Android图片缓存之Bitmap详解（一）
前言：
最近准备研究一下图片缓存框架，基于这个想法觉得还是先了解有关图片缓存的基础知识，今天重点学习一下Bitmap、BitmapFactory这两个类。
Bitmap：
Bitmap是Android系统中的图像处理的最重要类之一。用它可以获取图像文件信息，进行图像剪切、旋转、缩放等操作，并可以指定格式保存图像文件。
重要函数
•public void recycle() // 回收位图占用的内存空间，把位图标记为Dead
•public final boolean isRecycled() //判断位图内存是否已释放
•public final int getWidth()//获取位图的宽度
•public final int getHeight()//获取位图的高度
•public final boolean isMutable()//图片是否可修改
•public int getScaledWidth(Canvas canvas)//获取指定密度转换后的图像的宽度
•public int getScaledHeight(Canvas canvas)//获取指定密度转换后的图像的高度
•public boolean compress(CompressFormat format, int quality, OutputStream stream)//按指定的图片格式以及画质，将图片转换为输出流。
format：Bitmap.CompressFormat.PNG或Bitmap.CompressFormat.JPEG
quality：画质，0-100.0表示最低画质压缩，100以最高画质压缩。对于PNG等无损格式的图片，会忽略此项设置。
•public static Bitmap createBitmap(Bitmap class="lazy" data-src) //以class="lazy" data-src为原图生成不可变得新图像
•public static Bitmap createScaledBitmap(Bitmap class="lazy" data-src, int dstWidth, int dstHeight, boolean filter)//以class="lazy" data-src为原图，创建新的图像，指定新图像的高宽以及是否可变。
•public static Bitmap createBitmap(int width, int height, Config config)——创建指定格式、大小的位图
•public static Bitmap createBitmap(Bitmap source, int x, int y, int width, int height)以source为原图，创建新的图片，指定起始坐标以及新图像的高宽。
BitmapFactory工厂类：
Option 参数类：
•public boolean inJustDecodeBounds//如果设置为true，不获取图片，不分配内存，但会返回图片的高度宽度信息。
•public int inSampleSize//图片缩放的倍数
•public int outWidth//获取图片的宽度值
•public int outHeight//获取图片的高度值
•public int inDensity//用于位图的像素压缩比
•public int inTargetDensity//用于目标位图的像素压缩比（要生成的位图）
•public byte[] inTempStorage //创建临时文件，将图片存储
•public boolean inScaled//设置为true时进行图片压缩，从inDensity到inTargetDensity
•public boolean inDither //如果为true,解码器尝试抖动解码
•public Bitmap.Config inPreferredConfig //设置解码器
•public String outMimeType //设置解码图像
•public boolean inPurgeable//当存储Pixel的内存空间在系统内存不足时是否可以被回收
•public boolean inInputShareable //inPurgeable为true情况下才生效，是否可以共享一个InputStream
•public boolean inPreferQualityOverSpeed //为true则优先保证Bitmap质量其次是解码速度
•public boolean inMutable //配置Bitmap是否可以更改，比如：在Bitmap上隔几个像素加一条线段
•public int inScreenDensity //当前屏幕的像素密度
工厂方法:
•public static Bitmap decodeFile(String pathName, Options opts) //从文件读取图片
•public static Bitmap decodeFile(String pathName)
•public static Bitmap decodeStream(InputStream is) //从输入流读取图片
•public static Bitmap decodeStream(InputStream is, Rect outPadding, Options opts)
•public static Bitmap decodeResource(Resources res, int id) //从资源文件读取图片
•public static Bitmap decodeResource(Resources res, int id, Options opts)
•public static Bitmap decodeByteArray(byte[] data, int offset, int length) //从数组读取图片
•public static Bitmap decodeByteArray(byte[] data, int offset, int length, Options opts)
•public static Bitmap decodeFileDescriptor(FileDescriptor fd)//从文件读取文件 与decodeFile不同的是这个直接调用JNI函数进行读取 效率比较高
•public static Bitmap decodeFileDescriptor(FileDescriptor fd, Rect outPadding, Options opts)
Bitmap.Config inPreferredConfig :
枚举变量 （位图位数越高代表其可以存储的颜色信息越多，图像越逼真，占用内存越大）
•public static final Bitmap.Config ALPHA_8 //代表8位Alpha位图 每个像素占用1byte内存
•public static final Bitmap.Config ARGB_4444 //代表16位ARGB位图 每个像素占用2byte内存
•public static final Bitmap.Config ARGB_8888 //代表32位ARGB位图 每个像素占用4byte内存
•public static final Bitmap.Config RGB_565 //代表8位RGB位图 每个像素占用2byte内存
Android中一张图片（BitMap）占用的内存主要和以下几个因数有关：图片长度，图片宽度，单位像素占用的字节数。
一张图片（BitMap）占用的内存=图片长度*图片宽度*单位像素占用的字节数
图片读取实例：
1.）从文件读取方式一
public static Bitmap readBitmapFromFile(String filePath, int width, int height) {
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeFile(filePath, options);
float class="lazy" data-srcWidth = options.outWidth;
float class="lazy" data-srcHeight = options.outHeight;
int inSampleSize = 1;
if (class="lazy" data-srcHeight > height || class="lazy" data-srcWidth > width) {
if (class="lazy" data-srcWidth > class="lazy" data-srcHeight) {
inSampleSize = Math.round(class="lazy" data-srcHeight / height);
} else {
inSampleSize = Math.round(class="lazy" data-srcWidth / width);
}
}
options.inJustDecodeBounds = false;
options.inSampleSize = inSampleSize;
return BitmapFactory.decodeFile(filePath, options);
}
2.）从文件读取方式二 效率高于方式一
public static Bitmap readBitmapFromFileDescriptor(String filePath, int width, int height) {
try {
FileInputStream fis = new FileInputStream(filePath);
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeFileDescriptor(fis.getFD(), null, options);
float class="lazy" data-srcWidth = options.outWidth;
float class="lazy" data-srcHeight = options.outHeight;
int inSampleSize = 1;
if (class="lazy" data-srcHeight > height || class="lazy" data-srcWidth > width) {
if (class="lazy" data-srcWidth > class="lazy" data-srcHeight) {
inSampleSize = Math.round(class="lazy" data-srcHeight / height);
} else {
inSampleSize = Math.round(class="lazy" data-srcWidth / width);
}
}
options.inJustDecodeBounds = false;
options.inSampleSize = inSampleSize;
return BitmapFactory.decodeFileDescriptor(fis.getFD(), null, options);
} catch (Exception ex) {
}
return null;
}
测试同样生成10张图片两种方式耗时比较 cpu使用以及内存占用两者相差无几 第二种方式效率高一点 所以建议优先采用第二种方式
start = System.currentTimeMillis();
for (int i = 0; i < testMaxCount; i++) {
BitmapUtils.readBitmapFromFile(filePath, 400, 400);
}
end = System.currentTimeMillis();
Log.e(TAG, "BitmapFactory decodeFile--time-->" + (end - start));
start = System.currentTimeMillis();
for (int i = 0; i < testMaxCount; i++) {
BitmapUtils.readBitmapFromFileDescriptor(filePath, 400, 400);
}
end = System.currentTimeMillis();
Log.e(TAG, "BitmapFactory decodeFileDescriptor--time-->" + (end - start));
3.）从输入流中读取文件
public static Bitmap readBitmapFromInputStream(InputStream ins, int width, int height) {
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeStream(ins, null, options);
float class="lazy" data-srcWidth = options.outWidth;
float class="lazy" data-srcHeight = options.outHeight;
int inSampleSize = 1;
if (class="lazy" data-srcHeight > height || class="lazy" data-srcWidth > width) {
if (class="lazy" data-srcWidth > class="lazy" data-srcHeight) {
inSampleSize = Math.round(class="lazy" data-srcHeight / height);
} else {
inSampleSize = Math.round(class="lazy" data-srcWidth / width);
}
}
options.inJustDecodeBounds = false;
options.inSampleSize = inSampleSize;
return BitmapFactory.decodeStream(ins, null, options);
}
4.）从资源文件中读取文件
public static Bitmap readBitmapFromResource(Resources resources, int resourcesId, int width, int height) {
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeResource(resources, resourcesId, options);
float class="lazy" data-srcWidth = options.outWidth;
float class="lazy" data-srcHeight = options.outHeight;
int inSampleSize = 1;
if (class="lazy" data-srcHeight > height || class="lazy" data-srcWidth > width) {
if (class="lazy" data-srcWidth > class="lazy" data-srcHeight) {
inSampleSize = Math.round(class="lazy" data-srcHeight / height);
} else {
inSampleSize = Math.round(class="lazy" data-srcWidth / width);
}
}
options.inJustDecodeBounds = false;
