本文共 5254 字，大约阅读时间需要 17 分钟。

# -*- coding: utf-8 -*-import osimport sys, getoptfrom pycocotools.coco import COCO, maskUtilsimport cv2import numpy as npdef mkdir_os(path):    if not os.path.exists(path):        os.makedirs(path)def main(argv):    #json_file = './data/coco/annotations/instances_val2017.json'    #dataset_dir = './data/coco/val2017/'    #save_dir = './data/coco/vis/'    inputfile = ''    jsonfile = ''    outputfile = ''    try:        opts, args = getopt.getopt(argv,"hi:j:o:",["ifile=","jfile=","ofile="])    except getopt.GetoptError:        print('test.py -i 
   
     -j 
    
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      ')        sys.exit(2)    for opt, arg in opts:        if opt == '-h':            print('test.py -i 
      
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         ') sys.exit() elif opt in ("-i", "--ifile"): inputfile = arg elif opt in ("-j", "--jfile"): jsonfile = arg elif opt in ("-o", "--ofile"): outputfile = arg print('\n输入的文件为：', inputfile) print('\n输入的json为：', jsonfile) print('\n输出的文件为：', outputfile) mkdir_os(outputfile) coco = COCO(jsonfile) catIds = coco.getCatIds(catNms=['person']) # catIds=1 表示人这一类 imgIds = coco.getImgIds(catIds=catIds ) # 图片id，许多值 for i in range(len(imgIds)): if i%100 == 0: print(i,"/", len(imgIds)) img = coco.loadImgs(imgIds[i])[0] cvImage = cv2.imread(os.path.join(inputfile, img['file_name']), -1) cvImage = cv2.cvtColor(cvImage, cv2.COLOR_BGR2GRAY) cvImage = cv2.cvtColor(cvImage, cv2.COLOR_GRAY2BGR) annIds = coco.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None) anns = coco.loadAnns(annIds) polygons = [] color = [] for ann in anns: if 'segmentation' in ann: if type(ann['segmentation']) == list: # polygon for seg in ann['segmentation']: poly = np.array(seg).reshape((int(len(seg) / 2), 2)) poly_list = poly.tolist() polygons.append(poly_list) else: exit() print("-------------") # mask t = imgIds[ann['image_id']] if type(ann['segmentation']['counts']) == list: rle = maskUtils.frPyObjects([ann['segmentation']], t['height'], t['width']) else: rle = [ann['segmentation']] m = maskUtils.decode(rle) if ann['iscrowd'] == 1: color_mask = np.array([255, 0, 0]) if ann['iscrowd'] == 0: color_mask = np.array([255, 255, 0]) mask = m.astype(np.bool) cvImage[mask] = cvImage[mask] * 0.7 + color_mask * 0.3 point_size = 2 thickness = 2 for key in range(len(polygons)): ndata = polygons[key] for k in range(len(ndata)): data = ndata[k] cv2.circle(cvImage, (data[0], data[1]), point_size, (0, 255, 255), thickness) cv2.imwrite(os.path.join(outputfile, img['file_name']), cvImage)if __name__ == "__main__": main(sys.argv[1:])
        
       
      
     
    
   

修改版本：

# -*- coding: utf-8 -*-import osimport sys, getoptfrom pycocotools.coco import COCO, maskUtilsimport cv2import numpy as npdef mkdir_os(path):    if not os.path.exists(path):        os.makedirs(path)def main(argv):    # json_file = './data/coco/annotations/instances_val2017.json'    # dataset_dir = './data/coco/val2017/'    # save_dir = './data/coco/vis/'    inputfile = ''    jsonfile = ''    outputfile = ''    try:        opts, args = getopt.getopt(argv, "hi:j:o:", ["ifile=", "jfile=", "ofile="])    except getopt.GetoptError:        print('test.py -i 
   
     -j 
    
      -o 
     
      ')        sys.exit(2)    for opt, arg in opts:        if opt == '-h':            print('test.py -i 
      
        -j 
       
         -o 
        
         ') sys.exit() elif opt in ("-i", "--ifile"): inputfile = arg elif opt in ("-j", "--jfile"): jsonfile = arg elif opt in ("-o", "--ofile"): outputfile = arg print('\n输入的文件为：', inputfile) print('\n输入的json为：', jsonfile) print('\n输出的文件为：', outputfile) mkdir_os(outputfile) coco = COCO(jsonfile) catIds = coco.getCatIds(catNms=['wires']) # catIds=1 表示人这一类 imgIds = coco.getImgIds(catIds=catIds) # 图片id，许多值 for i in range(len(imgIds)): if i % 100 == 0: print(i, "/", len(imgIds)) img = coco.loadImgs(imgIds[i])[0] cvImage = cv2.imread(os.path.join(inputfile, img['file_name']), -1) cvImage = cv2.cvtColor(cvImage, cv2.COLOR_BGR2GRAY) cvImage = cv2.cvtColor(cvImage, cv2.COLOR_GRAY2BGR) annIds = coco.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None) anns = coco.loadAnns(annIds) polygons = [] color = [] for ann in anns: if 'segmentation' in ann: if type(ann['segmentation']) == list: # polygon for seg in ann['segmentation']: poly = np.array(seg).reshape((int(len(seg) / 2), 2)) poly_list = poly.tolist() polygons.append(poly_list) if ann['iscrowd'] == 0: color.append([0, 0, 255]) if ann['iscrowd'] == 1: color.append([0, 255, 255]) else: exit() print("-------------") # mask t = imgIds[ann['image_id']] if type(ann['segmentation']['counts']) == list: rle = maskUtils.frPyObjects([ann['segmentation']], t['height'], t['width']) else: rle = [ann['segmentation']] m = maskUtils.decode(rle) if ann['iscrowd'] == 0: color_mask = np.array([0, 0, 255]) if ann['iscrowd'] == 1: color_mask = np.array([0, 255, 255]) mask = m.astype(np.bool) cvImage[mask] = cvImage[mask] * 0.7 + color_mask * 0.3 point_size = 2 thickness = 2 for key in range(len(polygons)): ndata = polygons[key] cur_color = color[key] for k in range(len(ndata)): data = ndata[k] cv2.circle(cvImage, (data[0], data[1]), point_size, (cur_color[0], cur_color[1], cur_color[2]), thickness) cv2.imwrite(os.path.join(outputfile, img['file_name']), cvImage)if __name__ == "__main__": main(sys.argv[1:])
        
       
      
     
    
   

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