@thi.ng/pixel - npm Package Compare versions

Comparing version 0.6.1 to 0.7.1

api.d.ts

@@ -1,2 +0,2 @@
-import type { Fn, Fn2, IObjectOf, NumericArray, TypedArray, UintType } from "@thi.ng/api";
+import type { FloatArray, Fn, Fn2, Fn3, FnN, IObjectOf, NumericArray, TypedArray, UintType } from "@thi.ng/api";
 /**
@@ -299,2 +299,92 @@ * ABGR 8bit lane/channel IDs
 }
+export declare type PoolTemplate = Fn3<string[], number, number, string>;
+export interface ConvolutionKernelSpec {
+    /**
+     * Kernel coefficients.
+     */
+    spec: NumericArray;
+    /**
+     * Kernel size. If given as number, expands to `[size, size]`.
+     */
+    size: number | [number, number];
+}
+export interface PoolKernelSpec {
+    /**
+     * Code template function for {@link defPoolKernel}.
+     */
+    pool: PoolTemplate;
+    /**
+     * Kernel size. If given as number, expands to `[size, size]`.
+     */
+    size: number | [number, number];
+}
+export interface KernelFnSpec {
+    /**
+     * Kernel factory.
+     */
+    fn: Fn<IPixelBuffer<FloatArray, NumericArray>, FnN>;
+    /**
+     * Kernel size. If given as number, expands to `[size, size]`.
+     */
+    size: number | [number, number];
+}
+export declare type KernelSpec = ConvolutionKernelSpec | PoolKernelSpec | KernelFnSpec;
+export interface ConvolveOpts {
+    /**
+     * Convolution kernel details/implementation.
+     */
+    kernel: KernelSpec;
+    /**
+     * Channel ID to convolve.
+     *
+     * @defaultValue 0
+     */
+    channel?: number;
+    /**
+     * If true, the result image will be same size as source image with empty
+     * (padded) border pixels.
+     *
+     * @defaultValue true
+     */
+    pad?: boolean;
+    /**
+     * Result scale factor
+     *
+     * @defaultValue 1
+     */
+    scale?: number;
+    /**
+     * Step size to process only every nth pixel.
+     *
+     * @defaultValue 1
+     */
+    stride?: number | [number, number];
+}
+export interface NormalMapOpts {
+    /**
+     * Channel ID to use for gradient extraction in source image.
+     *
+     * @defaultValue 0
+     */
+    channel: number;
+    /**
+     * Step size (aka number of pixels) between left/right, top/bottom
+     * neighbors.
+     *
+     * @defaultValue 0
+     */
+    step: number;
+    /**
+     * Result gradient scale factor(s).
+     *
+     * @defaultValue 1
+     */
+    scale: number | [number, number];
+    /**
+     * Z-axis value to use in blue channel of normal map.
+     *
+     * @defaultValue 1
+     */
+    z: number;
+}
 //# sourceMappingURL=api.d.ts.map

CHANGELOG.md

@@ -6,2 +6,38 @@ # Change Log
 
+## [0.7.1](https://github.com/thi-ng/umbrella/compare/@thi.ng/pixel@[e-mail]/pixel@0.7.1) (2021-03-03)
+
+**Note:** Version bump only for package @thi.ng/pixel
+
+
+
+
+
+# [0.7.0](https://github.com/thi-ng/umbrella/compare/@thi.ng/pixel@[e-mail]/pixel@0.7.0) (2021-03-03)
+
+
+### Bug Fixes
+
+* **pixel:** add clamping for float->ABGR conversion ([41540e0](https://github.com/thi-ng/umbrella/commit/41540e085b2261208e44e6f25b327e3371eae2df))
+* **pixel:** fix POOL_NEAREST index ([b98d05d](https://github.com/thi-ng/umbrella/commit/b98d05d7827d98d3971bdbcd562735b96fa9b7ec))
+
+
+### Features
+
+* **pixel:** add 5x5 kernel presets ([56f96f4](https://github.com/thi-ng/umbrella/commit/56f96f4842e6a57087a565a8e5ce82e590da7d66))
+* **pixel:** add convolve() & preset kernels ([6a31dc3](https://github.com/thi-ng/umbrella/commit/6a31dc38f3f0ae48853d899420d0fbebcc6b8678))
+* **pixel:** add defKernel() kernel fn codegen ([25b97a3](https://github.com/thi-ng/umbrella/commit/25b97a341fa54ee8a82e3083fcb85a8061db8b1f))
+* **pixel:** add defLargeKernel(), conv presets ([9c71165](https://github.com/thi-ng/umbrella/commit/9c71165adb71103fa88a5486987f270fecd2f439))
+* **pixel:** add gradientImage() & FLOAT_NORMAL format ([78683b7](https://github.com/thi-ng/umbrella/commit/78683b701418bf184b2a1327cfd5e50397d687e0))
+* **pixel:** add IEmpty impls for Float/PackedBuffer ([46ac1a1](https://github.com/thi-ng/umbrella/commit/46ac1a1906b256eefab0934efea300c67db7ea28))
+* **pixel:** add normalMap(), add more kernels ([f32686d](https://github.com/thi-ng/umbrella/commit/f32686d463ffcb49b37e9b1b811ff5de06b58fed))
+* **pixel:** add POOL_THRESHOLD preset ([5f1c1de](https://github.com/thi-ng/umbrella/commit/5f1c1dea87251f8a584cbe94d83784e7e4cc31a5))
+* **pixel:** add step size support for normalMap() ([ab72a79](https://github.com/thi-ng/umbrella/commit/ab72a79532baab3f07f53419cb5970e90e97e0dd))
+* **pixel:** add/update buffer factory fns ([ba38e13](https://github.com/thi-ng/umbrella/commit/ba38e137c6913d048bb4d678137241ee179d160c))
+* **pixel:** update PackedBuffer.fromCanvas() ([3bdb086](https://github.com/thi-ng/umbrella/commit/3bdb0860bcd35a0475e83ebe948847f1ecd42db6))
+* **pixel:** update/extend/refactor convolveChannel/Image() ([6692865](https://github.com/thi-ng/umbrella/commit/6692865d5facb75bf667056afa9cfee93ade2da6))
+
+
+
+
+
 ## [0.6.1](https://github.com/thi-ng/umbrella/compare/@thi.ng/pixel@[e-mail]/pixel@0.6.1) (2021-02-20)
@@ -8,0 +44,0 @@

float.d.ts

@@ -1,2 +0,2 @@
-import { Fn, NumericArray } from "@thi.ng/api";
+import { Fn, ICopy, IEmpty, NumericArray } from "@thi.ng/api";
 import type { BlendFnFloat, BlitOpts, FloatFormat, FloatFormatSpec, IPixelBuffer, PackedFormat } from "./api";
@@ -12,4 +12,5 @@ import { PackedBuffer } from "./packed";
  */
-export declare const floatBuffer: (w: number, h: number, fmt: FloatFormat | FloatFormatSpec, pixels?: Float32Array | undefined) => FloatBuffer;
-export declare class FloatBuffer implements IPixelBuffer<Float32Array, NumericArray> {
+export declare function floatBuffer(w: number, h: number, fmt: FloatFormat | FloatFormatSpec, pixels?: Float32Array): FloatBuffer;
+export declare function floatBuffer(src: PackedBuffer, fmt: FloatFormat | FloatFormatSpec): FloatBuffer;
+export declare class FloatBuffer implements IPixelBuffer<Float32Array, NumericArray>, ICopy<FloatBuffer>, IEmpty<FloatBuffer> {
     /**
@@ -36,2 +37,3 @@ * Creates a new `FloatBuffer` from given {@link PackedBuffer} and using
     copy(): FloatBuffer;
+    empty(): FloatBuffer;
     getAt(x: number, y: number): NumericArray;
@@ -38,0 +40,0 @@ setAt(x: number, y: number, col: NumericArray): this;

