如何从带有图像注释的CSV文件中提取值，并将它们附加到Python中RetinaNet的新CSV文件中？

我正在尝试将VGG图像注释器软件中的csv文件转换为可在RetinaNet中使用的csv文件。我需要的视网膜网训练数据格式是：path/to/image.jpg，x1，y1，x2，y2，class_name。这是我的CSV文件示例，来自VIA： +=============+===========+==============+===========+========================================================+===+ |文件名|文件大小|区域计数|区域id |区域形状|属性|| +=============+===========+==============+===========+========================================================+===+ |img-30.png | 2331731 | 10 | 0 |{名称：rect，x:65，y:778，宽度：108，高度：65}| +-------+------+-------+------+----------------------------+--+

基本上，我需要从括号中提取x、y、width和height属性，并将它们附加到列表中。这是我的python代码：

import csv

via_path = 'data/tiled/via.csv'

image_annotations = []

with open(via_path, "r") as f:
    reader = csv.reader(f, delimiter=",")
    for line in reader: 
        if '#' in line[0][0]:
            # bypassing comments in csv
            continue
        filename = line[1][2:-2]
        # strip brackets, split and get only the values we care about, then convert all the string to int 
        top_left_x, top_left_y, width, height = list(map(int,list(map(float, line[4].strip('][').split(',')[1:]))))

        if width == 0 or height == 0:
            continue

        # move from top left and width/height to x and y values
        if top_left_x < 0:
            top_left_x = 1
        if top_left_y < 0:
            top_left_y = 1
        x1 = top_left_x
        x2 = top_left_x + width
        y1 = top_left_y
        y2 = top_left_y + height 

        # TODO didn't add names this time since it is all one class
        name = "bird"

        # create the csv row
        new_row = []
        new_row.append(filename)
        new_row.append(x1)
        new_row.append(y1)
        new_row.append(x2)
        new_row.append(y2)
        new_row.append(name)

        image_annotations.append(new_row)

区域\形状\属性列是一个JSON字符串。您需要对其进行解析，以获取其包含的值

Python具有内置的JSON支持：

import json

# ... open CSV file, for each record ...

    shape = json.parse(line[4])

    top_left_x = shape['x']
    top_left_y = shape['y']
    # etc

import json

# ... open CSV file, for each record ...

    shape = json.parse(line[4])

    top_left_x = shape['x']
    top_left_y = shape['y']
    # etc