AI代码解释 from mmdet.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'device='cuda:0'# 初始化检测器 model=init_detector(config_file,...
img='path/to/test/image.jpg'# 图片路径 result=inference_detector(model,img)# 可视化结果show_result_pyplot(model,img,result)# 如果你需要批量处理图片,可以使用以下代码 # images=['path/to/image1.jpg','path/to/image2.jpg',...]#forimginimages:# result=inference_detector(model,img)#show_resu...
result = inference_detector(model, img) #bbox_result, mask_result = result # 现实检测结果 show_result_pyplot(model, img, result, score_thr=0.3) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 3.对比自己的验证集标...
show_result_pyplot import cv2 # 加载模型和配置文件 model = init_detector('configs/myconfig.py', 'checkpoints/last.pth', device='cuda:0') # 读取测试图片 img = cv2.imread('test.jpg') # 推理并可视化结果 result = inference_detector(model, img) show_result_pyplot(model, img, result, scor...
frommmdet.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' device='cuda:0' ...
Can;t find show_result_pyplot in mmdet.apis, is there any way I can use the api. my mmdet version is v3.1.0
模型的配置文件模型文件需要进行推理的图片或者视频 详细的代码如下: from mmdet.apis import init_detector, inference_detector, show_result_pyplotimport mmcvconfig_file = '../configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'# download the checkpoint from model zoo and put it in `checkpoints/...
_coco_20200130-047c8118.pth'# build the model from a config file and a checkpoint filemodel = init_detector(config_file, checkpoint_file, device='cuda:0')# test a single imageimg ='demo.jpg'result = inference_detector(model, img)# show the resultsshow_result_pyplot(model, img, result...
#load tensorboard in colab%load_ext tensorboard#see curves in tensorboard%tensorboard --logdir ./tutorial_exps 测试经过训练的检测器 img = mmcv.imread('balloon/train/7178882742_f090f3ce56_k.jpg') model.cfg=cfg result=inference_detector(model, img) show_result_pyplot(model, img, result)...
安装好 mmdetection 之后,就想好好学学,现在就边学边记。先从最简单的模型推理开始,参考MMlab 的教程就好啦:https://github.com/open-mmlab/OpenMMLabCourse,清晰易懂! 首先试试RetinaNet: # mmdet常见的推理apifrommmdet.apisimportinit_detector,inference_detector,show_result_pyplot# mmcv是mmdet之类的通用库import...