float.js

@@ -8,11 +8,9 @@ import { assert } from "@thi.ng/api";
 import { clampRegion, ensureChannel, ensureSize, prepRegions } from "./utils";
-/**
- * Syntax sugar for {@link FloatBuffer} ctor.
- *
- * @param w -
- * @param h -
- * @param fmt -
- * @param pixels -
- */
-export const floatBuffer = (w, h, fmt, pixels) => new FloatBuffer(w, h, fmt, pixels);
+export function floatBuffer(...args) {
+    return args[0] instanceof PackedBuffer
+        ? // @ts-ignore
+            FloatBuffer.fromPacked(...args)
+        : // @ts-ignore
+            new FloatBuffer(...args);
+}
 export class FloatBuffer {
@@ -59,6 +57,9 @@ constructor(w, h, fmt, pixels) {
     copy() {
-        const dest = new FloatBuffer(this.width, this.height, this.format);
+        const dest = this.empty();
         dest.pixels.set(this.pixels);
         return dest;
     }
+    empty() {
+        return new FloatBuffer(this.width, this.height, this.format);
+    }
     getAt(x, y) {
@@ -65,0 +66,0 @@ const { width, stride } = this;

format/float-format.js

@@ -0,1 +1,2 @@
+import { clamp01 } from "@thi.ng/math";
 import { Lane } from "../api";
@@ -11,3 +12,3 @@ import { luminanceABGR } from "../utils";
     }
-    const to = (col, i) => ((col[i] * 0xff + 0.5) | 0) << chanShift[chan[i]];
+    const to = (col, i) => ((clamp01(col[i]) * 0xff + 0.5) | 0) << chanShift[chan[i]];
     const from = (col, i) => ((col >>> chanShift[chan[i]]) & 0xff) / 0xff;
@@ -42,3 +43,3 @@ switch (chan.length) {
 const defConvert1Gray = (res) => {
-    res.toABGR = (col) => ((((col[0] * 0xff + 0.5) | 0) * 0x010101) | 0xff000000) >>> 0;
+    res.toABGR = (col) => ((((clamp01(col[0]) * 0xff + 0.5) | 0) * 0x010101) | 0xff000000) >>> 0;
     res.fromABGR = (col, out = []) => ((out[0] = luminanceABGR(col) / 0xff), out);
@@ -63,3 +64,3 @@ };
     res.toABGR = (col) => {
-        let out = ((col[gray] * 0xff + 0.5) | 0) * 0x010101;
+        let out = ((clamp01(col[gray]) * 0xff + 0.5) | 0) * 0x010101;
         out |= ((col[alpha] * 0xff + 0.5) | 0) << 24;
@@ -66,0 +67,0 @@ return out >>> 0;

index.d.ts

 export * from "./api";
 export * from "./canvas";
 export * from "./codegen";
+export * from "./convolve";
 export * from "./dither";
 export * from "./float";
+export * from "./normal-map";
 export * from "./packed";
@@ -25,4 +27,5 @@ export * from "./utils";
 export * from "./format/float-hsva";
+export * from "./format/float-norm";
 export * from "./format/float-rgb";
 export * from "./format/float-rgba";
 //# sourceMappingURL=index.d.ts.map

index.js

 export * from "./api";
 export * from "./canvas";
 export * from "./codegen";
+export * from "./convolve";
 export * from "./dither";
 export * from "./float";
+export * from "./normal-map";
 export * from "./packed";
@@ -25,3 +27,4 @@ export * from "./utils";
 export * from "./format/float-hsva";
+export * from "./format/float-norm";
 export * from "./format/float-rgb";
 export * from "./format/float-rgba";

lib/index.js

@@ -126,2 +126,8 @@ 'use strict';
 };
+const asVec = (x) => checks.isNumber(x) ? [x, x] : x;
+const asIntVec = (x) => {
+    const v = asVec(x);
+    return [v[0] | 0, v[1] | 0];
+};
+const range = (n) => new Uint8Array(n).map((_, i) => i);
 
@@ -178,39 +184,2 @@ const compileLShift = (x, shift) => shift > 0
 
-const init = (x, y, size, val, step, mat) => {
-    if (size === 1) {
-        !mat[y] && (mat[y] = []);
-        mat[y][x] = val;
-        return mat;
-    }
-    size >>= 1;
-    const step4 = step << 2;
-    init(x, y, size, val, step4, mat);
-    init(x + size, y + size, size, val + step, step4, mat);
-    init(x + size, y, size, val + step * 2, step4, mat);
-    init(x, y + size, size, val + step * 3, step4, mat);
-    return mat;
-};
-const defBayer = (size) => ({
-    mat: init(0, 0, size, 0, 1, []),
-    invSize: 1 / (size * size),
-    mask: size - 1,
-});
-const orderedDither = ({ mat, mask, invSize }, dsteps, drange, srange, x, y, val) => {
-    val =
-        (dsteps * (val / srange) + mat[y & mask][x & mask] * invSize - 0.5) | 0;
-    dsteps--;
-    return math.clamp(val, 0, dsteps) * ((drange - 1) / dsteps);
-};
-const ditherPixels = (dest, src, width, height, mat, dsteps, drange, srange) => {
-    !dest && (dest = src.slice());
-    drange--;
-    for (let y = 0, i = 0; y < height; y++) {
-        for (let x = 0; x < width; x++) {
-            dest[i] = orderedDither(mat, dsteps, drange, srange, x, y, src[i]);
-            i++;
-        }
-    }
-    return dest;
-};
-
 const defFloatFormat = (fmt) => {
@@ -224,3 +193,3 @@ const chan = fmt.channels;
     }
-    const to = (col, i) => ((col[i] * 0xff + 0.5) | 0) << chanShift[chan[i]];
+    const to = (col, i) => ((math.clamp01(col[i]) * 0xff + 0.5) | 0) << chanShift[chan[i]];
     const from = (col, i) => ((col >>> chanShift[chan[i]]) & 0xff) / 0xff;
@@ -255,3 +224,3 @@ switch (chan.length) {
 const defConvert1Gray = (res) => {
-    res.toABGR = (col) => ((((col[0] * 0xff + 0.5) | 0) * 0x010101) | 0xff000000) >>> 0;
+    res.toABGR = (col) => ((((math.clamp01(col[0]) * 0xff + 0.5) | 0) * 0x010101) | 0xff000000) >>> 0;
     res.fromABGR = (col, out = []) => ((out[0] = luminanceABGR(col) / 0xff), out);
@@ -276,3 +245,3 @@ };
     res.toABGR = (col) => {
-        let out = ((col[gray] * 0xff + 0.5) | 0) * 0x010101;
+        let out = ((math.clamp01(col[gray]) * 0xff + 0.5) | 0) * 0x010101;
         out |= ((col[alpha] * 0xff + 0.5) | 0) << 24;
@@ -325,2 +294,39 @@ return out >>> 0;
 
