MedicalVision / detr_balloon_example

MedicalVision

Detección de objetos

Este modelo es un ejemplo de MedicalVision que utiliza DETR (Transformadores de detección de objetos) para detectar globos mediante un conjunto de datos de NIH y el modelo original de Facebook, detr-resnet-50. Ha sido entrenado para la detección de objetos y utiliza Safetensors para optimizar el almacenamiento del modelo.

Como usar

Cómo usar el modelo:
Original result

IoU metric: bbox
Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.018
Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.028
Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.018
Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.061
Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.031
Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.040
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.136
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.468
Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.393
Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.557
Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000

After training result

IoU metric: bbox
Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.581
Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.740
Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.661
Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.580
Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.722
Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.216
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.686
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.704
Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.615
Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.809
Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000

Funcionalidades

Detección de objetos
Transformadores
Safetensors
Puntos de inferencia

Casos de uso

Detección de globos en imágenes médicas
Detección de objetos en varias escalas