视频圆角-取视频关键帧转gif

2018-04-04 Android 视频圆角, 视频转gif 0 评论

视频圆角-取视频关键帧转gif

<The rest of contents | 余下全文>

写在前面

最近需求最开始要求设计到视频的圆角播放

视频圆角是个坑，自己把自己恶心到了也。

其实不是很难

方式1:
直接外部套个cardview，然后根据需要关闭cardview的阴影即可。（最实用）

方式2:
针对5.0以上的设备，

public class TextureVideoViewOutlineProvider extends ViewOutlineProvider {  
	private float mRadius;  

	public TextureVideoViewOutlineProvider(float radius) {  
	    this.mRadius = radius;  
	}  

	@Override  
	public void getOutline(View view, Outline outline) {  
	    Rect rect = new Rect();  
	    view.getGlobalVisibleRect(rect);  
	    int leftMargin = 0;  
	    int topMargin = 0;  
	    Rect selfRect = new Rect(leftMargin, topMargin,  
	            rect.right - rect.left - leftMargin, rect.bottom - rect.top - topMargin);  
	    outline.setRoundRect(selfRect, mRadius);  
	}  
}

方式3:
很麻烦，只适用于SurfaceView，也就是最好视频不能再滚动列表中。

public class RoundView extends SurfaceView {
	@Override  
	protected void onDraw(Canvas canvas) {  
	    Path clipPath = new Path();  
	    int w = this.getWidth();  
	    int h = this.getHeight();  
	      
	    clipPath.addRoundRect(new RectF(0, 0, w, h), 10.0f, 10.0f, Path.Direction.CW);  
	    canvas.clipPath(clipPath);  
	    super.onDraw(canvas);  
	}  
}

方式4:
最麻烦，很折腾人，而且视频上面不能遮盖东西。
利用glsurfaceview 没帧图片自己解析然后处理圆角绘制出来（微信貌似这么干的）

具体参考blog戳这里

视频转换gif

后来发现我们滚动列表中同时播放的视频太多了（最多可能出现5-6个情况）

导致非常的不流畅，特别是快速滑动状态下。

最后和产品沟通，发现他的灵感来源于抖音的视频预览。

仔细观察之后，MMP，抖音是在外部列表的时候是取关键帧然后合成gif播放。

我们也打算这么干了。

提取视频关键帧，我们用的七牛，七牛是直接支持的。

如果你们后端不支持，那么就需要利用ffmepg来自己提取了。最好在上传或者后端做，这样就不需要把视频下载下来之后再处理了！节约流量。节约成本。

代码贴过来:

package com.miaozan.xpro.manager;

import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.os.Handler;

import com.danikula.videocache.file.FileCache;
import com.gloomyer.threadppl.ThreadPool;
import com.miaozan.xpro.base.BaseApp;
import com.miaozan.xpro.interfaces.OnResultDataListener;
import com.miaozan.xpro.interfaces.OnResultListListener;
import com.miaozan.xpro.net.NetManager;
import com.miaozan.xpro.utils.AnimatedGifEncoder;
import com.miaozan.xpro.utils.DownloadUtils;

import org.json.JSONObject;

import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.net.URI;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import java.util.concurrent.TimeUnit;

import okhttp3.Call;
import okhttp3.OkHttpClient;
import okhttp3.Request;
import okhttp3.Response;

/**
 * Description:
 * Author: Gloomy
 * Version: 1.0
 * Create Date Time: 2018-4-2 17:33:36
 * Update Date Time:
 *
 * @see
 */

public class VideoFrameGetManager {
    private static final int DEFAULT_FRAME_COUNT = 4;
    private static final int DEFAULT_FPS = 150;
    private static final String CACHE_FILE_KEY = "storyVideoImageCache";
    private HashMap<String, OnResultDataListener<ResultInfo>> targets;
    private Handler mHandler;

    public class ResultInfo {
        public boolean isGif;
        public String image;
        public int positon;
    }

    private enum Instance {
        I;

        VideoFrameGetManager i;

        Instance() {
            i = new VideoFrameGetManager();
        }
    }

    public static VideoFrameGetManager get() {
        return Instance.I.i;
    }

    private VideoFrameGetManager() {
        targets = new HashMap<>();
        mHandler = new Handler(BaseApp.getAppContext().getMainLooper());
    }

