90
instances: 188
metrics: Box(P): 0.927, R: 0.904, mAP50: 0.96, mAP50-95: 0.667, class: name: double_folding_door
images: 19
instances: 37
metrics: Box(P): 0.867, R: 0.702, mAP50: 0.828, mAP50-95: 0.594, class: name: window
images: 88
instances: 669
metrics: Box(P): 0.871, R: 0.9, mAP50: 0.905, mAP50-95: 0.582, class: name: shower
images: 61
instances: 70
metrics: Box(P): 0.907, R: 0.957, mAP50: 0.947, mAP50-95: 0.778, class: name: bathtub
images: 71
instances: 103
metrics: Box(P): 0.947, R: 0.874, mAP50: 0.933, mAP50-95: 0.793, class: name: single_folding_door
images: 55
instances: 144
metrics: Box(P): 0.877, R: 0.839, mAP50: 0.9, mAP50-95: 0.647, class: name: dishwasher
images: 49
instances: 54
metrics: Box(P): 0.912, R: 0.833, mAP50: 0.863, mAP50-95: 0.568, class: name: refrigerator
images: 66
instances: 69
metrics: Box(P): 0.901, R: 0.87, mAP50: 0.916, mAP50-95: 0.712
source: name: Custom Object Detection Results
url: https://example.com/custom-object-detection-results
Likes: 0 | All-time downloads: 0
Created: 2024-11-19 01:31:55