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nickmuchi
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yolos-small-finetuned-masks

Object Detection
Transformers
PyTorch
Safetensors
yolos
face-mask-detection
Inference Endpoints
Model card Files Community
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@@ -69,15 +69,16 @@ This model achieves an AP (average precision) of **53.1**.
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  Accumulating evaluation results...
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  DONE (t=0.14s).
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  IoU metric: bbox
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- Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.273
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- Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.532
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- Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.257
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- Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.220
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- Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341
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- Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.545
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.154
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.361
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.415
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.349
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- Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.469
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584
 
 
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  Accumulating evaluation results...
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  DONE (t=0.14s).
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  IoU metric: bbox
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+ ----------------
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+ Average Precision | (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.273 |
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+ Average Precision | (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.532 |
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+ Average Precision | (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.257 |
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+ Average Precision | (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.220 |
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+ Average Precision | (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.341 |
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+ Average Precision | (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.545 |
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+ Average Recall | (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.154 |
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+ Average Recall | (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.361 |
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+ Average Recall | (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.415 |
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+ Average Recall | (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.349 |
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+ Average Recall | (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.469 |
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+ Average Recall | (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 |