def predict(self, x):
"""Run forward on given images and decode raw prediction into bboxes
Returns: bboxes, scores, classes
"""
class_outputs, box_outputs = self.forward(x)
anchors = box_utils.generate_anchors_boxes(x.shape[-2:])[0]
return box_utils.decode(class_outputs, box_outputs, anchors)
def predict(self, x):
"""
Run forward on given images and decode raw prediction into bboxes
Returns:
torch.Tensor with bboxes, scores and classes. bboxes in `lrtb` format
shape [BS, MAX_DETECTION_PER_IMAGE, 6]
"""
class_outputs, box_outputs = self.forward(x)
anchors = box_utils.generate_anchors_boxes(x.shape[-2:])[0]
return box_utils.decode(class_outputs, box_outputs, anchors)