options.inSampleSize = inSampleSize;
return BitmapFactory.decodeResource(resources, resourcesId, options);
}
此种方式相当的耗费内存 建议采用decodeStream代替decodeResource 可以如下形式
public static Bitmap readBitmapFromResource(Resources resources, int resourcesId, int width, int height) {
InputStream ins = resources.openRawResource(resourcesId);
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeStream(ins, null, options);
float class="lazy" data-srcWidth = options.outWidth;
float class="lazy" data-srcHeight = options.outHeight;
int inSampleSize = 1;
if (class="lazy" data-srcHeight > height || class="lazy" data-srcWidth > width) {
if (class="lazy" data-srcWidth > class="lazy" data-srcHeight) {
inSampleSize = Math.round(class="lazy" data-srcHeight / height);
} else {
inSampleSize = Math.round(class="lazy" data-srcWidth / width);
}
}
options.inJustDecodeBounds = false;
options.inSampleSize = inSampleSize;
return BitmapFactory.decodeStream(ins, null, options);
}
decodeStream、decodeResource占用内存对比：
start = System.currentTimeMillis();
for (int i = 0; i < testMaxCount; i++) {
BitmapUtils.readBitmapFromResource(getResources(), R.mipmap.ic_app_center_banner, 400, 400);
Log.e(TAG, "BitmapFactory decodeResource--num-->" + i);
}
end = System.currentTimeMillis();
Log.e(TAG, "BitmapFactory decodeResource--time-->" + (end - start));
start = System.currentTimeMillis();
for (int i = 0; i < testMaxCount; i++) {
BitmapUtils.readBitmapFromResource1(getResources(), R.mipmap.ic_app_center_banner, 400, 400);
Log.e(TAG, "BitmapFactory decodeStream--num-->" + i);
}
end = System.currentTimeMillis();
Log.e(TAG, "BitmapFactory decodeStream--time-->" + (end - start));
BitmapFactory.decodeResource 加载的图片可能会经过缩放，该缩放目前是放在 java 层做的，效率比较低，而且需要消耗 java 层的内存。因此，如果大量使用该接口加载图片，容易导致OOM错误。
BitmapFactory.decodeStream 不会对所加载的图片进行缩放，相比之下占用内存少，效率更高。
这两个接口各有用处，如果对性能要求较高，则应该使用 decodeStream；如果对性能要求不高，且需要 Android 自带的图片自适应缩放功能，则可以使用 decodeResource。
5. ）从二进制数据读取图片
public static Bitmap readBitmapFromByteArray(byte[] data, int width, int height) {
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeByteArray(data, 0, data.length, options);
float class="lazy" data-srcWidth = options.outWidth;
float class="lazy" data-srcHeight = options.outHeight;
int inSampleSize = 1;
if (class="lazy" data-srcHeight > height || class="lazy" data-srcWidth > width) {
if (class="lazy" data-srcWidth > class="lazy" data-srcHeight) {
inSampleSize = Math.round(class="lazy" data-srcHeight / height);
} else {
inSampleSize = Math.round(class="lazy" data-srcWidth / width);
}
}
options.inJustDecodeBounds = false;
options.inSampleSize = inSampleSize;
return BitmapFactory.decodeByteArray(data, 0, data.length, options);
}
6.）从assets文件读取图片
public static Bitmap readBitmapFromAssetsFile(Context context, String filePath) {
Bitmap image = null;
AssetManager am = context.getResources().getAssets();
try {
InputStream is = am.open(filePath);
image = BitmapFactory.decodeStream(is);
is.close();
} catch (IOException e) {
e.printStackTrace();
}
return image;
}
图片保存文件：
public static void writeBitmapToFile(String filePath, Bitmap b, int quality) {
try {
File desFile = new File(filePath);
FileOutputStream fos = new FileOutputStream(desFile);
BufferedOutputStream bos = new BufferedOutputStream(fos);
b.compress(Bitmap.CompressFormat.JPEG, quality, bos);
bos.flush();
bos.close();
} catch (IOException e) {
e.printStackTrace();
}
}
图片压缩：
private static Bitmap compressImage(Bitmap image) {
