Question

我想创建一个具有以下格式的JSON文件：

{
        fid: {
            "filename": "",
            "size": -1,
            "regions": [
                 "shape_attributes": {
                    "name": "polyline",
                    "all_points_x": [],
                    "all_points_y": []
                } ,
                 "shape_attributes": {
                 "name": "polyline",
                 "all_points_x": [],
                 "all_points_y": []
            }
            "file_attributes": {}
        },
        "region_attributes": {}
    },
       fid: {
            "filename": "",
            "size": -1,
            "regions": [
                 "shape_attributes": {
                    "name": "polyline",
                    "all_points_x": [],
                    "all_points_y": []
                } ,
                 "shape_attributes": {
                 "name": "polyline",
                 "all_points_x": [],
                 "all_points_y": []
            }
            "file_attributes": {}
        },
        "region_attributes": {}
    }
}

对于区域而言，这很容易。由于它是shape_attributes个对象的数组，因此我只用了append()来添加它。但是我需要在整个{}

中使用

如何创建一个像这样的空json文件：data = {}，然后将总计fid附加到其中？我尝试了这种方法，但出现错误：

AttributeError: 'dict' object has no attribute 'append'

这是我正在运行的代码：

import json
from tqdm import tqdm
from os import path, mkdir, listdir
im = '/home/luiscosta/PycharmProjects/wsi_preprocessing/nn_models/Unet/dsb2018_topcoders/selim/result/pred_resnet101_full_masks/1_0.jpeg'
import numpy as np
import cv2
import matplotlib.pyplot as plt

img = cv2.imread(
    '/home/luiscosta/PycharmProjects/wsi_preprocessing/nn_models/Unet/dsb2018_topcoders/selim/result/pred_resnet101_full_masks/1_0.jpeg')
original = '/home/luiscosta/PycharmProjects/wsi_preprocessing/nn_models/Unet/dsb2018_topcoders/data_test/1_0.jpeg'
# mask = np.zeros(20000, dtype=np.uint8).reshape(100, 200)
img_original = cv2.imread(
    '/home/luiscosta/PycharmProjects/wsi_preprocessing/nn_models/Unet/dsb2018_topcoders/data_test/1_0.jpeg',
    cv2.IMREAD_COLOR)
test_folder = '/home/luiscosta/PycharmProjects/wsi_preprocessing/nn_models/Unet/dsb2018_topcoders/selim/result/pred_resnet101_full_masks'

total_annotations = {} #I want this to work
for d in tqdm(listdir(test_folder)):

    fid = d
    annotation = {
        fid: {
            "filename": "",
            "size": -1,
            "regions": [],
            "file_attributes": {}
        },
        "region_attributes": {}
    }
    img = cv2.imread(path.join(test_folder, '{0}'.format(fid)))

    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    # define range of blue color in HSV
    lower_blue = np.array([110, 50, 50])
    upper_blue = np.array([130, 255, 255])
    # Threshold the HSV image to get only blue colors
    mask = cv2.inRange(hsv, lower_blue, upper_blue)
    blue_only = cv2.bitwise_and(img, img, mask=mask)

    im2, contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    for i, cnt in enumerate(contours):

        cv2.drawContours(img_original, cnt, -1, (0, 0, 255), 1)
        cv2.putText(blue_only, str(i), (cnt[0][0][0], cnt[0][0][1]), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 1)
        total_x = []
        total_y = []
        for cn in cnt:
            total_x.append(int(cn[0][0]))
            total_y.append(int(cn[0][1]))
            shape_attributes = {
                "shape_attributes": {
                    "name": "polyline",
                    "all_points_x": [],
                    "all_points_y": []
                }
            }
            # print(total_x)
            # print(contours[0][0])
            # print(total_x)
            shape_attributes["shape_attributes"]["all_points_x"] = total_x
            shape_attributes["shape_attributes"]["all_points_y"] = total_y
            annotation[fid]["regions"].append(shape_attributes)
            annotation[fid]["filename"] = fid
    total_annotations.append(annotation)

with open('data_start.json', 'w+', encoding='utf-8') as outfile:
    json.dump(total_annotations, outfile, indent=4)

将JSON文件初始化为{}

0 个答案: