AnimatedGifEncoder.java Source code

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Here is the source code for AnimatedGifEncoder.java

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import java.awt.Color;
import java.awt.Graphics2D;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.BufferedOutputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;

/**
 * Class AnimatedGifEncoder - Encodes a GIF file consisting of one or more
 * frames.
 * 
 * <pre>
 *  Example:
 *     AnimatedGifEncoder e = new AnimatedGifEncoder();
 *     e.start(outputFileName);
 *     e.setDelay(1000);   // 1 frame per sec
 *     e.addFrame(image1);
 *     e.addFrame(image2);
 *     e.finish();
 * </pre>
 * 
 * No copyright asserted on the source code of this class. May be used for any
 * purpose, however, refer to the Unisys LZW patent for restrictions on use of
 * the associated LZWEncoder class. Please forward any corrections to
 * kweiner@fmsware.com.
 * 
 * @author Kevin Weiner, FM Software
 * @version 1.03 November 2003
 * 
 */

public class AnimatedGifEncoder {

    protected int width; // image size

    protected int height;

    protected Color transparent = null; // 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 BufferedImage 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 = Math.round(ms / 10.0f);
    }

    /**
     * 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(Color 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(BufferedImage 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 = Math.round(100f / 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) {
        if (started && !firstFrame)
            return;
        width = w;
        height = h;
        if (width < 1)
            width = 320;
        if (height < 1)
            height = 240;
        sizeSet = true;
    }

    /**
     * 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;
    }

    /**
     * Initiates writing of a GIF file with the specified name.
     * 
     * @param file
     *          String containing output file name.
     * @return false if open or initial write failed.
     */
    public boolean start(String file) {
        boolean ok = true;
        try {
            out = new BufferedOutputStream(new FileOutputStream(file));
            ok = start(out);
            closeStream = true;
        } 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 != null) {
            transIndex = findClosest(transparent);
        }
    }

    /**
     * Returns index of palette color closest to c
     * 
     */
    protected int findClosest(Color c) {
        if (colorTab == null)
            return -1;
        int r = c.getRed();
        int g = c.getGreen();
        int b = c.getBlue();
        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();
        int type = image.getType();
        if ((w != width) || (h != height) || (type != BufferedImage.TYPE_3BYTE_BGR)) {
            // create new image with right size/format
            BufferedImage temp = new BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR);
            Graphics2D g = temp.createGraphics();
            g.drawImage(image, 0, 0, null);
            image = temp;
        }
        pixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
    }

    /**
     * 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 == null) {
            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(0); // image position x,y = 0,0
        writeShort(0);
        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 (mgardi@watdcsu.waterloo.edu)

    // 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() {
        for (int 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);
    }
}