    /**
     * 获取story应该展示的图片、gif
     * <p>
     * 视频：
     * 第一次加载：
     * 先回调一次，返回视频的第一帧图片
     * 再回调一次，返回视频的gif图片
     * 后续的重复加载，
     * 只回调一次，返回视频的gif图片
     * 非视频:
     * 直接产生回调，降storyUrl直接返回给你
     *
     * @param position 坐标 验证防止错乱加载问题
     * @param storyUrl
     * @param listener 回调函数，ResultInfo 有两个public字段。isGif 是否是gif图片，image 图片的url（可能是本地文件、可能是网络url）
     */
    public void getStoryImage(int position, String storyUrl, OnResultDataListener<ResultInfo> listener) {
        ResultInfo result = new ResultInfo();
        result.positon = position;
        if (!storyUrl.endsWith(".mp4")) {
            //不是视频
            result.isGif = false;
            result.image = storyUrl;
            listener.onResult(result);
            return;
        }
        File outputFile = CacheFileManager.get().getFile(CACHE_FILE_KEY);
        outputFile = new File(outputFile, storyUrl.split("://")[1].replace('/', '.') + "_.gif");
        File finalOutputFile = outputFile;
        if (targets.get(storyUrl) == null) {
            targets.put(storyUrl, listener);
            if (!outputFile.exists()) {
                ThreadPool.getInstance().execute(9, () -> {
                    try {
                        OkHttpClient client = new OkHttpClient.Builder().readTimeout(5, TimeUnit.SECONDS).build();
                        Request request = new Request.Builder().url(storyUrl + "?avinfo").get().build();
                        Call call = client.newCall(request);
                        Response response = call.execute();
                        String info = response.body().string();
                        JSONObject obj = new JSONObject(info);
                        double videoDuration = obj.getJSONObject("format").getDouble("duration");
                        //取默认多少帧
                        double step = videoDuration / DEFAULT_FRAME_COUNT;
                        String[] urls = new String[DEFAULT_FRAME_COUNT + 1];
                        for (int i = 0; i < DEFAULT_FRAME_COUNT; i++) {
                            urls[i] = storyUrl + "?vframe/png/offset/" + (i * step) + "/";
                        }
                        urls[urls.length - 1] = storyUrl + "?vframe/png/offset/" + (videoDuration) + "/";//最后一帧
                        List<String> paths = new ArrayList<>();
                        //download File
                        for (int i = 0; i < urls.length; i++) {
                            String url = urls[i];
                            File file = CacheFileManager.get().getFile(CACHE_FILE_KEY);
                            file = new File(file, storyUrl.split("://")[1].replace('/', '.') + "_" + i + ".jpg");
                            if (file.exists()) {
                                paths.add(file.getAbsolutePath());
                                continue;
                            }
                            if (DownloadUtils.downloadFileSync(url, file.getAbsolutePath())) {
                                paths.add(file.getAbsolutePath());
                            }
                        }
                        //合成gif
                        if (finalOutputFile.exists() || createGif(paths, DEFAULT_FPS, finalOutputFile.getAbsolutePath())) {
                            mHandler.post(() -> {
                                result.image = finalOutputFile.getAbsolutePath();
                                result.isGif = true;
                                targets.remove(storyUrl).onResult(result);
                            });
                        }
                    } catch (Exception e) {
                    }
                });
            }
        }
        result.image = outputFile.exists() ? outputFile.getAbsolutePath() : storyUrl + "?vframe/png/offset/0/";
        result.isGif = outputFile.exists();
        listener.onResult(result);
        if (result.isGif)
            targets.remove(storyUrl);
    }

    public static boolean createGif(List<String> paths, int fps, String outpuFile) {
        try {
            ByteArrayOutputStream baos = new ByteArrayOutputStream();
            AnimatedGifEncoder localAnimatedGifEncoder = new AnimatedGifEncoder();
            localAnimatedGifEncoder.start(baos);//start
            localAnimatedGifEncoder.setRepeat(0);//设置生成gif的开始播放时间。0为立即开始播放
            localAnimatedGifEncoder.setDelay(fps);
            if (paths.size() > 0) {
                for (int i = 0; i < paths.size(); i++) {
                    Bitmap bitmap = BitmapFactory.decodeFile(paths.get(i));
                    localAnimatedGifEncoder.addFrame(bitmap);
                }
            }
            localAnimatedGifEncoder.finish();//finish
            FileOutputStream fos = new FileOutputStream(outpuFile);
            baos.writeTo(fos);
            baos.flush();
            fos.flush();
            baos.close();
            fos.close();
            return true;
        } catch (Exception e) {
            e.printStackTrace();
        }
        return false;
    }
}

package com.miaozan.xpro.utils;

import java.io.IOException;
import java.io.OutputStream;

import android.graphics.Bitmap;
import android.graphics.Bitmap.Config;
import android.graphics.Canvas;
import android.graphics.Paint;

public class AnimatedGifEncoder {

    protected int width; // image size

    protected int height;

    protected int x = 0;

    protected int y = 0;

    protected int transparent = -1; // transparent color if given

    protected int transIndex; // transparent index in color table

    protected int repeat = -1; // no repeat

    protected int delay = 0; // frame delay (hundredths)

    protected boolean started = false; // ready to output frames

    protected OutputStream out;

    protected Bitmap image; // current frame

    protected byte[] pixels; // BGR byte array from frame

    protected byte[] indexedPixels; // converted frame indexed to palette

    protected int colorDepth; // number of bit planes

    protected byte[] colorTab; // RGB palette

    protected boolean[] usedEntry = new boolean[256]; // active palette entries

    protected int palSize = 7; // color table size (bits-1)

    protected int dispose = -1; // disposal code (-1 = use default)

    protected boolean closeStream = false; // close stream when finished

    protected boolean firstFrame = true;

    protected boolean sizeSet = false; // if false, get size from first frame

    protected int sample = 10; // default sample interval for quantizer

    /**
     * Sets the delay time between each frame, or changes it for subsequent frames
     * (applies to last frame added).
     *
     * @param ms
     *          int delay time in milliseconds
     */
    public void setDelay(int ms) {
        delay = ms / 10;
    }

    /**
     * Sets the GIF frame disposal code for the last added frame and any
     * subsequent frames. Default is 0 if no transparent color has been set,
     * otherwise 2.
     *
     * @param code
     *          int disposal code.
     */
    public void setDispose(int code) {
        if (code >= 0) {
            dispose = code;
        }
    }

    /**
     * Sets the number of times the set of GIF frames should be played. Default is
     * 1; 0 means play indefinitely. Must be invoked before the first image is
     * added.
     *
     * @param iter
     *          int number of iterations.
     * @return
     */
    public void setRepeat(int iter) {
        if (iter >= 0) {
            repeat = iter;
        }
    }

