It’s quite common for algorithms to be unable to work with a palette based image. The convert in the above changes it to have a full RGB value at each pixel location. 大致翻译如下：在算法中，不能处理一个调色板图像很正常。这种“转换”需要在每一个像素点有全RGB值。 所以对应修改代码如下:
import random
from pyecharts import options as opts
from pyecharts.charts import Bar3D
x_data = y_data = list(range(10))
def generate_data():
data = []
for j in range(10):
for k in range(10):
value = random.randint(0, 9)
data.append([j, k, value * 2 + 4])
return data
bar3d = Bar3D()
for _ in range(10):
bar3d.add(
"",
generate_data(),
shading="lambert",
xaxis3d_opts=opts.Axis3DOpts(data=x_data, type_="value"),
yaxis3d_opts=opts.Axis3DOpts(data=y_data, type_="value"),
zaxis3d_opts=opts.Axis3DOpts(type_="value"),
)
bar3d.set_global_opts(title_opts=opts.TitleOpts("Bar3D-堆叠柱状图示例"))
bar3d.set_series_opts(**{"stack": "stack"})
bar3d.render("bar3d_stack.html")
3D柱状图
6、饼图
from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.commons.utils import JsCode
fn = """
function(params) {
if(params.name == '其他')
return '\\n\\n\\n' + params.name + ' : ' + params.value + '%';
return params.name + ' : ' + params.value + '%';
}
"""
def new_label_opts():
return opts.LabelOpts(formatter=JsCode(fn), position="center")
c = (
Pie()
.add(
"",
[list(z) for z in zip(["剧情", "其他"], [25, 75])],
center=["20%", "30%"],
radius=[60, 80],
label_opts=new_label_opts(),
)
.add(
"",
[list(z) for z in zip(["奇幻", "其他"], [24, 76])],
center=["55%", "30%"],
radius=[60, 80],
label_opts=new_label_opts(),
)
.add(
"",
[list(z) for z in zip(["爱情", "其他"], [14, 86])],
center=["20%", "70%"],
radius=[60, 80],
label_opts=new_label_opts(),
)
.add(
"",
[list(z) for z in zip(["惊悚", "其他"], [11, 89])],
center=["55%", "70%"],
radius=[60, 80],
label_opts=new_label_opts(),
)
.set_global_opts(
title_opts=opts.TitleOpts(title="Pie-多饼图基本示例"),
legend_opts=opts.LegendOpts(
type_="scroll", pos_top="20%", pos_left="80%", orient="vertical"
),
)
.render("mutiple_pie.html")
)
OpenCV是一个基于BSD许可（开源）发行的跨平台计算机视觉和机器学习软件库，可以运行在Linux、Windows、Android和Mac OS操作系统上。 它轻量级而且高效——由一系列 C 函数和少量 C++ 类构成，同时提供了Python、Ruby、MATLAB等语言的接口，实现了图像处理和计算机视觉方面的很多通用算法。