+const init = (x, y, size, val, step, mat) => {
+    if (size === 1) {
+        !mat[y] && (mat[y] = []);
+        mat[y][x] = val;
+        return mat;
+    }
+    size >>= 1;
+    const step4 = step << 2;
+    init(x, y, size, val, step4, mat);
+    init(x + size, y + size, size, val + step, step4, mat);
+    init(x + size, y, size, val + step * 2, step4, mat);
+    init(x, y + size, size, val + step * 3, step4, mat);
+    return mat;
+};
+const defBayer = (size) => ({
+    mat: init(0, 0, size, 0, 1, []),
+    invSize: 1 / (size * size),
+    mask: size - 1,
+});
+const orderedDither = ({ mat, mask, invSize }, dsteps, drange, srange, x, y, val) => {
+    val =
+        (dsteps * (val / srange) + mat[y & mask][x & mask] * invSize - 0.5) | 0;
+    dsteps--;
+    return math.clamp(val, 0, dsteps) * ((drange - 1) / dsteps);
+};
+const ditherPixels = (dest, src, width, height, mat, dsteps, drange, srange) => {
+    !dest && (dest = src.slice());
+    drange--;
+    for (let y = 0, i = 0; y < height; y++) {
+        for (let x = 0; x < width; x++) {
+            dest[i] = orderedDither(mat, dsteps, drange, srange, x, y, src[i]);
+            i++;
+        }
+    }
+    return dest;
+};
+
 const defChannel = (ch, idx, shift) => {
@@ -380,3 +386,8 @@ const num = 1 << ch.size;
 
-const packedBuffer = (w, h, fmt, pixels) => new PackedBuffer(w, h, fmt, pixels);
+function packedBuffer(...args) {
+    return args[0] instanceof PackedBuffer
+        ? args[0].as(args[1])
+        :
+            new PackedBuffer(...args);
+}
 const buffer = packedBuffer;
@@ -393,16 +404,22 @@ class PackedBuffer {
     static fromImage(img, fmt, width, height = width) {
-        const ctx = imageCanvas(img, width, height);
-        const w = ctx.canvas.width;
-        const h = ctx.canvas.height;
-        const src = new Uint32Array(ctx.ctx.getImageData(0, 0, w, h).data.buffer);
-        const dest = api.typedArray(fmt.type, w * h);
-        const from = fmt.fromABGR;
-        for (let i = dest.length; --i >= 0;) {
-            dest[i] = from(src[i]);
+        return PackedBuffer.fromCanvas(imageCanvas(img, width, height).canvas, fmt);
+    }
+    static fromCanvas(canvas, fmt = ABGR8888) {
+        const ctx = canvasPixels(canvas);
+        const w = canvas.width;
+        const h = canvas.height;
+        let dest;
+        if (fmt === ABGR8888) {
+            dest = ctx.pixels;
         }
+        else {
+            dest = api.typedArray(fmt.type, w * h);
+            const src = ctx.pixels;
+            const from = fmt.fromABGR;
+            for (let i = dest.length; --i >= 0;) {
+                dest[i] = from(src[i]);
+            }
+        }
         return new PackedBuffer(w, h, fmt, dest);
     }
-    static fromCanvas(canvas) {
-        return new PackedBuffer(canvas.width, canvas.height, ABGR8888, canvasPixels(canvas).pixels);
-    }
     get stride() {
@@ -415,6 +432,9 @@ return 1;
     copy() {
-        const dest = new PackedBuffer(this.width, this.height, this.format);
+        const dest = this.empty();
         dest.pixels.set(this.pixels);
         return dest;
     }
+    empty() {
+        return new PackedBuffer(this.width, this.height, this.format);
+    }
     getAt(x, y) {
@@ -621,3 +641,9 @@ return x >= 0 && x < this.width && y >= 0 && y < this.height
 
-const floatBuffer = (w, h, fmt, pixels) => new FloatBuffer(w, h, fmt, pixels);
+function floatBuffer(...args) {
+    return args[0] instanceof PackedBuffer
+        ?
+            FloatBuffer.fromPacked(...args)
+        :
+            new FloatBuffer(...args);
+}
 class FloatBuffer {
@@ -654,6 +680,9 @@ constructor(w, h, fmt, pixels) {
     copy() {
-        const dest = new FloatBuffer(this.width, this.height, this.format);
+        const dest = this.empty();
         dest.pixels.set(this.pixels);
         return dest;
     }
+    empty() {
+        return new FloatBuffer(this.width, this.height, this.format);
+    }
     getAt(x, y) {
@@ -818,2 +847,228 @@ const { width, stride } = this;
 