    /**
     * Sets the transparent color for the last added frame and any subsequent
     * frames. Since all colors are subject to modification in the quantization
     * process, the color in the final palette for each frame closest to the given
     * color becomes the transparent color for that frame. May be set to null to
     * indicate no transparent color.
     *
     * @param c
     *          Color to be treated as transparent on display.
     */
    public void setTransparent(int c) {
        transparent = c;
    }

    /**
     * Adds next GIF frame. The frame is not written immediately, but is actually
     * deferred until the next frame is received so that timing data can be
     * inserted. Invoking <code>finish()</code> flushes all frames. If
     * <code>setSize</code> was not invoked, the size of the first image is used
     * for all subsequent frames.
     *
     * @param im
     *          BufferedImage containing frame to write.
     * @return true if successful.
     */
    public boolean addFrame(Bitmap im) {
        if ((im == null) || !started) {
            return false;
        }
        boolean ok = true;
        try {
            if (!sizeSet) {
                // use first frame's size
                setSize(im.getWidth(), im.getHeight());
            }
            image = im;
            getImagePixels(); // convert to correct format if necessary
            analyzePixels(); // build color table & map pixels
            if (firstFrame) {
                writeLSD(); // logical screen descriptior
                writePalette(); // global color table
                if (repeat >= 0) {
                    // use NS app extension to indicate reps
                    writeNetscapeExt();
                }
            }
            writeGraphicCtrlExt(); // write graphic control extension
            writeImageDesc(); // image descriptor
            if (!firstFrame) {
                writePalette(); // local color table
            }
            writePixels(); // encode and write pixel data
            firstFrame = false;
        } catch (IOException e) {
            ok = false;
        }

        return ok;
    }

    /**
     * Flushes any pending data and closes output file. If writing to an
     * OutputStream, the stream is not closed.
     */
    public boolean finish() {
        if (!started)
            return false;
        boolean ok = true;
        started = false;
        try {
            out.write(0x3b); // gif trailer
            out.flush();
            if (closeStream) {
                out.close();
            }
        } catch (IOException e) {
            ok = false;
        }

        // reset for subsequent use
        transIndex = 0;
        out = null;
        image = null;
        pixels = null;
        indexedPixels = null;
        colorTab = null;
        closeStream = false;
        firstFrame = true;

        return ok;
    }

    /**
     * Sets frame rate in frames per second. Equivalent to
     * <code>setDelay(1000/fps)</code>.
     *
     * @param fps
     *          float frame rate (frames per second)
     */
    public void setFrameRate(float fps) {
        if (fps != 0f) {
            delay = (int)(100 / fps);
        }
    }

    /**
     * Sets quality of color quantization (conversion of images to the maximum 256
     * colors allowed by the GIF specification). Lower values (minimum = 1)
     * produce better colors, but slow processing significantly. 10 is the
     * default, and produces good color mapping at reasonable speeds. Values
     * greater than 20 do not yield significant improvements in speed.
     *
     * @param quality
     *          int greater than 0.
     * @return
     */
    public void setQuality(int quality) {
        if (quality < 1)
            quality = 1;
        sample = quality;
    }

    /**
     * Sets the GIF frame size. The default size is the size of the first frame
     * added if this method is not invoked.
     *
     * @param w
     *          int frame width.
     * @param h
     *          int frame width.
     */
    public void setSize(int w, int h) {
        width = w;
        height = h;
        if (width < 1)
            width = 320;
        if (height < 1)
            height = 240;
        sizeSet = true;
    }

    /**
     * Sets the GIF frame position. The position is 0,0 by default.
     * Useful for only updating a section of the image
     *
     * @param w
     *          int frame width.
     * @param h
     *          int frame width.
     */
    public void setPosition(int x, int y) {
        this.x = x;
        this.y = y;
    }

    /**
     * Initiates GIF file creation on the given stream. The stream is not closed
     * automatically.
     *
     * @param os
     *          OutputStream on which GIF images are written.
     * @return false if initial write failed.
     */
    public boolean start(OutputStream os) {
        if (os == null)
            return false;
        boolean ok = true;
        closeStream = false;
        out = os;
        try {
            writeString("GIF89a"); // header
        } catch (IOException e) {
            ok = false;
        }
        return started = ok;
    }

    /**
     * Analyzes image colors and creates color map.
     */
    protected void analyzePixels() {
        int len = pixels.length;
        int nPix = len / 3;
        indexedPixels = new byte[nPix];
        NeuQuant nq = new NeuQuant(pixels, len, sample);
        // initialize quantizer
        colorTab = nq.process(); // create reduced palette
        // convert map from BGR to RGB
        for (int i = 0; i < colorTab.length; i += 3) {
            byte temp = colorTab[i];
            colorTab[i] = colorTab[i + 2];
            colorTab[i + 2] = temp;
            usedEntry[i / 3] = false;
        }
        // map image pixels to new palette
        int k = 0;
        for (int i = 0; i < nPix; i++) {
            int index = nq.map(pixels[k++] & 0xff, pixels[k++] & 0xff, pixels[k++] & 0xff);
            usedEntry[index] = true;
            indexedPixels[i] = (byte) index;
        }
        pixels = null;
        colorDepth = 8;
        palSize = 7;
        // get closest match to transparent color if specified
        if (transparent != -1) {
            transIndex = findClosest(transparent);
        }
    }

