Source code for mmdet.models.detectors.cascade_rcnn

from ..builder import DETECTORS
from .two_stage import TwoStageDetector

[docs]@DETECTORS.register_module() class CascadeRCNN(TwoStageDetector): r"""Implementation of `Cascade R-CNN: Delving into High Quality Object Detection <>`_""" def __init__(self, backbone, neck=None, rpn_head=None, roi_head=None, train_cfg=None, test_cfg=None, pretrained=None, init_cfg=None): super(CascadeRCNN, self).__init__( backbone=backbone, neck=neck, rpn_head=rpn_head, roi_head=roi_head, train_cfg=train_cfg, test_cfg=test_cfg, pretrained=pretrained, init_cfg=init_cfg)
[docs] def show_result(self, data, result, **kwargs): """Show prediction results of the detector. Args: data (str or np.ndarray): Image filename or loaded image. result (Tensor or tuple): The results to draw over `img` bbox_result or (bbox_result, segm_result). Returns: np.ndarray: The image with bboxes drawn on it. """ if self.with_mask: ms_bbox_result, ms_segm_result = result if isinstance(ms_bbox_result, dict): result = (ms_bbox_result['ensemble'], ms_segm_result['ensemble']) else: if isinstance(result, dict): result = result['ensemble'] return super(CascadeRCNN, self).show_result(data, result, **kwargs)