+const convolveChannel = (src, opts) => convolve(initConvolve(src, opts));
+const convolveImage = (src, opts) => {
+    const state = initConvolve(src, opts);
+    const dest = new FloatBuffer(state.dwidth, state.dheight, src.format);
+    for (let channel of opts.channels || range(src.format.channels.length)) {
+        dest.setChannel(channel, convolve(Object.assign(Object.assign({}, state), { channel })));
+    }
+    return dest;
+};
+const convolve = ({ channel, dest, dwidth, kernel, kh2, kw2, pad, rowStride, scale, src, srcStride, strideX, strideY, }) => {
+    ensureChannel(src.format, channel);
+    const maxY = src.height - kh2;
+    const maxX = src.width - kw2;
+    const padX = pad && strideX === 1;
+    const padY = pad && strideY === 1;
+    const dpix = dest.pixels;
+    for (let sy = kh2, dy = padY ? kh2 : 0; sy < maxY; sy += strideY, dy++) {
+        for (let x = kw2, i = sy * rowStride + x * srcStride + channel, j = dy * dwidth + (padX ? x : 0); x < maxX; x += strideX, i += strideX * srcStride, j++) {
+            dpix[j] = kernel(i) * scale;
+        }
+    }
+    return dest;
+};
+const initKernel = (src, kernel, kw, kh) => (checks.isFunction(kernel.fn)
+    ? kernel.fn
+    : defKernel(kernel.spec ||
+        kernel.pool, kw, kh))(src);
+const initConvolve = (src, opts) => {
+    const { kernel, channel, stride: sampleStride, pad, scale } = Object.assign({ channel: 0, pad: true, scale: 1, stride: 1 }, opts);
+    const size = kernel.size;
+    const [kw, kh] = asIntVec(size);
+    const [strideX, strideY] = asIntVec(sampleStride);
+    api.assert(strideX >= 1 && strideY >= 1, `illegal stride: ${sampleStride}`);
+    const { width, height, stride: srcStride, rowStride } = src;
+    api.assert(kw >= 0 && kw <= width && kh >= 0 && kh <= height, `invalid kernel size: ${size}`);
+    const dwidth = destSize(width, strideX, kw, pad);
+    const dheight = destSize(height, strideY, kh, pad);
+    const dest = new FloatBuffer(dwidth, dheight, FLOAT_GRAY);
+    return {
+        channel,
+        dest,
+        dheight,
+        dwidth,
+        kernel: initKernel(src, kernel, kw, kh),
+        kh2: kh >> 1,
+        kw2: kw >> 1,
+        pad,
+        rowStride,
+        scale,
+        src,
+        srcStride,
+        strideX,
+        strideY,
+    };
+};
+const destSize = (orig, res, k, pad) => pad ? Math.floor(orig / res) : Math.ceil((orig - k + 1) / res);
+const defKernel = (tpl, w, h) => {
+    if (w * h > 1024 && !checks.isFunction(tpl))
+        return defLargeKernel(tpl, w, h);
+    const isPool = checks.isFunction(tpl);
+    const prefix = [];
+    const prefixI = [];
+    const body = [];
+    const kvars = [];
+    const h2 = h >> 1;
+    const w2 = w >> 1;
+    for (let y = 0, i = 0; y < h; y++) {
+        const yy = y - h2;
+        const row = [];
+        for (let x = 0; x < w; x++, i++) {
+            const kv = `k${y}_${x}`;
+            kvars.push(kv);
+            const xx = x - w2;
+            const idx = (yy !== 0 ? `i${y}` : `i`) + (xx !== 0 ? `+x${x}` : "");
+            isPool
+                ? row.push(`pix[${idx}]`)
+                : tpl[i] !== 0 && row.push(`${kv}*pix[${idx}]`);
+            y === 0 && xx !== 0 && prefix.push(`const x${x} = ${xx} * stride;`);
+        }
+        row.length && body.push(...row);
+        if (yy !== 0) {
+            prefix.push(`const y${y} = ${yy} * rowStride;`);
+            prefixI.push(`const i${y} = i + y${y};`);
+        }
+    }
+    const decls = isPool
+        ? ""
+        : `const [${kvars.join(", ")}] = [${tpl.join(", ")}];`;
+    const inner = isPool ? tpl(body, w, h) : body.join(" + ");
+    const fnBody = [
+        decls,
+        "const { pixels: pix, stride, rowStride } = src;",
+        ...prefix,
+        "return (i) => {",
+        ...prefixI,
+        `return ${inner};`,
+        "}",
+    ].join("\n");
+    return new Function("src", fnBody);
+};
+const defLargeKernel = (kernel, w, h) => {
+    const h2 = h >> 1;
+    const w2 = w >> 1;
+    return (src) => {
+        const { pixels, rowStride, stride } = src;
+        return (i) => {
+            let sum = 0;
+            for (let y = -h2, k = 0; y <= h2; y++) {
+                for (let x = -w2, ii = i + y * rowStride; x <= w2; x++, ii += stride, k++) {
+                    sum += kernel[k] * pixels[ii];
+                }
+            }
+            return sum;
+        };
+    };
+};
+const POOL_NEAREST = (body, w, h) => body[(h >> 1) * w + (w >> 1)];
+const POOL_MEAN = (body, w, h) => `(${body.join("+")})*${1 / (w * h)}`;
+const POOL_MIN = (body) => `Math.min(${body.join(",")})`;
+const POOL_MAX = (body) => `Math.max(${body.join(",")})`;
+const POOL_THRESHOLD = (bias = 0) => (body, w, h) => {
+    const center = POOL_NEAREST(body, w, h);
+    const mean = `(${body.join("+")})/${w * h}`;
+    return `(${center} - ${mean} + ${bias}) < 0 ? 0 : 1`;
+};
+const SOBEL_X = {
+    spec: [-1, -2, -1, 0, 0, 0, 1, 2, 1],
+    size: 3,
+};
+const SOBEL_Y = {
+    spec: [-1, 0, 1, -2, 0, 2, -1, 0, 1],
+    size: 3,
+};
+const SHARPEN3 = {
+    spec: [0, -1, 0, -1, 5, -1, 0, -1, 0],
+    size: 3,
+};
+const HIGHPASS3 = {
+    spec: [-1, -1, -1, -1, 9, -1, -1, -1, -1],
+    size: 3,
+};
+const BOX_BLUR3 = {
+    pool: POOL_MEAN,
+    size: 3,
+};
+const BOX_BLUR5 = {
+    pool: POOL_MEAN,
+    size: 5,
+};
+const GAUSSIAN_BLUR3 = {
+    spec: [1 / 16, 1 / 8, 1 / 16, 1 / 8, 1 / 4, 1 / 8, 1 / 16, 1 / 8, 1 / 16],
+    size: 3,
+};
+const GAUSSIAN_BLUR5 = {
+    spec: [
+        1 / 256, 1 / 64, 3 / 128, 1 / 64, 1 / 256,
+        1 / 64, 1 / 16, 3 / 32, 1 / 16, 1 / 64,
+        3 / 128, 3 / 32, 9 / 64, 3 / 32, 3 / 128,
+        1 / 64, 1 / 16, 3 / 32, 1 / 16, 1 / 64,
+        1 / 256, 1 / 64, 3 / 128, 1 / 64, 1 / 256,
+    ],
+    size: 5,
+};
+const GAUSSIAN = (r) => {
+    r |= 0;
+    api.assert(r > 0, `invalid kernel radius: ${r}`);
+    const sigma = -1 / (2 * (Math.hypot(r, r) / 3) ** 2);
+    const res = [];
+    let sum = 0;
+    for (let y = -r; y <= r; y++) {
+        for (let x = -r; x <= r; x++) {
+            const g = Math.exp((x * x + y * y) * sigma);
+            res.push(g);
+            sum += g;
+        }
+    }
+    return { spec: res.map((x) => x / sum), size: r * 2 + 1 };
+};
+const UNSHARP_MASK5 = {
+    spec: [
+        -1 / 256, -1 / 64, -3 / 128, -1 / 64, -1 / 256,
+        -1 / 64, -1 / 16, -3 / 32, -1 / 16, -1 / 64,
+        -3 / 128, -3 / 32, 119 / 64, -3 / 32, -3 / 128,
+        -1 / 64, -1 / 16, -3 / 32, -1 / 16, -1 / 64,
+        -1 / 256, -1 / 64, -3 / 128, -1 / 64, -1 / 256,
+    ],
+    size: 5,
+};
+
+const from = (x) => x / 127.5 - 1;
+const to = (x, shift) => math.clamp(x * 127.5 + 128, 0, 255) << shift;
+const FLOAT_NORMAL = {
+    __float: true,
+    alpha: false,
+    gray: false,
+    channels: [exports.Lane.RED, exports.Lane.GREEN, exports.Lane.BLUE],
+    shift: { 3: 0, 2: 8, 1: 16 },
+    size: 3,
+    fromABGR: (src) => [
+        from(src & 0xff),
+        from((src >> 8) & 0xff),
+        from((src >> 16) & 0xff),
+    ],
+    toABGR: (src) => to(src[0], 0) | to(src[1], 8) | to(src[2], 16) | 0xff000000,
+};
+
+const normalMap = (src, opts) => {
+    const { channel, step, scale, z } = Object.assign({ channel: 0, step: 0, scale: 1, z: 1 }, opts);
+    ensureChannel(src.format, channel);
+    const spec = [-1, ...new Array(step).fill(0), 1];
+    const [sx, sy] = asVec(scale);
+    const dest = new FloatBuffer(src.width, src.height, FLOAT_NORMAL);
+    dest.setChannel(0, convolveChannel(src, {
+        kernel: { spec, size: [step + 2, 1] },
+        scale: sx,
+        channel,
+    }));
+    dest.setChannel(1, convolveChannel(src, {
+        kernel: { spec, size: [1, step + 2] },
+        scale: sy,
+        channel,
+    }));
+    dest.setChannel(2, z);
+    return dest;
+};
+
 const ALPHA8 = defPackedFormat({
@@ -1015,8 +1270,14 @@ type: "u8",
 exports.BGR888 = BGR888;
+exports.BOX_BLUR3 = BOX_BLUR3;
+exports.BOX_BLUR5 = BOX_BLUR5;
 exports.FLOAT_GRAY = FLOAT_GRAY;
 exports.FLOAT_GRAY_ALPHA = FLOAT_GRAY_ALPHA;
 exports.FLOAT_HSVA = FLOAT_HSVA;
+exports.FLOAT_NORMAL = FLOAT_NORMAL;
 exports.FLOAT_RGB = FLOAT_RGB;
 exports.FLOAT_RGBA = FLOAT_RGBA;
 exports.FloatBuffer = FloatBuffer;
+exports.GAUSSIAN = GAUSSIAN;
+exports.GAUSSIAN_BLUR3 = GAUSSIAN_BLUR3;
+exports.GAUSSIAN_BLUR5 = GAUSSIAN_BLUR5;
 exports.GRAY16 = GRAY16;
@@ -1026,5 +1287,17 @@ exports.GRAY8 = GRAY8;
 exports.GRAY_ALPHA8 = GRAY_ALPHA8;
+exports.HIGHPASS3 = HIGHPASS3;
+exports.POOL_MAX = POOL_MAX;
+exports.POOL_MEAN = POOL_MEAN;
+exports.POOL_MIN = POOL_MIN;
+exports.POOL_NEAREST = POOL_NEAREST;
+exports.POOL_THRESHOLD = POOL_THRESHOLD;
 exports.PackedBuffer = PackedBuffer;
 exports.RGB565 = RGB565;
 exports.RGB888 = RGB888;
+exports.SHARPEN3 = SHARPEN3;
+exports.SOBEL_X = SOBEL_X;
+exports.SOBEL_Y = SOBEL_Y;
+exports.UNSHARP_MASK5 = UNSHARP_MASK5;
+exports.asIntVec = asIntVec;
+exports.asVec = asVec;
 exports.buffer = buffer;
@@ -1038,4 +1311,8 @@ exports.canvas2d = canvas2d;
 exports.compileToABGR = compileToABGR;
+exports.convolveChannel = convolveChannel;
+exports.convolveImage = convolveImage;
 exports.defBayer = defBayer;
 exports.defFloatFormat = defFloatFormat;
+exports.defKernel = defKernel;
+exports.defLargeKernel = defLargeKernel;
 exports.defPackedFormat = defPackedFormat;
@@ -1049,5 +1326,7 @@ exports.ditherPixels = ditherPixels;
 exports.luminanceABGR = luminanceABGR;
+exports.normalMap = normalMap;
 exports.orderedDither = orderedDither;
 exports.packedBuffer = packedBuffer;
 exports.prepRegions = prepRegions;
+exports.range = range;
 exports.setChannelConvert = setChannelConvert;
@@ -1054,0 +1333,0 @@ exports.setChannelSame = setChannelSame;