if (image == null) {
return null;
}
ByteArrayOutputStream baos = null;
try {
baos = new ByteArrayOutputStream();
image.compress(Bitmap.CompressFormat.JPEG, 100, baos);
byte[] bytes = baos.toByteArray();
ByteArrayInputStream isBm = new ByteArrayInputStream(bytes);
Bitmap bitmap = BitmapFactory.decodeStream(isBm);
return bitmap;
} catch (OutOfMemoryError e) {
} finally {
try {
if (baos != null) {
baos.close();
}
} catch (IOException e) {
}
}
return null;
}
图片缩放：
public static Bitmap bitmapScale(Bitmap bitmap, float scale) {
Matrix matrix = new Matrix();
matrix.postScale(scale, scale); // 长和宽放大缩小的比例
Bitmap resizeBmp = Bitmap.createBitmap(bitmap, 0, 0, bitmap.getWidth(), bitmap.getHeight(), matrix, true);
return resizeBmp;
}
获取图片旋转角度：
private static int readPictureDegree(String path) {
if (TextUtils.isEmpty(path)) {
return 0;
}
int degree = 0;
try {
ExifInterface exifInterface = new ExifInterface(path);
int orientation = exifInterface.getAttributeInt(ExifInterface.TAG_ORIENTATION, ExifInterface.ORIENTATION_NORMAL);
switch (orientation) {
case ExifInterface.ORIENTATION_ROTATE_90:
degree = 90;
break;
case ExifInterface.ORIENTATION_ROTATE_180:
degree = 180;
break;
case ExifInterface.ORIENTATION_ROTATE_270:
degree = 270;
break;
}
} catch (Exception e) {
}
return degree;
}
图片旋转角度：
private static Bitmap rotateBitmap(Bitmap b, float rotateDegree) {
if (b == null) {
return null;
}
Matrix matrix = new Matrix();
matrix.postRotate(rotateDegree);
Bitmap rotaBitmap = Bitmap.createBitmap(b, 0, 0, b.getWidth(), b.getHeight(), matrix, true);
return rotaBitmap;
}
图片转二进制：
public byte[] bitmap2Bytes(Bitmap bm) {
ByteArrayOutputStream baos = new ByteArrayOutputStream();
bm.compress(Bitmap.CompressFormat.PNG, 100, baos);
return baos.toByteArray();
}
Bitmap转Drawable
public static Drawable bitmapToDrawable(Resources resources, Bitmap bm) {
Drawable drawable = new BitmapDrawable(resources, bm);
return drawable;
}
Drawable转Bitmap
public static Bitmap drawableToBitmap(Drawable drawable) {
Bitmap bitmap = Bitmap.createBitmap(drawable.getIntrinsicWidth(), drawable.getIntrinsicHeight(), drawable.getOpacity() != PixelFormat.OPAQUE ? Bitmap.Config.ARGB_8888 : Bitmap.Config.RGB_565);
Canvas canvas = new Canvas(bitmap);
drawable.setBounds(0, 0, drawable.getIntrinsicWidth(), drawable.getIntrinsicHeight());
drawable.draw(canvas);
return bitmap;
}
Drawable、Bitmap占用内存探讨
之前一直使用过Afinal 和Xutils 熟悉这两框架的都知道，两者出自同一人，Xutils是Afina的升级版，AFinal中的图片内存缓存使用的是Bitmap 而后来为何Xutils将内存缓存的对象改成了Drawable了呢?我们一探究竟
写个测试程序：
List<Bitmap> bitmaps = new ArrayList<>();
start = System.currentTimeMillis();
for (int i = 0; i < testMaxCount; i++) {
Bitmap bitmap = BitmapUtils.readBitMap(this, R.mipmap.ic_app_center_banner);
bitmaps.add(bitmap);
Log.e(TAG, "BitmapFactory Bitmap--num-->" + i);
}
end = System.currentTimeMillis();
Log.e(TAG, "BitmapFactory Bitmap--time-->" + (end - start));
List<Drawable> drawables = new ArrayList<>();
start = System.currentTimeMillis();
for (int i = 0; i < testMaxCount; i++) {
Drawable drawable = getResources().getDrawable(R.mipmap.ic_app_center_banner);
drawables.add(drawable);
Log.e(TAG, "BitmapFactory Drawable--num-->" + i);
}
end = System.currentTimeMillis();
Log.e(TAG, "BitmapFactory Drawable--time-->" + (end - start));
测试数据1000 同一张图片
从测试说明Drawable 相对Bitmap有很大的内存占用优势。这也是为啥现在主流的图片缓存框架内存缓存那一层采用Drawable作为缓存对象的原因。
小结：图片处理就暂时学习到这里，以后再做补充。
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