metainfo = { 'classes': ('class1','class2', 'class2',), 'palette': [ (220, 20, 60), (221, 11, 22),(221, 11, 42), ] }方案二:修改mmdet/evaluation/metrics 文件的内容,mmdet 是 python/site-package下的 mmdet1 修改 mmdet/evaluation/functional/class_names.py1...
create_meg_info首先解读数据集,整理成 python 的字典格式,其包括两个值:data_list和meta_info。然后...
create_meg_info首先解读数据集,整理成 python 的字典格式,其包括两个值:data_list和meta_info。然后...
ann_info = super().parse_ann_info(info) if ann_info is None: ann_info = dict() # 空实例 ann_info['gt_bboxes_3d'] = np.zeros((0, 7), dtype=np.float32) ann_info['gt_labels_3d'] = np.zeros(0, dtype=np.int64) # 过滤掉没有在训练中使用的类别 ann_info = self._remove_...
第十三个:Collect3D,这一步其实很简单,就是用于pipeline的最后一步,其根据我们初始化时候给它指定的meta_keys,为了我们具体的任务搞出来所需要的整顿好,把dict中我们已经存下的这么多东西进行自定义的收集,放入img_metas这个key中,其是一个包含了我们所收集的内容的DataContainer。
in create_input meta_data = _get_dataset_metainfo(self.model_cfg) File "C:\Users\user\anaconda3\envs\openmmlab\lib\site-packages\mmdeploy\codebase\mmpose\deploy\pose_detection.py", line 102, in _get_dataset_metainfo meta = dataset_mmpose._load_metainfo( File "d:\mmpose\mmpose\datasets...
forward([one_img], [[one_meta]], return_loss=False) batch_results.append(result) Example #4Source File: inference.py From AerialDetection with Apache License 2.0 5 votes def init_detector(config, checkpoint=None, device='cuda:0'): """Initialize a detector from config file. Args: config...
"""Call functions to load image and get image meta information. Args: results (dict): Result dict from :obj:`mmdet.CustomDataset`. Returns: dict: The dict contains loaded image and meta information. """ if self.file_client is None: ...
训练的时候,首先进入parse_data_info函数,然后调用parse_ann_info函数。其中的参数info是 读取的 pkl 格式。其中,METAINFO 根据自定义数据集的实际类别情况修改。下面 gt_bboxes_3d 也根据实际情况自行编写: gt_bboxes_3d=LiDARInstance3DBoxes(ann_info['gt_bboxes_3d'],box_dim=ann_info['gt_bboxes_3d...
metainfo=dict(classes=['Pedestrian', 'Cyclist', 'Car']), box_type_3d='LiDAR', backend_args=None)) test_dataloader = dict( batch_size=1, num_workers=1, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), ...