Shortcuts

KeypointDetector

class flash.image.keypoint_detection.model.KeypointDetector(num_keypoints, num_classes=2, backbone='resnet18_fpn', head='keypoint_rcnn', pretrained=True, optimizer='Adam', lr_scheduler=None, learning_rate=0.0005, output=None, predict_kwargs=None, **kwargs)[source]

The KeypointDetector is a Task for detecting keypoints in images. For more details, see Keypoint Detection.

Parameters
  • num_keypoints (int) – Number of keypoints to detect.

  • num_classes (int) – The number of keypoint classes.

  • backbone (Optional[str]) – String indicating the backbone CNN architecture to use.

  • head (Optional[str]) – String indicating the head module to use on top of the backbone.

  • pretrained (bool) – Whether the model should be loaded with it’s pretrained weights.

  • optimizer (~OPTIMIZER_TYPE) – Optimizer to use for training.

  • lr_scheduler (Optional[~LR_SCHEDULER_TYPE]) – The LR scheduler to use during training.

  • learning_rate (float) – The learning rate to use for training.

  • output (Optional[~OUTPUT_TYPE]) – The Output to use when formatting prediction outputs.

  • predict_kwargs (Optional[Dict]) – dictionary containing parameters that will be used during the prediction phase.

  • **kwargs – additional kwargs used for initializing the task

property predict_kwargs: Dict[str, Any]

The kwargs used for the prediction step.

Return type

Dict[str, Any]

Read the Docs v: stable
Versions
latest
stable
0.6.0
0.5.2
0.5.1
0.5.0
0.4.0
0.3.2
0.3.1
0.3.0
0.2.3
0.2.2
0.2.1
0.2.0
0.1.0post1
docs-fix_typing
Downloads
pdf
html
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.