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Source code for mmdet.models.detectors.yolo

# Copyright (c) OpenMMLab. All rights reserved.
# Copyright (c) 2019 Western Digital Corporation or its affiliates.
import torch

from ..builder import DETECTORS
from .single_stage import SingleStageDetector


[docs]@DETECTORS.register_module() class YOLOV3(SingleStageDetector): def __init__(self, backbone, neck, bbox_head, train_cfg=None, test_cfg=None, pretrained=None, init_cfg=None): super(YOLOV3, self).__init__(backbone, neck, bbox_head, train_cfg, test_cfg, pretrained, init_cfg)
[docs] def onnx_export(self, img, img_metas): """Test function for exporting to ONNX, without test time augmentation. Args: img (torch.Tensor): input images. img_metas (list[dict]): List of image information. Returns: tuple[Tensor, Tensor]: dets of shape [N, num_det, 5] and class labels of shape [N, num_det]. """ x = self.extract_feat(img) outs = self.bbox_head.forward(x) # get shape as tensor img_shape = torch._shape_as_tensor(img)[2:] img_metas[0]['img_shape_for_onnx'] = img_shape det_bboxes, det_labels = self.bbox_head.onnx_export(*outs, img_metas) return det_bboxes, det_labels
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