lib/index.umd.js

@@ -1,1 +0,1 @@
-!function(t,e){"object"==typeof exports&&"undefined"!=typeof module?e(exports,require("@thi.ng/checks"),require("@thi.ng/api"),require("@thi.ng/math"),require("@thi.ng/porter-duff"),require("@thi.ng/binary")):"function"==typeof define&&define.amd?define(["exports","@thi.ng/checks","@thi.ng/api","@thi.ng/math","@thi.ng/porter-duff","@thi.ng/binary"],e):e(((t="undefined"!=typeof globalThis?globalThis:t||self).thi=t.thi||{},t.thi.ng=t.thi.ng||{},t.thi.ng.pixel={}),t.thi.ng.checks,t.thi.ng.api,t.thi.ng.math,t.thi.ng.porterDuff,t.thi.ng.binary)}(this,(function(t,e,s,i,n,r){"use strict";var a,h,l;t.Lane=void 0,(a=t.Lane||(t.Lane={}))[a.ALPHA=0]="ALPHA",a[a.BLUE=1]="BLUE",a[a.GREEN=2]="GREEN",a[a.RED=3]="RED",t.Wrap=void 0,(h=t.Wrap||(t.Wrap={}))[h.NONE=0]="NONE",h[h.U=1]="U",h[h.V=2]="V",h[h.UV=3]="UV",t.Filter=void 0,(l=t.Filter||(t.Filter={}))[l.NEAREST=0]="NEAREST",l[l.LINEAR=1]="LINEAR";const o=(t,e=t,s)=>{const i=document.createElement("canvas");return i.width=t,i.height=e,s&&s.appendChild(i),{canvas:i,ctx:i.getContext("2d")}};function c(t,s){let i,n;if(e.isNumber(t)){const e=o(t,s);i=e.canvas,n=e.ctx}else i=t,n=i.getContext("2d");const r=n.getImageData(0,0,i.width,i.height);return{canvas:i,ctx:n,img:r,pixels:new Uint32Array(r.data.buffer)}}const f=(t,s,i=s,n)=>{const r=e.isNumber(s)?o(s,i,n):o(t.width,t.height,n);return r.ctx.drawImage(t,0,0,r.canvas.width,r.canvas.height),r},p=(t,e,i,n=1)=>s.assert(t.length>=e*i*n,"pixel buffer too small"),u=(t,e)=>{const i=t.channels[e];return s.assert(null!=i,`invalid channel ID: ${e}`),i},m=t=>(29*(t>>>16&255)+150*(t>>>8&255)+76*(255&t))/255,d=(t,e,s,n,r,a,h=0,l=0)=>(s|=0,n|=0,(t|=0)<0&&(s+=t,h-=t,t=0),(e|=0)<0&&(n+=e,l-=e,e=0),[t,e,i.clamp(s,0,r-t),i.clamp(n,0,a-e),h,l]),A=(t,e,s={})=>{let i,n,r,a,h,l,o=t.width,c=e.width;return[i,n,h,l]=d(s.sx||0,s.sy||0,s.w||o,s.h||t.height,o,t.height),[r,a,h,l,i,n]=d(s.dx||0,s.dy||0,h,l,c,e.height,i,n),{sx:i,sy:n,dx:r,dy:a,rw:h,rh:l}},g=(t,e,s)=>{for(let i=t.length;--i>=0;)t[i]=s(t[i],e)},R=(t,e,s,i)=>{for(let n=t.length;--n>=0;)t[n]=i(t[n],s(e[n]))},w=(t,e,s,i,n)=>{const r=~n;for(let a=t.length;--a>=0;)t[a]=t[a]&r|s(i(e[a]))&n},x=(t,e,s)=>{const i=e.fromABGR,n=e.toABGR;for(let e=t.length;--e>=0;)t[e]=i(s(n(t[e])))},L=(t,e)=>e>0?`(${t} << ${e})`:e<0?`(${t} >>> ${-e})`:`${t}`,G=(t,e)=>L(t,-e),y=t=>`0x${t.toString(16)}`,B=t=>{const e=(1<<t)-1;return new Function("luma",`return (x) => ${G("luma(x)",8-t)} & ${e};`)(m)},z=t=>{let e;if(8!==t){const s=(1<<t)-1;e=`(((x & ${s}) * ${255/s}) | 0)`}else e="x";return new Function("x",`return 0xff000000 | (${e} * 0x010101);`)},E=t=>new Function("x","return ("+t.map((t=>{const e=t.abgrShift+(8-t.size);return`(${G("x",e)} & ${y(t.maskA)})`})).join(" | ")+") >>> 0;"),b=(t,e)=>{const s=t.map((t=>{if(8!==t.size){const e=t.mask0,s=255/e,i=G("x",t.shift);return L(`((${i} & ${e}) * ${s})`,24-8*t.lane)}return L(`(x & ${y(t.maskA)})`,t.abgrShift)})).join(" | ");return new Function("x",`return (${e?"":"0xff000000 | "}${s}) >>> 0;`)},v=(t,e,s,i,n,r)=>{if(1===s)return!r[e]&&(r[e]=[]),r[e][t]=i,r;const a=n<<2;return v(t,e,s>>=1,i,a,r),v(t+s,e+s,s,i+n,a,r),v(t+s,e,s,i+2*n,a,r),v(t,e+s,s,i+3*n,a,r),r},D=t=>({mat:v(0,0,t,0,1,[]),invSize:1/(t*t),mask:t-1}),F=({mat:t,mask:e,invSize:s},n,r,a,h,l,o)=>(o=n*(o/a)+t[l&e][h&e]*s-.5|0,n--,i.clamp(o,0,n)*((r-1)/n)),P=t=>{const e=t.channels,s=e.reduce(((t,e)=>(t[e]=3-e<<3,t)),{}),i=Object.assign(Object.assign({},t),{size:e.length,shift:s,__float:!0});if(t.convert)return Object.assign(i,t.convert),i;const n=(t,i)=>(255*t[i]+.5|0)<<s[e[i]],r=(t,i)=>(t>>>s[e[i]]&255)/255;switch(e.length){case 1:t.gray?C(i):N(i,r,n);break;case 2:t.gray?