save_result.py

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[list] 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/benchmarks/mmdetection/voc0712/faster_rcnn_swin_fpn_voc0712ls_iter.py'#'./configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'
    # 训练好的模型
    checkpoint_file = './work_dirs/selfsup/densecl_resnet50_8xb32-coslr-200e_in1k_swin_pred_grid_num/20221213_161335_grid1/epoch_200.pth'#'./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 = '/media/ls/disk1/NWPU VHR-10 dataset 3/VOCdevkit/VOC2007/JPEGImages/'#'./data/val/'
    # 检测后存放图片路径
    out_dir = '/media/ls/disk1/NWPU VHR-10 dataset 3/result/'#'./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 ='/media/ls/disk1/NWPU VHR-10 dataset 3/VOCdevkit/VOC2007/ImageSets/Main/val.txt'# './val.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()