最近准备研究一下图片缓存框架,基于这个想法以为仍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。html
图片缓存相关博客地址:java
Bitmap是Android系统中的图像处理的最重要类之一。用它能够获取图像文件信息,进行图像剪切、旋转、缩放等操做,并能够指定格式保存图像文件。算法
重要函数canvas
public void recycle() // 回收位图占用的内存空间,把位图标记为Dead数组
public final boolean isRecycled() //判断位图内存是否已释放 缓存
public final int getWidth()//获取位图的宽度 app
public final int getHeight()//获取位图的高度框架
public final boolean isMutable()//图片是否可修改 ide
public int getScaledWidth(Canvas canvas)//获取指定密度转换后的图像的宽度 函数
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 src) //以src为原图生成不可变得新图像
public static Bitmap createScaledBitmap(Bitmap src, int dstWidth, int dstHeight, boolean filter)//以src为原图,建立新的图像,指定新图像的高宽以及是否可变。
public static Bitmap createBitmap(int width, int height, Config config)——建立指定格式、大小的位图
public static Bitmap createBitmap(Bitmap source, int x, int y, int width, int height)以source为原图,建立新的图片,指定起始坐标以及新图像的高宽。
BitmapFactory工厂类:
public boolean inJustDecodeBounds//若是设置为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 //建立临时文件,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 //若是为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能够被回收
public boolean inInputShareable //inPurgeable为true状况下才生效,是否能够共享一个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是否能够更改,好比: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
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不一样的是这个直接调用JNI函数进行读取 效率比较高
public static Bitmap decodeFileDescriptor(FileDescriptor fd, Rect outPadding, Options opts)
枚举变量 (位图位数越高表明其能够存储的颜色信息越多,图像越逼真,占用内存越大)
/** * 获取缩放后的本地图片 * * @param filePath 文件路径 * @param width 宽 * @param height 高 * @return */ public static Bitmap readBitmapFromFile(String filePath, int width, int height) { BitmapFactory.Options options = new BitmapFactory.Options(); options.inJustDecodeBounds = true; BitmapFactory.decodeFile(filePath, options); float srcWidth = options.outWidth; float srcHeight = options.outHeight; int inSampleSize = 1; if (srcHeight > height || srcWidth > width) { if (srcWidth > srcHeight) { inSampleSize = Math.round(srcHeight / height); } else { inSampleSize = Math.round(srcWidth / width); } } options.inJustDecodeBounds = false; options.inSampleSize = inSampleSize; return BitmapFactory.decodeFile(filePath, options); }
/** * 获取缩放后的本地图片 * * @param filePath 文件路径 * @param width 宽 * @param height 高 * @return */ 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 srcWidth = options.outWidth; float srcHeight = options.outHeight; int inSampleSize = 1; if (srcHeight > height || srcWidth > width) { if (srcWidth > srcHeight) { inSampleSize = Math.round(srcHeight / height); } else { inSampleSize = Math.round(srcWidth / width); } } options.inJustDecodeBounds = false; options.inSampleSize = inSampleSize; return BitmapFactory.decodeFileDescriptor(fis.getFD(), null, options); } catch (Exception ex) { } return null; }
测试一样生成10张图片两种方式耗时比较 cpu使用以及内存占用二者相差无几 第二种方式效率高一点 因此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));
/** * 获取缩放后的本地图片 * * @param ins 输入流 * @param width 宽 * @param height 高 * @return */ 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 srcWidth = options.outWidth; float srcHeight = options.outHeight; int inSampleSize = 1; if (srcHeight > height || srcWidth > width) { if (srcWidth > srcHeight) { inSampleSize = Math.round(srcHeight / height); } else { inSampleSize = Math.round(srcWidth / width); } } options.inJustDecodeBounds = false; options.inSampleSize = inSampleSize; return BitmapFactory.decodeStream(ins, null, options); }
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 srcWidth = options.outWidth; float srcHeight = options.outHeight; int inSampleSize = 1; if (srcHeight > height || srcWidth > width) { if (srcWidth > srcHeight) { inSampleSize = Math.round(srcHeight / height); } else { inSampleSize = Math.round(srcWidth / width); } } options.inJustDecodeBounds = false; options.inSampleSize = inSampleSize; return BitmapFactory.decodeResource(resources, resourcesId, options); }
此种方式至关的耗费内存 建议采用decodeStream代替decodeResource 能够以下形式
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 srcWidth = options.outWidth; float srcHeight = options.outHeight; int inSampleSize = 1; if (srcHeight > height || srcWidth > width) { if (srcWidth > srcHeight) { inSampleSize = Math.round(srcHeight / height); } else { inSampleSize = Math.round(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 加载的图片可能会通过缩放,该缩放目前是放在 java 层作的,效率比较低,并且须要消耗 java 层的内存。所以,若是大量使用该接口加载图片,容易致使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,若是对性能要求较高,则应该使用 decodeStream;若是对性能要求不高,且须要 Android 自带的图片自适应缩放功能,则可使用 decodeResource。
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 srcWidth = options.outWidth; float srcHeight = options.outHeight; int inSampleSize = 1; if (srcHeight > height || srcWidth > width) { if (srcWidth > srcHeight) { inSampleSize = Math.round(srcHeight / height); } else { inSampleSize = Math.round(srcWidth / width); } } options.inJustDecodeBounds = false; options.inSampleSize = inSampleSize; return BitmapFactory.decodeByteArray(data, 0, data.length, options); }
/** * 获取缩放后的本地图片 * * @param filePath 文件路径 * @return */ 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; }
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(); } }
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; }
/** * 根据scale生成一张图片 * * @param bitmap * @param scale 等比缩放值 * @return */ 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; }
/** * 读取照片exif信息中的旋转角度 * * @param path 照片路径 * @return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; }
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; }
public byte[] bitmap2Bytes(Bitmap bm) { ByteArrayOutputStream baos = new ByteArrayOutputStream(); bm.compress(Bitmap.CompressFormat.PNG, 100, baos); return baos.toByteArray(); }
public static Drawable bitmapToDrawable(Resources resources, Bitmap bm) { Drawable drawable = new BitmapDrawable(resources, bm); return drawable; }
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; }
以前一直使用过Afinal 和Xutils 熟悉这两框架的都知道,二者出自同一人,Xutils是Afina的升级版,AFinal中的图片内存缓存使用的是Bitmap 然后来为什么Xutils将内存缓存的对象改为了Drawable了呢?咱们一探究竟
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
Bitmap 直接70条数据的时候挂掉
Drawable 轻松1000条数据经过
从测试说明Drawable 相对Bitmap有很大的内存占用优点。这也是为啥如今主流的图片缓存框架内存缓存那一层采用Drawable做为缓存对象的缘由。
小结:
图片处理就暂时学习到这里,之后再作补充。