_(i,r):S(i,r,n);break;case 3:U(i,r,n);break;case 4:k(i,r,n)}return i},N=(t,e,s)=>{t.toABGR=e=>{let i=t.alpha?0:4278190080;return i|=s(e,0),i>>>0},t.fromABGR=(t,s=[])=>(s[0]=e(t,0),s)},C=t=>{t.toABGR=t=>(65793*(255*t[0]+.5|0)|4278190080)>>>0,t.fromABGR=(t,e=[])=>(e[0]=m(t)/255,e)},S=(t,e,s)=>{t.toABGR=e=>{let i=t.alpha?0:4278190080;return i|=s(e,0),i|=s(e,1),i>>>0},t.fromABGR=(t,s=[])=>(s[0]=e(t,0),s[1]=e(t,1),s)},_=(e,s)=>{const i=~~(e.channels[0]===t.Lane.ALPHA),n=1^i;e.toABGR=t=>{let e=65793*(255*t[i]+.5|0);return e|=(255*t[n]+.5|0)<<24,e>>>0},e.fromABGR=(t,e=[])=>(e[i]=m(t)/255,e[n]=s(t,n),e)},U=(t,e,s)=>{t.toABGR=e=>{let i=t.alpha?0:4278190080;return i|=s(e,0),i|=s(e,1),i|=s(e,2),i>>>0},t.fromABGR=(t,s=[])=>(s[0]=e(t,0),s[1]=e(t,1),s[2]=e(t,2),s)},k=(t,e,s)=>{t.toABGR=e=>{let i=t.alpha?0:4278190080;return i|=s(e,0),i|=s(e,1),i|=s(e,2),i|=s(e,3),i>>>0},t.fromABGR=(t,s=[])=>(s[0]=e(t,0),s[1]=e(t,1),s[2]=e(t,2),s[3]=e(t,3),s)},$=P({gray:!0,channels:[t.Lane.RED]}),I=t=>{s.assert(t.channels.length>0,"no channel specs given");const e=t.channels.reduce((([t,e],s,n)=>(e-=s.size,t.push(((t,e,s)=>{const 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s=(t>>>24&255)/255,i=(t>>>16&255)/255,r=(t>>>8&255)/255,a=(255&t)/255;let h,l,o,c,f,p,u,d;r<i?(h=i,l=r,o=-1,c=2/3):(h=r,l=i,o=0,c=-1/3),a<h?(f=h,p=l,u=c,d=a):(f=a,p=l,u=o,d=h);const m=f-xt(p,d);return f=n.clamp01(f),e[0]=n.clamp01(Lt((d-p)/(6*m+n.EPS)+u)),e[1]=n.clamp01(m/(f+n.EPS)),e[2]=f,e[3]=s,e},toABGR:t=>{const e=6*t[0],s=t[1],i=255*t[2],r=255*t[3],a=((n.clamp01(Lt(e-3)-1)-1)*s+1)*i,h=((n.clamp01(2-Lt(e-2))-1)*s+1)*i;return(r<<24|((n.clamp01(2-Lt(e-4))-1)*s+1)*i<<16|h<<8|a)>>>0}}}),yt=N({channels:[t.Lane.RED,t.Lane.GREEN,t.Lane.BLUE]}),Gt=N({alpha:!0,channels:[t.Lane.RED,t.Lane.GREEN,t.Lane.BLUE,t.Lane.ALPHA]});t.ABGR8888=M,t.ALPHA8=lt,t.ARGB1555=ot,t.ARGB4444=ct,t.ARGB8888=ft,t.BGR888=pt,t.BOX_BLUR3=nt,t.BOX_BLUR5=it,t.FLOAT_GRAY=C,t.FLOAT_GRAY_ALPHA=wt,t.FLOAT_HSVA=Bt,t.FLOAT_NORMAL=ht,t.FLOAT_RGB=yt,t.FLOAT_RGBA=Gt,t.FloatBuffer=X,t.GAUSSIAN=t=>{t|=0,s.assert(t>0,`invalid kernel radius: ${t}`);const e=-1/(2*(Math.hypot(t,t)/3)**2),n=[];let i=0;for(let s=-t;s<=t;s++)for(let r=-t;r<=t;r++){const t=Math.exp((r*r+s*s)*e);n.push(t),i+=t}return{spec:n.map((t=>t/i)),size:2*t+1}},t.GAUSSIAN_BLUR3={spec:[1/16,1/8,1/16,1/8,1/4,1/8,1/16,1/8,1/16],size:3},t.GAUSSIAN_BLUR5={spec:[1/256,1/64,3/128,1/64,1/256,1/64,1/16,3/32,1/16,1/64,3/128,3/32,9/64,3/32,3/128,1/64,1/16,3/32,1/16,1/64,1/256,1/64,3/128,1/64,1/256],size:5},t.GRAY16=ut,t.GRAY8=mt,t.GRAY_ALPHA16=dt,t.GRAY_ALPHA8=At,t.HIGHPASS3={spec:[-1,-1,-1,-1,9,-1,-1,-1,-1],size:3},t.POOL_MAX=t=>`Math.max(${t.join(",")})`,t.POOL_MEAN=st,t.POOL_MIN=t=>`Math.min(${t.join(",")})`,t.POOL_NEAREST=et,t.POOL_THRESHOLD=(t=0)=>(e,s,n)=>`(${et(e,s,n)} - ${`(${e.join("+")})/${s*n}`} + ${t}) < 0 ? 0 : 1`,t.PackedBuffer=V,t.RGB565=gt,t.RGB888=Rt,t.SHARPEN3={spec:[0,-1,0,-1,5,-1,0,-1,0],size:3},t.SOBEL_X={spec:[-1,-2,-1,0,0,0,1,2,1],size:3},t.SOBEL_Y={spec:[-1,0,1,-2,0,2,-1,0,1],size:3},t.UNSHARP_MASK5={spec:[-1/256,-1/64,-3/128,-1/64,-1/256,-1/64,-1/16,-3/32,-1/16,-1/64,-3/128,-3/32,119/64,-3/32,-3/128,-1/64,-1/16,-3/32,-1/16,-1/64,-1/256,-1/64,-3/128,-1/64,-1/256],size:5},t.asIntVec=B,t.asVec=x,t.buffer=Y,t.canvas2d=o,t.canvasPixels=c,t.clampRegion=m,t.compileFromABGR=S,t.compileGrayFromABGR=b,t.compileGrayToABGR=$,t.compileToABGR=_,t.convolveChannel=q,t.convolveImage=(t,e)=>{const s=J(t,e),n=new X(s.dwidth,s.dheight,t.format);for(let i of e.channels||y(t.format.channels.length))n.setChannel(i,W(Object.assign(Object.assign({},s),{channel:i})));return n},t.defBayer=I,t.defFloatFormat=N,t.defKernel=Z,t.defLargeKernel=tt,t.defPackedFormat=j,t.ditherPixels=(t,e,s,n,i,r,a,h)=>{!t&&(t=e.slice()),a--;for(let l=0,o=0;l<n;l++)for(let n=0;n<s;n++)t[o]=H(i,r,a,h,n,l,e[o]),o++;return t},t.ensureChannel=u,t.ensureSize=p,t.floatBuffer=function(...t){return t[0]instanceof V?X.fromPacked(...t):new X(...t)},t.imageCanvas=f,t.imagePromise=async t=>{const e=new Image;return e.src=t,await e.decode(),e},t.luminanceABGR=d,t.normalMap=(t,e)=>{const{channel:s,step:n,scale:i,z:r}=Object.assign({channel:0,step:0,scale:1,z:1},e);u(t.format,s);const a=[-1,...new Array(n).fill(0),1],[h,l]=x(i),o=new X(t.width,t.height,ht);return o.setChannel(0,q(t,{kernel:{spec:a,size:[n+2,1]},scale:h,channel:s})),o.setChannel(1,q(t,{kernel:{spec:a,size:[1,n+2]},scale:l,channel:s})),o.setChannel(2,r),o},t.orderedDither=H,t.packedBuffer=T,t.prepRegions=A,t.range=y,t.setChannelConvert=w,t.setChannelSame=R,t.setChannelUni=g,t.transformABGR=L,Object.defineProperty(t,"__esModule",{value:!0})}));

