小编Sin*_*Lok的帖子

如何将Bitmap转换为Base64字符串

我正在开发一个Android应用程序,它将Base64图像的字符串上传到Web服务器.因此,我使用以下代码将Bitmap转换为Base64String.

public String getEncoded64ImageStringFromBitmap(Bitmap bitmap) {
    ByteArrayOutputStream stream = new ByteArrayOutputStream();
    bitmap.compress(Bitmap.CompressFormat.PNG, 100, stream);
    byte[] byteFormat = stream.toByteArray();
    String imgString = Base64.encodeToString(byteFormat, Base64.NO_WRAP);
    return imgString;
}
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例如,我需要转换此图像.转换后,我没有Base64像我预期的那样得到String.

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它应该是真正的Base64字符串(我用这个网站转换)

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我的转换有什么问题?谢谢 !

base64 android bitmap

14
推荐指数
2
解决办法
2万
查看次数

卡尔曼滤波器总是在第一时间预测 0,0

以下代码用于从下到上扫描图像。然而,卡尔曼滤波器的预测在第一次时总是显示0,0。这样,它就会从底部到 0,0 绘制一条线。如何使路径(卡尔曼滤波器)更接近实际路径?

以下代码和图像已更新。

import cv2
import matplotlib.pyplot as plt
import numpy as np

img = cv2.imread('IMG_4614.jpg',1)
img = cv2.resize(img, (600, 800))
hsv_image = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
low_yellow = np.array([18, 94, 140])
up_yellow = np.array([48, 255, 255])
hsv_mask = cv2.inRange(hsv_image, low_yellow, up_yellow)
hls_image = cv2.cvtColor(img, cv2.COLOR_BGR2HLS)
low_yellow = np.array([0, 170, 24])
up_yellow = np.array([54, 255, 255])
hls_mask = cv2.inRange(hls_image, low_yellow, up_yellow)
mask = np.logical_or(hsv_mask,hls_mask)

offset = 100
height, width, _ = img.shape
previousPos = h
currentPos = h - offset
finalImg …
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python opencv kalman-filter opencv3.0

3
推荐指数
1
解决办法
1364
查看次数

C++返回指针

#include <iostream>
using namespace std;

int* createArray();

int main() {
    int *arr = createArray();
    cout << "Main: " << arr << endl;

    arr[0] = 0;
    arr[1] = 1;

    cout << arr[0] << endl;
    cout << arr[1] << endl;
}

int* createArray() {
    int arr[2];
    cout << "createArray()1: " << arr << endl;
    return arr;
}
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我不明白为什么我只打电话给这个陈述

cout << arr[0] << endl;
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要么

cout << arr[1] << endl;
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可以显示正确的价值.但如果我同时打电话给两个声明,它就会显示出来

createArray()1: 00AFFAF4
Main: 00AFFAF4
0
11533068  //Don't show 1
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c++ pointers

1
推荐指数
1
解决办法
273
查看次数

标签 统计

android ×1

base64 ×1

bitmap ×1

c++ ×1

kalman-filter ×1

opencv ×1

opencv3.0 ×1

pointers ×1

python ×1