Python 将JSON坐标转换为numpy数组
我想将JSON文件转换回png图像或NumPy数组。 JSON文件由坐标和其他元数据的列表组成。举个例子。它看起来是这样的:Python 将JSON坐标转换为numpy数组,python,arrays,json,numpy,png,Python,Arrays,Json,Numpy,Png,我想将JSON文件转换回png图像或NumPy数组。 JSON文件由坐标和其他元数据的列表组成。举个例子。它看起来是这样的: "firstEditDate": "2019-12-02T19:05:45.393Z", "lastEditDate": "2020-06-30T13:21:33.371Z", "folder": "/Pictures/poly", "
"firstEditDate": "2019-12-02T19:05:45.393Z",
"lastEditDate": "2020-06-30T13:21:33.371Z",
"folder": "/Pictures/poly",
"objects": [
{
"classIndex": 5,
"layer": 0,
"polygon": [
{
"x": 0,
"y": 0
},
{
"x": 1699.7291626931146,
"y": 0
},
{
"x": 1699.7291626931146,
"y": 1066.87392714095
},
{
"x": 0,
"y": 1066.87392714095
}
],
},
{
"classIndex": 2,
"layer": 0,
"polygon": [
{
"x": 844.2300556586271,
"y": 711.8243676199173
},
{
"x": 851.156462585034,
"y": 740.5194820293175
},
{
"x": 854.1249226963513,
"y": 744.477428844407
},
{
"x": 854.1249226963513,
"y": 747.4458889557243
},
(创建阵列或图像之前,应将坐标四舍五入到最近的坐标)
阵列/图片的尺寸应为1727 x 971
python中是否有任何函数可以将文件转换为一个数组,该数组的值位于ClassIndex
的数组中?或者将每个ClassIndex
分配给特定颜色的图片中?这里有一个解决方案:
import matplotlib.pyplot as plt
import numpy as np
import mahotas.polygon as mp
json_dict = {
"firstEditDate": "2019-12-02T19:05:45.393Z",
"lastEditDate": "2020-06-30T13:21:33.371Z",
"folder": "/Pictures/poly",
"objects": [{
"classIndex": 1,
"layer": 0,
"polygon": [
{"x": 170, "y": 674},
{"x": 70, "y": 674},
{"x": 70, "y": 1120},
{"x": 870, "y": 1120},
{"x": 870, "y": 674},
{"x": 770, "y": 674},
{"x": 770, "y": 1020},
{"x": 170, "y": 1020},
],
}, {
"classIndex": 2,
"layer": 0,
"polygon": [
{"x": 220, "y": 870},
{"x": 220, "y": 970},
{"x": 720, "y": 970},
{"x": 720, "y": 870},
]
}, {
"classIndex": 3,
"layer": 0,
"polygon": [
{"x": 250, "y": 615},
{"x": 225, "y": 710},
{"x": 705, "y": 840},
{"x": 730, "y": 745},
]
}, {
"classIndex": 4,
"layer": 0,
"polygon": [
{"x": 350, "y": 380},
{"x": 300, "y": 465},
{"x": 730, "y": 710},
{"x": 780, "y": 630},
]
}, {
"classIndex": 5,
"layer": 0,
"polygon": [
{"x": 505, "y": 180},
{"x": 435, "y": 250},
{"x": 790, "y": 605},
{"x": 855, "y": 535},
]
}, {
"classIndex": 6,
"layer": 0,
"polygon": [
{"x": 700, "y": 30},
{"x": 615, "y": 80},
{"x": 870, "y": 515},
{"x": 950, "y": 465},
]
}]
}
canvas = np.zeros((1000,1150))
for obj in json_dict["objects"]:
pts = [(round(p["x"]),round(p["y"])) for p in obj["polygon"]]
mp.fill_polygon(pts, canvas, obj["classIndex"])
plt.imshow(canvas.transpose())
plt.colorbar()
plt.show()
输出:
mahotas.polygon似乎是您问题的解决方案。您可以使用它在numpy数组中绘制多边形(请参见中的samplebias答案),谢谢您的帮助!刚刚通过了mahotas图书馆。谢谢。当我为我的小狗使用代码时,我遇到了一个问题。当我将画布设置为具有形状(1727971)的数组时,我得到了
mp的索引错误。填充多边形索引器:索引1728超出了大小为1728的轴0的界限。你知道问题是什么吗?