package.json

 {
     "name": "@thi.ng/pixel",
-    "version": "0.6.1",
-    "description": "Typed array backed, integer and floating point pixel buffers w/ customizable formats, blitting, dithering, conversions",
+    "version": "0.7.1",
+    "description": "Typedarray integer & float pixel buffers w/ customizable formats, blitting, dithering, convolution",
     "module": "./index.js",
@@ -42,3 +42,3 @@ "main": "./lib/index.js",
         "@istanbuljs/nyc-config-typescript": "^1.0.1",
-        "@microsoft/api-extractor": "^7.12.1",
+        "@microsoft/api-extractor": "^7.13.1",
         "@types/mocha": "^8.2.0",
@@ -49,11 +49,11 @@ "@types/node": "^14.14.14",
         "ts-node": "^9.1.1",
-        "typedoc": "^0.20.26",
-        "typescript": "^4.1.5"
+        "typedoc": "^0.20.28",
+        "typescript": "^4.2.2"
     },
     "dependencies": {
-        "@thi.ng/api": "^7.0.0",
-        "@thi.ng/binary": "^2.1.0",
-        "@thi.ng/checks": "^2.9.0",
-        "@thi.ng/math": "^3.2.0",
-        "@thi.ng/porter-duff": "^0.1.38"
+        "@thi.ng/api": "^7.1.1",
+        "@thi.ng/binary": "^2.2.1",
+        "@thi.ng/checks": "^2.9.2",
+        "@thi.ng/math": "^3.2.2",
+        "@thi.ng/porter-duff": "^0.1.40"
     },
@@ -77,2 +77,3 @@ "files": [
         "blit",
+        "blur",
         "canvas",
@@ -82,2 +83,3 @@ "channel",
         "conversion",
+        "convolution",
         "datastructure",
@@ -87,2 +89,3 @@ "dither",
         "format",
+        "gaussian",
         "grayscale",
@@ -92,5 +95,7 @@ "image",
         "multiformat",
+        "normal",
         "pixel",
         "resize",
         "rgb565",
+        "sharpen",
         "typedarray",
@@ -109,3 +114,3 @@ "typescript"
     },
-    "gitHead": "2cb9a54255d6a5d7f21c9875002b86c42dd038de"
+    "gitHead": "a59cd470a1728cb5f40e96e010fb98ead30e3142"
 }

packed.d.ts

@@ -1,2 +0,2 @@
-import { Fn, UIntArray } from "@thi.ng/api";
+import { Fn, ICopy, IEmpty, UIntArray } from "@thi.ng/api";
 import { BayerMatrix, BayerSize, BlendFnInt, BlitOpts, IPixelBuffer, PackedFormat, PackedFormatSpec } from "./api";
@@ -11,10 +11,20 @@ /**
  */
-export declare const packedBuffer: (w: number, h: number, fmt: PackedFormat | PackedFormatSpec, pixels?: Uint8Array | Uint8ClampedArray | Uint16Array | Uint32Array | undefined) => PackedBuffer;
+export declare function packedBuffer(w: number, h: number, fmt: PackedFormat | PackedFormatSpec, pixels?: UIntArray): PackedBuffer;
+export declare function packedBuffer(src: PackedBuffer, fmt: PackedFormat | PackedFormatSpec): PackedBuffer;
 /**
  * @deprecated use {@link packedBuffer} instead.
  */
-export declare const buffer: (w: number, h: number, fmt: PackedFormat | PackedFormatSpec, pixels?: Uint8Array | Uint8ClampedArray | Uint16Array | Uint32Array | undefined) => PackedBuffer;
-export declare class PackedBuffer implements IPixelBuffer<UIntArray, number> {
-    static fromImage(img: HTMLImageElement, fmt: PackedFormat, width?: number, height?: number | undefined): PackedBuffer;
-    static fromCanvas(canvas: HTMLCanvasElement): PackedBuffer;
+export declare const buffer: typeof packedBuffer;
+export declare class PackedBuffer implements IPixelBuffer<UIntArray, number>, ICopy<PackedBuffer>, IEmpty<PackedBuffer> {
+    /**
+     * Creates a new pixel buffer from given HTML image element with optional
+     * support for format conversion (default: {@link ABGR8888} & resizing.
+     *
+     * @param img
+     * @param fmt
+     * @param width
+     * @param height
+     */
+    static fromImage(img: HTMLImageElement, fmt?: PackedFormat, width?: number, height?: number | undefined): PackedBuffer;
+    static fromCanvas(canvas: HTMLCanvasElement, fmt?: PackedFormat): PackedBuffer;
     readonly width: number;
@@ -28,2 +38,3 @@ readonly height: number;
     copy(): PackedBuffer;
+    empty(): PackedBuffer;
     getAt(x: number, y: number): number;
@@ -30,0 +41,0 @@ setAt(x: number, y: number, col: number): this;

