mmdetection2测试单张图片并保存

from argparse import ArgumentParser
import os
from mmdet.apis import inference_detector, init_detector  #, show_result_pyplot
import cv2
 
def show_result_pyplot(model, img, result, score_thr=0.3, fig_size=(15, 10)):
    """Visualize the detection results on the image.
    Args:
        model (nn.Module): The loaded detector.
        img (str or np.ndarray): Image filename or loaded image.
        result (tuple
or list): The detection result, can be either (bbox, segm) or just bbox. score_thr (float): The threshold to visualize the bboxes and masks. fig_size (tuple): Figure size of the pyplot figure. """ if hasattr(model, 'module'): model = model.module img = model.show_result(img, result, score_thr=score_thr, show=False) return img def main(): # config文件 config_file = '/root/mmdetection/work_dirs/faster_rcnn_r50_fpn_1x_coco/faster_rcnn_r50_fpn_1x_coco.py' # 训练好的模型 checkpoint_file = '/root/mmdetection/work_dirs/faster_rcnn_r50_fpn_1x_coco/latest.pth' # model = init_detector(config_file, checkpoint_file) model = init_detector(config_file, checkpoint_file, device='cuda:0') # 图片路径 name= '/root/mmdetection/data/coco/val2017/000088.jpg' # 检测后存放图片路径 out_dir = '/root/output/' if not os.path.exists(out_dir): os.mkdir(out_dir) result = inference_detector(model, name) img = show_result_pyplot(model, name, result, score_thr=0.8) #命名输出图片名称 cv2.imwrite("{}/{}.jpg".format(out_dir, 122), img) if __name__ == '__main__': main()

版权声明:本文为CSDN博主「一口大米饭」的原创文章,遵循CC 4.0 BY-SA版权协议,转载请附上原文出处链接及本声明。
原文链接:https://blog.csdn.net/m0_60360632/article/details/121554049

一口大米饭

我还没有学会写个人说明!

暂无评论

发表评论

相关推荐

yolov5训练数据集划分

yolov5训练数据集划分 按照默认8:1:1划分训练集,测试集,验证集。 txt文件出现在imageset文件夹。 import os import randomtrainval_pe

深度学习之目标检测YOLOv5

一.简介 YOLOV4出现之后不久,YOLOv5横空出世。YOLOv5在YOLOv4算法的基础上做了进一步的改进,检测性能得到进一步的提升。虽然YOLOv5算法并没有与YOLOv4算法进行性能比较与分析&#xff0