from mmdet.apis import init_detector, inference_detector, show_result_pyplot image = 'data/kitti_tiny/training/image_2/000066.jpeg' model = init_detector('retinanet_r18_fpn_1x_kitti.py', 'work_dirs/retinanet_r18_fpn_1x_kitti/latest.pth') result = inference_detector(model, image) show_...
device = 'cuda:0' model = init_detector(config_file, 'fcos_r50_caffe_fpn_gn-head_4x4_1x_coco_20200229-4c4fc3ad.pth', device=device) 加载图像并进行预测: img = mmcv.imread('https://github.com/open-mmlab/mmdetection/blob/master/demo/demo.jpg') result = inference_detector(model, img)...
为了查看模型的结构和参数,首先需要加载模型。在MMDetection中,模型通常是通过配置文件(config file)来定义的。以下是一个加载模型的示例代码: python from mmdet.apis import init_detector # 指定配置文件的路径 config_file = 'path/to/your/config_file.py' # 指定预训练模型权重文件的路径 checkpoint_file = ...
init_detector(config_file, checkpoint_file, device='cuda:0') # 测试单张图片并展示结果 img = os.path.join(base_dir, r'demo\demo.jpg') # 或者 img = mmcv.imread(img),这样图片仅会被读一次 result = inference_detector(model, img) # 在一个新的窗口中将结果可视化 model.show_result(img, ...
gt_bboxes, # gt_bboxes (list[Tensor]): 框的GT,shape:[tl_x, tl_y, br_x, br_y] (t代表上,l代表左,b代表下,r代表右) gt_labels, # gt_labels (list[Tensor]): Class indices corresponding to each box gt_bboxes_ignore=None): super(SingleStageDetector, self).forward_train(img, ...
importtorchfrommmdet.apisimportinit_detector,inference_detector# Load the model from config fileconfig_file='configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'checkpoint_file='checkpoints/faster_rcnn_r50_fpn_1x_coco.pth'model=init_detector(config_file,checkpoint_file,device='cuda:0') ...
apis import init_detector, inference_detector, show_result_pyplot model = init_detector('configs/my_config.py', 'checkpoints/my_model.pth', device='cuda:0') # 初始化模型 img = 'path/to/your/image.jpg' # 输入图像的路径 result = inference_detector(model, img) # 推理 show_result_pyplot...
『记录』简单调试mmdet3d的训练流程 调试流程 主要流程:train.py,train_model函数,train_detector函数,runner.run 在train.py主流程,和进入的train_detector中管理了外部事务。进入所构建的runner.run(),开始训练。 在mm
from mmdet.apis import inference_detector, init_detector File "/home/nvidia/zd/miniconda3/envs/py3810/lib/python3.8/site-packages/mmdet/apis/init.py", line 2, in from .det_inferencer import DetInferencer File "/home/nvidia/zd/miniconda3/envs/py3810/lib/python3.8/site-packages/mmdet/apis/...
importtorchfrommmdet.apisimportinit_detector,inference_detector,show_result_pyplot config_file='configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'checkpoint_file='checkpoints/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth'# 初始化模型model=init_detector(config_file,checkpoint_file,device='...