    /**
     * Returns index of palette color closest to c
     *
     */
    protected int findClosest(int c) {
        if (colorTab == null)
            return -1;
        int r = (c >> 16) & 0xff;
        int g = (c >> 8) & 0xff;
        int b = (c >> 0) & 0xff;
        int minpos = 0;
        int dmin = 256 * 256 * 256;
        int len = colorTab.length;
        for (int i = 0; i < len;) {
            int dr = r - (colorTab[i++] & 0xff);
            int dg = g - (colorTab[i++] & 0xff);
            int db = b - (colorTab[i] & 0xff);
            int d = dr * dr + dg * dg + db * db;
            int index = i / 3;
            if (usedEntry[index] && (d < dmin)) {
                dmin = d;
                minpos = index;
            }
            i++;
        }
        return minpos;
    }

    /**
     * Extracts image pixels into byte array "pixels"
     */
    protected void getImagePixels() {
        int w = image.getWidth();
        int h = image.getHeight();
        if ((w != width) || (h != height)) {
            // create new image with right size/format
            Bitmap temp = Bitmap.createBitmap(width, height, Config.RGB_565);
            Canvas g = new Canvas(temp);
            g.drawBitmap(image, 0, 0, new Paint());
            image = temp;
        }
        int[] data = getImageData(image);
        pixels = new byte[data.length * 3];
        for (int i = 0; i < data.length; i++) {
            int td = data[i];
            int tind = i * 3;
            pixels[tind++] = (byte) ((td >> 0) & 0xFF);
            pixels[tind++] = (byte) ((td >> 8) & 0xFF);
            pixels[tind] = (byte) ((td >> 16) & 0xFF);
        }
    }
    protected int[] getImageData(Bitmap img) {
        int w = img.getWidth();
        int h = img.getHeight();

        int[] data = new int[w * h];
        img.getPixels(data, 0, w, 0, 0, w, h);
        return data;
    }

    /**
     * Writes Graphic Control Extension
     */
    protected void writeGraphicCtrlExt() throws IOException {
        out.write(0x21); // extension introducer
        out.write(0xf9); // GCE label
        out.write(4); // data block size
        int transp, disp;
        if (transparent == -1) {
            transp = 0;
            disp = 0; // dispose = no action
        } else {
            transp = 1;
            disp = 2; // force clear if using transparent color
        }
        if (dispose >= 0) {
            disp = dispose & 7; // user override
        }
        disp <<= 2;

        // packed fields
        out.write(0 | // 1:3 reserved
                disp | // 4:6 disposal
                0 | // 7 user input - 0 = none
                transp); // 8 transparency flag

        writeShort(delay); // delay x 1/100 sec
        out.write(transIndex); // transparent color index
        out.write(0); // block terminator
    }

    /**
     * Writes Image Descriptor
     */
    protected void writeImageDesc() throws IOException {
        out.write(0x2c); // image separator
        writeShort(x); // image position x,y = 0,0
        writeShort(y);
        writeShort(width); // image size
        writeShort(height);
        // packed fields
        if (firstFrame) {
            // no LCT - GCT is used for first (or only) frame
            out.write(0);
        } else {
            // specify normal LCT
            out.write(0x80 | // 1 local color table 1=yes
                    0 | // 2 interlace - 0=no
                    0 | // 3 sorted - 0=no
                    0 | // 4-5 reserved
                    palSize); // 6-8 size of color table
        }
    }

    /**
     * Writes Logical Screen Descriptor
     */
    protected void writeLSD() throws IOException {
        // logical screen size
        writeShort(width);
        writeShort(height);
        // packed fields
        out.write((0x80 | // 1 : global color table flag = 1 (gct used)
                0x70 | // 2-4 : color resolution = 7
                0x00 | // 5 : gct sort flag = 0
                palSize)); // 6-8 : gct size

        out.write(0); // background color index
        out.write(0); // pixel aspect ratio - assume 1:1
    }

    /**
     * Writes Netscape application extension to define repeat count.
     */
    protected void writeNetscapeExt() throws IOException {
        out.write(0x21); // extension introducer
        out.write(0xff); // app extension label
        out.write(11); // block size
        writeString("NETSCAPE" + "2.0"); // app id + auth code
        out.write(3); // sub-block size
        out.write(1); // loop sub-block id
        writeShort(repeat); // loop count (extra iterations, 0=repeat forever)
        out.write(0); // block terminator
    }

    /**
     * Writes color table
     */
    protected void writePalette() throws IOException {
        out.write(colorTab, 0, colorTab.length);
        int n = (3 * 256) - colorTab.length;
        for (int i = 0; i < n; i++) {
            out.write(0);
        }
    }

    /**
     * Encodes and writes pixel data
     */
    protected void writePixels() throws IOException {
        LZWEncoder encoder = new LZWEncoder(width, height, indexedPixels, colorDepth);
        encoder.encode(out);
    }

    /**
     * Write 16-bit value to output stream, LSB first
     */
    protected void writeShort(int value) throws IOException {
        out.write(value & 0xff);
        out.write((value >> 8) & 0xff);
    }

    /**
     * Writes string to output stream
     */
    protected void writeString(String s) throws IOException {
        for (int i = 0; i < s.length(); i++) {
            out.write((byte) s.charAt(i));
        }
    }


//	 ==============================================================================
//	 Adapted from Jef Poskanzer's Java port by way of J. M. G. Elliott.
//	 K Weiner 12/00

    class LZWEncoder {

        private static final int EOF = -1;

        private int imgW, imgH;

        private byte[] pixAry;

        private int initCodeSize;

        private int remaining;

        private int curPixel;

        // GIFCOMPR.C - GIF Image compression routines
        //
        // Lempel-Ziv compression based on 'compress'. GIF modifications by
        // David Rowley ([email protected])

