fpn_1x_coco_20200130-047c8118.pth', device='cuda:0') # 测试单张图片 img = 'demo/demo.jpg' # 或者使用mmcv.imread(img)来读取图片 result = inference_detector(model, img) # 显示结果 # 注意:你可能需要安装matplotlib或其他库来显示图像 # model.show_result(img, result, out_file='result....
result = inference_detector(model, img) img = mmcv.imconvert(img, 'bgr', 'rgb') visualizer.add_datasample( name='result', image=img, data_sample=result, draw_gt=False, pred_score_thr=0.3, show=False) img = visualizer.get_image() ...
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) show_result_pyplot(m...
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='...
model = 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...
# Test a single imageimg='test.jpg'result=inference_detector(model,img)# Visualize the resultsmodel.show_result(img,result,out_file='result.jpg') 1. 2. 3. 4. 5. 6. 在这个示例中,我们首先导入 MMDetection API,加载预训练模型,并对一张图像进行推理。结果将保存在result.jpg中。
--show --dump-info I have updated the mmdeploy code to latest, and I have checked my TensorRT installtion, and ran sampleMNIST successfully (the running result is fail, but got no error). I didn't know how to fix it. Thanks a lot. ...
result = inference_detector(model, frame, test_pipeline=test_pipeline) 这一行其实和对单张图片的检测是一样的,frame是一帧,可以看为一张图片,只不过多了 test_pipeline import cv2 from mmcv.transforms import Compose from mmengine.utils import track_iter_progress # Test a video and show the result...
!python tools/analysis_tools/analyze_results.py \ configs/faster_rcnn/faster-rcnn_r50_fpn_2x_voc.py \ work_dirs/faster-rcnn_r50_fpn_2x_voc/result_epoch_24.pkl \ work_dirs/faster-rcnn_r50_fpn_2x_voc/analyze_results \ --show 如果想过过滤低评分的预测,可以修改--show-score-thr 0.6 默...
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(model, img, result) # ...