The example gallery will be extended in the future to provide more comprehensive examples and serve as a reference for common torchvision tasks. For more details, refer to the documentation.
(Beta) New models for detection
SSD and SSDlite are two popular object detection architectures that are efficient in terms of speed and provide good results for low resolution pictures. In this release, we provide implementations for the original SSD model with VGG16 backbone and for its mobile-friendly variant SSDlite with MobileNetV3-Large backbone.
The models were pre-trained on COCO train2017 and can be used as follows:
```python
import torch
import torchvision
Original SSD variant
x = [torch.rand(3, 300, 300), torch.rand(3, 500, 400)]
m_detector = torchvision.models.detection.ssd300_vgg16(pretrained=True)
m_detector.eval()
predictions = m_detector(x)