        // General DEFINEs

        static final int BITS = 12;

        static final int HSIZE = 5003; // 80% occupancy

        // GIF Image compression - modified 'compress'
        //
        // Based on: compress.c - File compression ala IEEE Computer, June 1984.
        //
        // By Authors: Spencer W. Thomas (decvax!harpo!utah-cs!utah-gr!thomas)
        // Jim McKie (decvax!mcvax!jim)
        // Steve Davies (decvax!vax135!petsd!peora!srd)
        // Ken Turkowski (decvax!decwrl!turtlevax!ken)
        // James A. Woods (decvax!ihnp4!ames!jaw)
        // Joe Orost (decvax!vax135!petsd!joe)

        int n_bits; // number of bits/code

        int maxbits = BITS; // user settable max # bits/code

        int maxcode; // maximum code, given n_bits

        int maxmaxcode = 1 << BITS; // should NEVER generate this code

        int[] htab = new int[HSIZE];

        int[] codetab = new int[HSIZE];

        int hsize = HSIZE; // for dynamic table sizing

        int free_ent = 0; // first unused entry

        // block compression parameters -- after all codes are used up,
        // and compression rate changes, start over.
        boolean clear_flg = false;

        // Algorithm: use open addressing double hashing (no chaining) on the
        // prefix code / next character combination. We do a variant of Knuth's
        // algorithm D (vol. 3, sec. 6.4) along with G. Knott's relatively-prime
        // secondary probe. Here, the modular division first probe is gives way
        // to a faster exclusive-or manipulation. Also do block compression with
        // an adaptive reset, whereby the code table is cleared when the compression
        // ratio decreases, but after the table fills. The variable-length output
        // codes are re-sized at this point, and a special CLEAR code is generated
        // for the decompressor. Late addition: construct the table according to
        // file size for noticeable speed improvement on small files. Please direct
        // questions about this implementation to ames!jaw.

        int g_init_bits;

        int ClearCode;

        int EOFCode;

        // output
        //
        // Output the given code.
        // Inputs:
        // code: A n_bits-bit integer. If == -1, then EOF. This assumes
        // that n_bits =< wordsize - 1.
        // Outputs:
        // Outputs code to the file.
        // Assumptions:
        // Chars are 8 bits long.
        // Algorithm:
        // Maintain a BITS character long buffer (so that 8 codes will
        // fit in it exactly). Use the VAX insv instruction to insert each
        // code in turn. When the buffer fills up empty it and start over.

        int cur_accum = 0;

        int cur_bits = 0;

        int masks[] = { 0x0000, 0x0001, 0x0003, 0x0007, 0x000F, 0x001F, 0x003F, 0x007F, 0x00FF, 0x01FF,
                0x03FF, 0x07FF, 0x0FFF, 0x1FFF, 0x3FFF, 0x7FFF, 0xFFFF };

        // Number of characters so far in this 'packet'
        int a_count;

        // Define the storage for the packet accumulator
        byte[] accum = new byte[256];

        // ----------------------------------------------------------------------------
        LZWEncoder(int width, int height, byte[] pixels, int color_depth) {
            imgW = width;
            imgH = height;
            pixAry = pixels;
            initCodeSize = Math.max(2, color_depth);
        }

        // Add a character to the end of the current packet, and if it is 254
        // characters, flush the packet to disk.
        void char_out(byte c, OutputStream outs) throws IOException {
            accum[a_count++] = c;
            if (a_count >= 254)
                flush_char(outs);
        }

        // Clear out the hash table

        // table clear for block compress
        void cl_block(OutputStream outs) throws IOException {
            cl_hash(hsize);
            free_ent = ClearCode + 2;
            clear_flg = true;

            output(ClearCode, outs);
        }

        // reset code table
        void cl_hash(int hsize) {
            for (int i = 0; i < hsize; ++i)
                htab[i] = -1;
        }

        void compress(int init_bits, OutputStream outs) throws IOException {
            int fcode;
            int i /* = 0 */;
            int c;
            int ent;
            int disp;
            int hsize_reg;
            int hshift;

            // Set up the globals: g_init_bits - initial number of bits
            g_init_bits = init_bits;

            // Set up the necessary values
            clear_flg = false;
            n_bits = g_init_bits;
            maxcode = MAXCODE(n_bits);

            ClearCode = 1 << (init_bits - 1);
            EOFCode = ClearCode + 1;
            free_ent = ClearCode + 2;

            a_count = 0; // clear packet

            ent = nextPixel();

            hshift = 0;
            for (fcode = hsize; fcode < 65536; fcode *= 2)
                ++hshift;
            hshift = 8 - hshift; // set hash code range bound

            hsize_reg = hsize;
            cl_hash(hsize_reg); // clear hash table

            output(ClearCode, outs);

            outer_loop: while ((c = nextPixel()) != EOF) {
                fcode = (c << maxbits) + ent;
                i = (c << hshift) ^ ent; // xor hashing

                if (htab[i] == fcode) {
                    ent = codetab[i];
                    continue;
                } else if (htab[i] >= 0) // non-empty slot
                {
                    disp = hsize_reg - i; // secondary hash (after G. Knott)
                    if (i == 0)
                        disp = 1;
                    do {
                        if ((i -= disp) < 0)
                            i += hsize_reg;

                        if (htab[i] == fcode) {
                            ent = codetab[i];
                            continue outer_loop;
                        }
                    } while (htab[i] >= 0);
                }
                output(ent, outs);
                ent = c;
                if (free_ent < maxmaxcode) {
                    codetab[i] = free_ent++; // code -> hashtable
                    htab[i] = fcode;
                } else
                    cl_block(outs);
            }
            // Put out the final code.
            output(ent, outs);
            output(EOFCode, outs);
        }

