相同的图像，但 Azure Web 应用程序和本地计算机中的 base64 字符串不同
Same Image, but different base64 string in Azure Web app and local machine
我有一个很奇怪的问题。我在 Azure 应用程序服务中托管的 asp.net 网络 API 中将图像转换为 base64string，并得到错误的图像字符串。
如果我 运行 本地机器中的代码，我会得到正确的值。
public static string GetImageFromSharePointOnline(string imageUrl)
{
try
{
using (var clientContext = CreateContext(URL))
{
clientContext.ExecutingWebRequest += ExecutingWebRequest;
FileInformation fileInformation = null;
Stream returnStream = new MemoryStream();
int readCount;
var buffer = new byte[8192];
Uri image = new Uri(imageUrl);
try
{
fileInformation = Microsoft.SharePoint.Client.File.OpenBinaryDirect(clientContext, image.AbsolutePath);
while ((readCount = fileInformation.Stream.Read(buffer, 0, buffer.Length)) != 0)
{
returnStream.Write(buffer, 0, readCount);
}
}
catch (Exception ex) { }
returnStream.Seek(0, SeekOrigin.Begin);
return "data:image/" + GetFileExtensionFromUrl(imageUrl) + ";base64," + Convert.ToBase64String(buffer);
// return Convert.ToBase64String(buffer);
}
}
catch (Exception ex) { }
}
Azure web api 输出：
data:image/jpg;base64,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
output from my local machine:
data:image/jpg;base64,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谁能帮我解决这个问题。
您正在初始化 MemoryStream：
Stream returnStream = new MemoryStream();
（应该是var returnStream = new MemoryStream();）
作为从 Stream 中读取的字节的容器。
使用缓冲区从源流中读取图像字节：
var buffer = new byte[8192];
对于 NetworkStream 来说没问题。
假设 Uri image = new Uri(imageUrl); 在两个环境中代表同一个对象，你读取一个 [buffer] 字节数（这是最大值，实际读取的字节数可能小于该值）并写入读取的字节数 -值存储在 readCount 变量中 - 到 MemoryStream:
try
{
fileInformation = Microsoft.SharePoint.Client.File.OpenBinaryDirect(clientContext, image.AbsolutePath);
while ((readCount = fileInformation.Stream.Read(buffer, 0, buffer.Length)) != 0)
{
returnStream.Write(buffer, 0, readCount);
}
}
当源Stream读取结束时，MemoryStream包含Image字节。
此时，您想将图像字节转换为 Base64String。
当然，您需要转换 MemoryStream 的内容，returnStream，而不是 buffer 内容，后者仅用作来自源流的字节的临时容器。所以只需更改：
Convert.ToBase64String(buffer);
至：
Convert.ToBase64String(returnStream.ToArray());
在调用 returnStream.ToArray() 之前设置 returnStream.Position = 0 在这种情况下没有必要，但也没有坏处。
旁注：那些空的 catch 块对你没有好处。添加日志功能或删除。
我有一个很奇怪的问题。我在 Azure 应用程序服务中托管的 asp.net 网络 API 中将图像转换为 base64string，并得到错误的图像字符串。
如果我 运行 本地机器中的代码，我会得到正确的值。
public static string GetImageFromSharePointOnline(string imageUrl)
{
try
{
using (var clientContext = CreateContext(URL))
{
clientContext.ExecutingWebRequest += ExecutingWebRequest;
FileInformation fileInformation = null;
Stream returnStream = new MemoryStream();
int readCount;
var buffer = new byte[8192];
Uri image = new Uri(imageUrl);
try
{
fileInformation = Microsoft.SharePoint.Client.File.OpenBinaryDirect(clientContext, image.AbsolutePath);
while ((readCount = fileInformation.Stream.Read(buffer, 0, buffer.Length)) != 0)
{
returnStream.Write(buffer, 0, readCount);
}
}
catch (Exception ex) { }
returnStream.Seek(0, SeekOrigin.Begin);
return "data:image/" + GetFileExtensionFromUrl(imageUrl) + ";base64," + Convert.ToBase64String(buffer);
// return Convert.ToBase64String(buffer);
}
}
catch (Exception ex) { }
}
Azure web api 输出：
data:image/jpg;base64,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
output from my local machine:
data:image/jpg;base64,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谁能帮我解决这个问题。
您正在初始化 MemoryStream：
Stream returnStream = new MemoryStream();
（应该是var returnStream = new MemoryStream();）
作为从 Stream 中读取的字节的容器。
使用缓冲区从源流中读取图像字节：
var buffer = new byte[8192];
对于 NetworkStream 来说没问题。
假设 Uri image = new Uri(imageUrl); 在两个环境中代表同一个对象，你读取一个 [buffer] 字节数（这是最大值，实际读取的字节数可能小于该值）并写入读取的字节数 -值存储在 readCount 变量中 - 到 MemoryStream:
try
{
fileInformation = Microsoft.SharePoint.Client.File.OpenBinaryDirect(clientContext, image.AbsolutePath);
while ((readCount = fileInformation.Stream.Read(buffer, 0, buffer.Length)) != 0)
{
returnStream.Write(buffer, 0, readCount);
}
}
当源Stream读取结束时，MemoryStream包含Image字节。
此时，您想将图像字节转换为 Base64String。
当然，您需要转换 MemoryStream 的内容，returnStream，而不是 buffer 内容，后者仅用作来自源流的字节的临时容器。所以只需更改：
Convert.ToBase64String(buffer);
至：
Convert.ToBase64String(returnStream.ToArray());
在调用 returnStream.ToArray() 之前设置 returnStream.Position = 0 在这种情况下没有必要，但也没有坏处。
旁注：那些空的 catch 块对你没有好处。添加日志功能或删除。