转自http://www.cnblogs.com/zgz345/archive/2013/01/08/2851204.html
在android设备上(where you have only 16MB memory available),如果使用BitmapFactory解码一个较大文件,程序立刻蹦出了java.lang.OutOfMemoryError: bitmap size exceeds VM budget的OOM错误!
解决办法:
方法一:将载入的图片缩小,这种方式以牺牲图片的质量为代价。在BitmapFactory中有一个内部类BitmapFactory.Options,其中当options.inSampleSize值>1时,
根据文档:
If set to a value > 1, requests the decoder to subsample the original image, returning a smaller image to save memory. (1 -> decodes full size; 2 -> decodes 1/4th size; 4 -> decode 1/16th size). Because you rarely need to show and have full size bitmap images on your phone. For manipulations smaller sizes are usually enough.
也就是说,options.inSampleSize是以2的指数的倒数被进行放缩。这样,我们可以依靠inSampleSize的值的设定将图片放缩载入,这样一般情况也就不会出现上述的OOM问题了。现在问题是怎么确定inSampleSize的值?每张图片的放缩大小的比例应该是不一样的!这样的话就要运行时动态确定。在BitmapFactory.Options中提供了另一个成员inJustDecodeBounds。
BitmapFactory.Options opts = new BitmapFactory.Options();
opts.inJustDecodeBounds = true;
Bitmap bitmap = BitmapFactory.decodeFile(imageFile, opts);
Android提供了一种动态计算的方法。如下:
public Bitmap getBitmapFromFile(File dst, int width, int height) {
if (null != dst && dst.exists()) {
BitmapFactory.Options opts = null;
if (width > 0 && height > 0) {
opts = new BitmapFactory.Options();
//设置inJustDecodeBounds为true后,decodeFile并不分配空间,此时计算原始图片的长度和宽度
opts.inJustDecodeBounds = true;
BitmapFactory.decodeFile(dst.getPath(), opts);
// 计算图片缩放比例
final int minSideLength = Math.min(width, height);
opts.inSampleSize = computeSampleSize(opts, minSideLength,
width * height);
//这里一定要将其设置回false,因为之前我们将其设置成了true
opts.inJustDecodeBounds = false;
opts.inInputShareable = true;
opts.inPurgeable = true;
}
try {
return BitmapFactory.decodeFile(dst.getPath(), opts);
} catch (OutOfMemoryError e) {
e.printStackTrace();
}
}
return null;
}
public static int computeSampleSize(BitmapFactory.Options options,
int minSideLength, int maxNumOfPixels) {
int initialSize = computeInitialSampleSize(options, minSideLength,
maxNumOfPixels);
int roundedSize;
if (initialSize <= 8) {
roundedSize = 1;
while (roundedSize < initialSize) {
roundedSize <<= 1;
}
} else {
roundedSize = (initialSize + 7) / 8 * 8;
}
return roundedSize;
}
private static int computeInitialSampleSize(BitmapFactory.Options options,
int minSideLength, int maxNumOfPixels) {
double w = options.outWidth;
double h = options.outHeight;
int lowerBound = (maxNumOfPixels == -1) ? 1 : (int) Math.ceil(Math
.sqrt(w * h / maxNumOfPixels));
int upperBound = (minSideLength == -1) ? 128 : (int) Math.min(Math
.floor(w / minSideLength), Math.floor(h / minSideLength));
if (upperBound < lowerBound) {
// return the larger one when there is no overlapping zone.
return lowerBound;
}
if ((maxNumOfPixels == -1) && (minSideLength == -1)) {
return 1;
} else if (minSideLength == -1) {
return lowerBound;
} else {
return upperBound;
}
}
这样,在BitmapFactory.decodeFile执行处,也就不会报出上面的OOM Error。
如前面提到的,这种方式在一定程度上是以牺牲图片质量为代价的。如何才能更加优化的实现需求?
当在android设备中载入较大图片资源时,可以创建一些临时空间,将载入的资源载入到临时空间中。
BitmapFactory.Options bfOptions=new BitmapFactory.Options();
bfOptions.inTempStorage=newbyte[12 * 1024];
Bitmap bitmapImage = BitmapFactory.decodeFile(path,bfOptions);
BitmapFactory.Options bfOptions=new BitmapFactory.Options();
bfOptions.inDither=false;
bfOptions.inPurgeable=true;
bfOptions.inTempStorage=newbyte[12 * 1024];
bfOptions.inJustDecodeBounds = true;
File file = new File(pePicFile.getAbsolutePath() + "/"+info.getImage());
FileInputStream fs=null;
Bitmap bmp = null;
try {
fs = new FileInputStream(file);
if(fs != null)
bmp = BitmapFactory.decodeFileDescriptor(fs.getFD(), null, bfOptions);
} catch (Exception e) {
e.printStackTrace();
}
当然要将取得图片进行放缩显示等处理也可以在以上得到的bmp进行。
图片处理后记得回收内存
if(!bmp.isRecycle() ){
bmp.recycle() //回收图片所占的内存
system.gc() //提醒系统及时回收
}