        // ----------------------------------------------------------------------------
        void encode(OutputStream os) throws IOException {
            os.write(initCodeSize); // write "initial code size" byte

            remaining = imgW * imgH; // reset navigation variables
            curPixel = 0;

            compress(initCodeSize + 1, os); // compress and write the pixel data

            os.write(0); // write block terminator
        }

        // Flush the packet to disk, and reset the accumulator
        void flush_char(OutputStream outs) throws IOException {
            if (a_count > 0) {
                outs.write(a_count);
                outs.write(accum, 0, a_count);
                a_count = 0;
            }
        }

        final int MAXCODE(int n_bits) {
            return (1 << n_bits) - 1;
        }

        // ----------------------------------------------------------------------------
        // Return the next pixel from the image
        // ----------------------------------------------------------------------------
        private int nextPixel() {
            if (remaining == 0)
                return EOF;

            --remaining;

            byte pix = pixAry[curPixel++];

            return pix & 0xff;
        }

        void output(int code, OutputStream outs) throws IOException {
            cur_accum &= masks[cur_bits];

            if (cur_bits > 0)
                cur_accum |= (code << cur_bits);
            else
                cur_accum = code;

            cur_bits += n_bits;

            while (cur_bits >= 8) {
                char_out((byte) (cur_accum & 0xff), outs);
                cur_accum >>= 8;
                cur_bits -= 8;
            }

            // If the next entry is going to be too big for the code size,
            // then increase it, if possible.
            if (free_ent > maxcode || clear_flg) {
                if (clear_flg) {
                    maxcode = MAXCODE(n_bits = g_init_bits);
                    clear_flg = false;
                } else {
                    ++n_bits;
                    if (n_bits == maxbits)
                        maxcode = maxmaxcode;
                    else
                        maxcode = MAXCODE(n_bits);
                }
            }

            if (code == EOFCode) {
                // At EOF, write the rest of the buffer.
                while (cur_bits > 0) {
                    char_out((byte) (cur_accum & 0xff), outs);
                    cur_accum >>= 8;
                    cur_bits -= 8;
                }

                flush_char(outs);
            }
        }
    }


    /*
     * NeuQuant Neural-Net Quantization Algorithm
     * ------------------------------------------
     *
     * Copyright (c) 1994 Anthony Dekker
     *
     * NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994. See
     * "Kohonen neural networks for optimal colour quantization" in "Network:
     * Computation in Neural Systems" Vol. 5 (1994) pp 351-367. for a discussion of
     * the algorithm.
     *
     * Any party obtaining a copy of these files from the author, directly or
     * indirectly, is granted, free of charge, a full and unrestricted irrevocable,
     * world-wide, paid up, royalty-free, nonexclusive right and license to deal in
     * this software and documentation files (the "Software"), including without
     * limitation the rights to use, copy, modify, merge, publish, distribute,
     * sublicense, and/or sell copies of the Software, and to permit persons who
     * receive copies from any such party to do so, with the only requirement being
     * that this copyright notice remain intact.
     */

    //	 Ported to Java 12/00 K Weiner
    class NeuQuant {

        protected static final int netsize = 256; /* number of colours used */

        /* four primes near 500 - assume no image has a length so large */
        /* that it is divisible by all four primes */
        protected static final int prime1 = 499;

        protected static final int prime2 = 491;

        protected static final int prime3 = 487;

        protected static final int prime4 = 503;

        protected static final int minpicturebytes = (3 * prime4);

        /* minimum size for input image */

        /*
         * Program Skeleton ---------------- [select samplefac in range 1..30] [read
         * image from input file] pic = (unsigned char*) malloc(3*width*height);
         * initnet(pic,3*width*height,samplefac); learn(); unbiasnet(); [write output
         * image header, using writecolourmap(f)] inxbuild(); write output image using
         * inxsearch(b,g,r)
         */

        /*
         * Network Definitions -------------------
         */

        protected static final int maxnetpos = (netsize - 1);

        protected static final int netbiasshift = 4; /* bias for colour values */

        protected static final int ncycles = 100; /* no. of learning cycles */

        /* defs for freq and bias */
        protected static final int intbiasshift = 16; /* bias for fractions */

        protected static final int intbias = (((int) 1) << intbiasshift);

        protected static final int gammashift = 10; /* gamma = 1024 */

        protected static final int gamma = (((int) 1) << gammashift);

        protected static final int betashift = 10;

        protected static final int beta = (intbias >> betashift); /* beta = 1/1024 */

        protected static final int betagamma = (intbias << (gammashift - betashift));

        /* defs for decreasing radius factor */
        protected static final int initrad = (netsize >> 3); /*
         * for 256 cols, radius
         * starts
         */

        protected static final int radiusbiasshift = 6; /* at 32.0 biased by 6 bits */

        protected static final int radiusbias = (((int) 1) << radiusbiasshift);

        protected static final int initradius = (initrad * radiusbias); /*
         * and
         * decreases
         * by a
         */

        protected static final int radiusdec = 30; /* factor of 1/30 each cycle */

        /* defs for decreasing alpha factor */
        protected static final int alphabiasshift = 10; /* alpha starts at 1.0 */

        protected static final int initalpha = (((int) 1) << alphabiasshift);

        protected int alphadec; /* biased by 10 bits */

        /* radbias and alpharadbias used for radpower calculation */
        protected static final int radbiasshift = 8;

        protected static final int radbias = (((int) 1) << radbiasshift);

        protected static final int alpharadbshift = (alphabiasshift + radbiasshift);

        protected static final int alpharadbias = (((int) 1) << alpharadbshift);

