sharp4= “AAV“ gap1= 0.0025805234909057617 gap2= 0.0010069608688354492 gap3= 0.0010012388229370117 sharp4 代表方向，A代表 1 ， V代表-1， gap1,gap2,gap3代表长度，请将方向和长度放入一个列表中， 形如【1，001】

好的，根据您的要求，经过处理后得到的列表为：[1, 258, 100, 100]。其中，第一个元素代表方向，A代表1，V代表-1；后续的三个元素代表长度，分别为0.0025805234909057617、0.0010069608688354492和0.0010012388229370117，经过转换后分别为258、100、100。最后三个元素的值需要乘以1000，去掉小数点之后再转为整型。

相关问题

from PIL import Image, ImageFilter img = Image.open("red1.jpg") img_gray = img.convert('L') img_sharp = img_gray.filter(ImageFilter.SHARPEN) sharpness = ImageStat.Stat(img_sharp).var[0] print("ruidu:", sharpness)报错NameError: name 'ImageStat' is not defined

这个错误是因为你没有导入ImageStat模块。请修改你的代码，添加导入ImageStat模块的语句：

from PIL import Image, ImageFilter, ImageStat

img = Image.open("red1.jpg")
img_gray = img.convert('L')
img_sharp = img_gray.filter(ImageFilter.SHARPEN)
sharpness = ImageStat.Stat(img_sharp).var[0]
print("锐度:", sharpness)

这样就可以顺利地计算图像的锐度了。

用opencvsharp编写函数实现以下功能 // 极值点评分 void Caliper::ExtremePointRating() { if(extremePoints.empty()) return; // 评分： value * (1 - |i - 0.5 * le| / 0.5 * len) int halfLen = static_cast<int>(path.size() / 2); for(auto& e: extremePoints) { e.score = e.value * (1 - static_cast<double>(std::abs(e.ps - halfLen)) / halfLen); } //按评分排序：降序 sort(extremePoints.begin(), extremePoints.end(), CompareExtremPointInfoBysocre); result.peak = extremePoints.at(0).pt; if(extremePoints.size() == 1) { result.center = result.front = result.back = extremePoints.at(0).pt; return; } if(extremePoints.size() == 2) { int a = std::abs(extremePoints.at(0).ps - halfLen); int b = std::abs(extremePoints.at(1).ps - halfLen); if(a > b) { result.front = result.back = extremePoints.at(0).pt; result.center = extremePoints.at(1).pt; }else { } }else { std::vector<ExtremPointInfo> epf(extremePoints.begin(), extremePoints.begin() + 3); sort(epf.begin(), epf.end(), CompareExtremPointInfoByPs);//降序 result.back = epf.at(0).pt; result.center = epf.at(1).pt; result.front = epf.at(2).pt; } }

以下是使用 OpenCvSharp3 编写的实现上述功能的代码：

using OpenCvSharp;
using System;
using System.Collections.Generic;
using System.Linq;

public class Caliper
{
    public void ExtremePointRating()
    {
        if (extremePoints.Count == 0)
            return;

        int halfLen = path.Count / 2;

        foreach (var e in extremePoints)
        {
            e.score = e.value * (1 - Math.Abs(e.ps - 0.5 * path.Count) / halfLen);
        }

        extremePoints.Sort(new CompareExtremPointInfoBysocre());

        result.peak = extremePoints[0].pt;

        if (extremePoints.Count == 1)
        {
            result.center = result.front = result.back = extremePoints[0].pt;
            return;
        }

        if (extremePoints.Count == 2)
        {
            int a = Math.Abs(extremePoints[0].ps - halfLen);
            int b = Math.Abs(extremePoints[1].ps - halfLen);

            if (a > b)
            {
                result.front = result.back = extremePoints[0].pt;
                result.center = extremePoints[1].pt;
            }
            else
            {
                result.front = result.back = extremePoints[1].pt;
                result.center = extremePoints[0].pt;
            }

            return;
        }

        var epf = extremePoints.Take(3).ToList();
        epf.Sort(new CompareExtremPointInfoByPs());

        result.back = epf[0].pt;
        result.center = epf[1].pt;
        result.front = epf[2].pt;
    }

    private class CompareExtremPointInfoBysocre : IComparer<ExtremPointInfo>
    {
        public int Compare(ExtremPointInfo x, ExtremPointInfo y)
        {
            return -x.score.CompareTo(y.score);
        }
    }

    private class CompareExtremPointInfoByPs : IComparer<ExtremPointInfo>
    {
        public int Compare(ExtremPointInfo x, ExtremPointInfo y)
        {
            return -x.ps.CompareTo(y.ps);
        }
    }
}

注意，由于缺少完整的代码，我无法保证此代码的完全正确性。因此，如果您在使用此代码时遇到任何问题，请自行进行调试和修改。