fasterrcnn_mobilenet_v3_large_fpn¶
-
torchvision.models.detection.
fasterrcnn_mobilenet_v3_large_fpn
(pretrained=False, progress=True, num_classes=91, pretrained_backbone=True, trainable_backbone_layers=None, **kwargs)[source]¶ Constructs a high resolution Faster R-CNN model with a MobileNetV3-Large FPN backbone. It works similarly to Faster R-CNN with ResNet-50 FPN backbone. See
fasterrcnn_resnet50_fpn()
for more details.Example:
>>> model = torchvision.models.detection.fasterrcnn_mobilenet_v3_large_fpn(pretrained=True) >>> model.eval() >>> x = [torch.rand(3, 300, 400), torch.rand(3, 500, 400)] >>> predictions = model(x)
- Parameters
pretrained (bool) – If True, returns a model pre-trained on COCO train2017
progress (bool) – If True, displays a progress bar of the download to stderr
num_classes (int) – number of output classes of the model (including the background)
pretrained_backbone (bool) – If True, returns a model with backbone pre-trained on Imagenet
trainable_backbone_layers (int) – number of trainable (not frozen) resnet layers starting from final block. Valid values are between 0 and 6, with 6 meaning all backbone layers are trainable. If
None
is passed (the default) this value is set to 3.