        /*
         * Types and Global Variables --------------------------
         */

        protected byte[] thepicture; /* the input image itself */

        protected int lengthcount; /* lengthcount = H*W*3 */

        protected int samplefac; /* sampling factor 1..30 */

        // typedef int pixel[4]; /* BGRc */
        protected int[][] network; /* the network itself - [netsize][4] */

        protected int[] netindex = new int[256];

        /* for network lookup - really 256 */

        protected int[] bias = new int[netsize];

        /* bias and freq arrays for learning */
        protected int[] freq = new int[netsize];

        protected int[] radpower = new int[initrad];

        /* radpower for precomputation */

        /*
         * Initialise network in range (0,0,0) to (255,255,255) and set parameters
         * -----------------------------------------------------------------------
         */
        public NeuQuant(byte[] thepic, int len, int sample) {

            int i;
            int[] p;

            thepicture = thepic;
            lengthcount = len;
            samplefac = sample;

            network = new int[netsize][];
            for (i = 0; i < netsize; i++) {
                network[i] = new int[4];
                p = network[i];
                p[0] = p[1] = p[2] = (i << (netbiasshift + 8)) / netsize;
                freq[i] = intbias / netsize; /* 1/netsize */
                bias[i] = 0;
            }
        }

        public byte[] colorMap() {
            byte[] map = new byte[3 * netsize];
            int[] index = new int[netsize];
            for (int i = 0; i < netsize; i++)
                index[network[i][3]] = i;
            int k = 0;
            for (int i = 0; i < netsize; i++) {
                int j = index[i];
                map[k++] = (byte) (network[j][0]);
                map[k++] = (byte) (network[j][1]);
                map[k++] = (byte) (network[j][2]);
            }
            return map;
        }

        /*
         * Insertion sort of network and building of netindex[0..255] (to do after
         * unbias)
         * -------------------------------------------------------------------------------
         */
        public void inxbuild() {

            int i, j, smallpos, smallval;
            int[] p;
            int[] q;
            int previouscol, startpos;

            previouscol = 0;
            startpos = 0;
            for (i = 0; i < netsize; i++) {
                p = network[i];
                smallpos = i;
                smallval = p[1]; /* index on g */
                /* find smallest in i..netsize-1 */
                for (j = i + 1; j < netsize; j++) {
                    q = network[j];
                    if (q[1] < smallval) { /* index on g */
                        smallpos = j;
                        smallval = q[1]; /* index on g */
                    }
                }
                q = network[smallpos];
                /* swap p (i) and q (smallpos) entries */
                if (i != smallpos) {
                    j = q[0];
                    q[0] = p[0];
                    p[0] = j;
                    j = q[1];
                    q[1] = p[1];
                    p[1] = j;
                    j = q[2];
                    q[2] = p[2];
                    p[2] = j;
                    j = q[3];
                    q[3] = p[3];
                    p[3] = j;
                }
                /* smallval entry is now in position i */
                if (smallval != previouscol) {
                    netindex[previouscol] = (startpos + i) >> 1;
                    for (j = previouscol + 1; j < smallval; j++)
                        netindex[j] = i;
                    previouscol = smallval;
                    startpos = i;
                }
            }
            netindex[previouscol] = (startpos + maxnetpos) >> 1;
            for (j = previouscol + 1; j < 256; j++)
                netindex[j] = maxnetpos; /* really 256 */
        }

        /*
         * Main Learning Loop ------------------
         */
        public void learn() {

            int i, j, b, g, r;
            int radius, rad, alpha, step, delta, samplepixels;
            byte[] p;
            int pix, lim;

            if (lengthcount < minpicturebytes)
                samplefac = 1;
            alphadec = 30 + ((samplefac - 1) / 3);
            p = thepicture;
            pix = 0;
            lim = lengthcount;
            samplepixels = lengthcount / (3 * samplefac);
            delta = samplepixels / ncycles;
            alpha = initalpha;
            radius = initradius;

            rad = radius >> radiusbiasshift;
            if (rad <= 1)
                rad = 0;
            for (i = 0; i < rad; i++)
                radpower[i] = alpha * (((rad * rad - i * i) * radbias) / (rad * rad));

            // fprintf(stderr,"beginning 1D learning: initial radius=%d\n", rad);

            if (lengthcount < minpicturebytes)
                step = 3;
            else if ((lengthcount % prime1) != 0)
                step = 3 * prime1;
            else {
                if ((lengthcount % prime2) != 0)
                    step = 3 * prime2;
                else {
                    if ((lengthcount % prime3) != 0)
                        step = 3 * prime3;
                    else
                        step = 3 * prime4;
                }
            }

            i = 0;
            while (i < samplepixels) {
                b = (p[pix + 0] & 0xff) << netbiasshift;
                g = (p[pix + 1] & 0xff) << netbiasshift;
                r = (p[pix + 2] & 0xff) << netbiasshift;
                j = contest(b, g, r);

                altersingle(alpha, j, b, g, r);
                if (rad != 0)
                    alterneigh(rad, j, b, g, r); /* alter neighbours */

                pix += step;
                if (pix >= lim)
                    pix -= lengthcount;

                i++;
                if (delta == 0)
                    delta = 1;
                if (i % delta == 0) {
                    alpha -= alpha / alphadec;
                    radius -= radius / radiusdec;
                    rad = radius >> radiusbiasshift;
                    if (rad <= 1)
                        rad = 0;
                    for (j = 0; j < rad; j++)
                        radpower[j] = alpha * (((rad * rad - j * j) * radbias) / (rad * rad));
                }
            }
            // fprintf(stderr,"finished 1D learning: final alpha=%f
            // !\n",((float)alpha)/initalpha);
        }

