【mmdetection】mmdetection批量推理图片并保存到文件夹

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 # plt.figure(figsize=fig_size) # plt.imshow(mmcv.bgr2rgb(img)) # plt.show() def main(): # config文件 config_file = './configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' # 训练好的模型 checkpoint_file = './work_dirs/faster_rcnn_r50_fpn_1x_coco/epoch_200.pth' # model = init_detector(config_file, checkpoint_file) model = init_detector(config_file, checkpoint_file, device='cuda:0') # 图片路径 img_dir = './data/coco/val2017/' # 检测后存放图片路径 out_dir = './faster_rcnn_result/' if not os.path.exists(out_dir): os.mkdir(out_dir) # 测试集的图片名称txt test_path = './img.txt' fp = open(test_path, 'r') test_list = fp.readlines() count = 0 imgs = [] for test in test_list: test = test.replace('\n', '') test = test.split('.')[0] # 如果test里面内容的名字是xxx.jpg,需要这行语句,是因为生成的图片会出现.jpg.jpg,否则不需要。 name = img_dir + test + '.jpg' count += 1 print('model is processing the {}/{} images.'.format(count, len(test_list))) # result = inference_detector(model, name) # model = init_detector(config_file, checkpoint_file, device='cuda:0') result = inference_detector(model, name) img = show_result_pyplot(model, name, result, score_thr=0.8) cv2.imwrite("{}/{}.jpg".format(out_dir, test), img) if __name__ == '__main__': main()

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原文链接:https://blog.csdn.net/wxd1233/article/details/123022877

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