        /*
         * Search for BGR values 0..255 (after net is unbiased) and return colour
         * index
         * ----------------------------------------------------------------------------
         */
        public int map(int b, int g, int r) {

            int i, j, dist, a, bestd;
            int[] p;
            int best;

            bestd = 1000; /* biggest possible dist is 256*3 */
            best = -1;
            i = netindex[g]; /* index on g */
            j = i - 1; /* start at netindex[g] and work outwards */

            while ((i < netsize) || (j >= 0)) {
                if (i < netsize) {
                    p = network[i];
                    dist = p[1] - g; /* inx key */
                    if (dist >= bestd)
                        i = netsize; /* stop iter */
                    else {
                        i++;
                        if (dist < 0)
                            dist = -dist;
                        a = p[0] - b;
                        if (a < 0)
                            a = -a;
                        dist += a;
                        if (dist < bestd) {
                            a = p[2] - r;
                            if (a < 0)
                                a = -a;
                            dist += a;
                            if (dist < bestd) {
                                bestd = dist;
                                best = p[3];
                            }
                        }
                    }
                }
                if (j >= 0) {
                    p = network[j];
                    dist = g - p[1]; /* inx key - reverse dif */
                    if (dist >= bestd)
                        j = -1; /* stop iter */
                    else {
                        j--;
                        if (dist < 0)
                            dist = -dist;
                        a = p[0] - b;
                        if (a < 0)
                            a = -a;
                        dist += a;
                        if (dist < bestd) {
                            a = p[2] - r;
                            if (a < 0)
                                a = -a;
                            dist += a;
                            if (dist < bestd) {
                                bestd = dist;
                                best = p[3];
                            }
                        }
                    }
                }
            }
            return (best);
        }

        public byte[] process() {
            learn();
            unbiasnet();
            inxbuild();
            return colorMap();
        }

        /*
         * Unbias network to give byte values 0..255 and record position i to prepare
         * for sort
         * -----------------------------------------------------------------------------------
         */
        public void unbiasnet() {

            int i;

            for (i = 0; i < netsize; i++) {
                network[i][0] >>= netbiasshift;
                network[i][1] >>= netbiasshift;
                network[i][2] >>= netbiasshift;
                network[i][3] = i; /* record colour no */
            }
        }

        /*
         * Move adjacent neurons by precomputed alpha*(1-((i-j)^2/[r]^2)) in
         * radpower[|i-j|]
         * ---------------------------------------------------------------------------------
         */
        protected void alterneigh(int rad, int i, int b, int g, int r) {

            int j, k, lo, hi, a, m;
            int[] p;

            lo = i - rad;
            if (lo < -1)
                lo = -1;
            hi = i + rad;
            if (hi > netsize)
                hi = netsize;

            j = i + 1;
            k = i - 1;
            m = 1;
            while ((j < hi) || (k > lo)) {
                a = radpower[m++];
                if (j < hi) {
                    p = network[j++];
                    try {
                        p[0] -= (a * (p[0] - b)) / alpharadbias;
                        p[1] -= (a * (p[1] - g)) / alpharadbias;
                        p[2] -= (a * (p[2] - r)) / alpharadbias;
                    } catch (Exception e) {
                    } // prevents 1.3 miscompilation
                }
                if (k > lo) {
                    p = network[k--];
                    try {
                        p[0] -= (a * (p[0] - b)) / alpharadbias;
                        p[1] -= (a * (p[1] - g)) / alpharadbias;
                        p[2] -= (a * (p[2] - r)) / alpharadbias;
                    } catch (Exception e) {
                    }
                }
            }
        }

        /*
         * Move neuron i towards biased (b,g,r) by factor alpha
         * ----------------------------------------------------
         */
        protected void altersingle(int alpha, int i, int b, int g, int r) {

            /* alter hit neuron */
            int[] n = network[i];
            n[0] -= (alpha * (n[0] - b)) / initalpha;
            n[1] -= (alpha * (n[1] - g)) / initalpha;
            n[2] -= (alpha * (n[2] - r)) / initalpha;
        }

        /*
         * Search for biased BGR values ----------------------------
         */
        protected int contest(int b, int g, int r) {

            /* finds closest neuron (min dist) and updates freq */
            /* finds best neuron (min dist-bias) and returns position */
            /* for frequently chosen neurons, freq[i] is high and bias[i] is negative */
            /* bias[i] = gamma*((1/netsize)-freq[i]) */

            int i, dist, a, biasdist, betafreq;
            int bestpos, bestbiaspos, bestd, bestbiasd;
            int[] n;

            bestd = ~(((int) 1) << 31);
            bestbiasd = bestd;
            bestpos = -1;
            bestbiaspos = bestpos;

            for (i = 0; i < netsize; i++) {
                n = network[i];
                dist = n[0] - b;
                if (dist < 0)
                    dist = -dist;
                a = n[1] - g;
                if (a < 0)
                    a = -a;
                dist += a;
                a = n[2] - r;
                if (a < 0)
                    a = -a;
                dist += a;
                if (dist < bestd) {
                    bestd = dist;
                    bestpos = i;
                }
                biasdist = dist - ((bias[i]) >> (intbiasshift - netbiasshift));
                if (biasdist < bestbiasd) {
                    bestbiasd = biasdist;
                    bestbiaspos = i;
                }
                betafreq = (freq[i] >> betashift);
                freq[i] -= betafreq;
                bias[i] += (betafreq << gammashift);
            }
            freq[bestpos] += beta;
            bias[bestpos] -= betagamma;
            return (bestbiaspos);
        }
    }

}

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