packed.js

@@ -1,2 +0,2 @@
-import { typedArray, uintTypeForBits } from "@thi.ng/api";
+import { typedArray, uintTypeForBits, } from "@thi.ng/api";
 import { isNumber } from "@thi.ng/checks";
@@ -11,12 +11,9 @@ import { isPremultipliedInt, postmultiplyInt, premultiplyInt, } from "@thi.ng/porter-duff";
 import { clampRegion, ensureChannel, ensureSize, prepRegions, setChannelConvert, setChannelSame, setChannelUni, transformABGR, } from "./utils";
+export function packedBuffer(...args) {
+    return args[0] instanceof PackedBuffer
+        ? args[0].as(args[1])
+        : // @ts-ignore
+            new PackedBuffer(...args);
+}
 /**
- * Syntax sugar for {@link PackedBuffer} ctor.
- *
- * @param w -
- * @param h -
- * @param fmt -
- * @param pixels -
- */
-export const packedBuffer = (w, h, fmt, pixels) => new PackedBuffer(w, h, fmt, pixels);
-/**
  * @deprecated use {@link packedBuffer} instead.
@@ -34,17 +31,32 @@ */
     }
+    /**
+     * Creates a new pixel buffer from given HTML image element with optional
+     * support for format conversion (default: {@link ABGR8888} & resizing.
+     *
+     * @param img
+     * @param fmt
+     * @param width
+     * @param height
+     */
     static fromImage(img, fmt, width, height = width) {
-        const ctx = imageCanvas(img, width, height);
-        const w = ctx.canvas.width;
-        const h = ctx.canvas.height;
-        const src = new Uint32Array(ctx.ctx.getImageData(0, 0, w, h).data.buffer);
-        const dest = typedArray(fmt.type, w * h);
-        const from = fmt.fromABGR;
-        for (let i = dest.length; --i >= 0;) {
-            dest[i] = from(src[i]);
+        return PackedBuffer.fromCanvas(imageCanvas(img, width, height).canvas, fmt);
+    }
+    static fromCanvas(canvas, fmt = ABGR8888) {
+        const ctx = canvasPixels(canvas);
+        const w = canvas.width;
+        const h = canvas.height;
+        let dest;
+        if (fmt === ABGR8888) {
+            dest = ctx.pixels;
         }
+        else {
+            dest = typedArray(fmt.type, w * h);
+            const src = ctx.pixels;
+            const from = fmt.fromABGR;
+            for (let i = dest.length; --i >= 0;) {
+                dest[i] = from(src[i]);
+            }
+        }
         return new PackedBuffer(w, h, fmt, dest);
     }
-    static fromCanvas(canvas) {
-        return new PackedBuffer(canvas.width, canvas.height, ABGR8888, canvasPixels(canvas).pixels);
-    }
     get stride() {
@@ -57,6 +69,9 @@ return 1;
     copy() {
-        const dest = new PackedBuffer(this.width, this.height, this.format);
+        const dest = this.empty();
         dest.pixels.set(this.pixels);
         return dest;
     }
+    empty() {
+        return new PackedBuffer(this.width, this.height, this.format);
+    }
     getAt(x, y) {
@@ -63,0 +78,0 @@ return x >= 0 && x < this.width && y >= 0 && y < this.height

README.md

@@ -16,2 +16,4 @@ <!-- This file is generated - DO NOT EDIT! -->
   - [Floating point pixel formats](#floating-point-pixel-formats)
+  - [Strided convolution & pooling](#strided-convolution--pooling)
+  - [Normal map generation](#normal-map-generation)
   - [Status](#status)
@@ -29,3 +31,3 @@ - [Support packages](#support-packages)
 
-Typed array backed, integer and floating point pixel buffers w/ customizable formats, blitting, dithering, conversions.
+Typedarray integer & float pixel buffers w/ customizable formats, blitting, dithering, convolution.
 
@@ -43,6 +45,9 @@ ![screenshot](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/pixel-basics.png)
 - Single-channel manipulation / extraction / replacement / conversion
+- Convolution w/ arbitrary shaped/sized kernels, pooling, striding (resizing)
+- Convolution kernel & pooling kernels presets
+- Customizable normal map generation (i.e. X/Y gradients plus static Z component)
 - Inversion
-- XY pixel accessors
-- 10 packed integer and 4 floating point preset formats (see table
-  below)
+- Image downsampling (nearest neighbor, mean/min/max pooling)
+- XY full pixel & channel-only accessors
+- 12 packed integer and 6 floating point preset formats (see table below)
 - Ordered dithering w/ customizable Bayer matrix size and target color
@@ -108,10 +113,83 @@ steps (int formats only)
 | `FLOAT_GRAY_ALPHA` | 2             | Grayscale and alpha channel |
+| `FLOAT_NORMAL`     | 3             | Normal map (signed values)  |
 | `FLOAT_RGB`        | 3             | Red, Green, Blue            |
 | `FLOAT_RGBA`       | 4             | Red, Green, Blue, Alpha     |
 
-- All color channels are unclamped (but can be clamped via
-  `buf.clamp()`). For conversion to packed int formats assumed to
-  contain normalized data (i.e. [0..1] interval)
+- All color channels are unclamped (but can be clamped via `buf.clamp()`). For
+  conversion to packed int formats assumed to contain normalized data (i.e.
+  [0..1] interval, with exception of `FLOAT_NORMAL` which uses [-1..1] range)
 - Conversion between float formats is currently unsupported
 
+### Strided convolution & pooling
+
+Floating point buffers can be processed using arbitrary convolution kernels. The
+following convolution kernel presets are provided for convenience:
+
+| Kernel           | Size        |
+|------------------|-------------|
+| `BOX_BLUR3`      | 3x3         |
+| `BOX_BLUR5`      | 5x5         |
+| `GAUSSIAN_BLUR3` | 3x3         |
+| `GAUSSIAN_BLUR5` | 5x5         |
+| `GAUSSIAN(n)`    | 2n+1 x 2n+1 |
+| `HIGHPASS3`      | 3x3         |
+| `SHARPEN3`       | 3x3         |
+| `SOBEL_X`        | 3x3         |
+| `SOBEL_Y`        | 3x3         |
+| `UNSHARP_MASK5`  | 5x5         |
+
+Furthermore, convolution supports striding (i.e. only processing every nth pixel
+column/row) and pixel pooling (e.g. for ML applications). Available pooling
+kernel presets (kernel sizes are configured independently):
+
+| Kernel                 | Description        |
+|------------------------|--------------------|
+| `POOL_MEAN`            | Moving average     |
+| `POOL_MAX`             | Local maximum      |
+| `POOL_MIN`             | Local minimum      |
+| `POOL_NEAREST`         | Nearest neighbor   |
+| `POOL_THRESHOLD(bias)` | Adaptive threshold |
+
+Convolution can be applied to single, multiple or all channels of a
+`FloatBuffer`. See
+[`convolveChannel()`](https://docs.thi.ng/umbrella/pixel/modules.html#convolvechannel)
+and
+[`convolveImage()`](https://docs.thi.ng/umbrella/pixel/modules.html#convolveimage)
+
+TODO add image & code example
+
+### Normal map generation
+
+Normal maps can be created via `normalMap()`. This function uses an adjustable
+convolution kernel size to control gradient smoothness & details. Result X/Y
+gradients can also be scaled (uniform or anisotropic) and the Z component can be
+customized to (default: 1.0). The resulting image is in `FLOAT_NORMAL` format,
+using signed channel values. This channel format is auto-translating these into
+unsigned values when the image is converted into an integer format.
+
+| Step | Scale = 1                                                                                | Scale = 2                                                                                | Scale = 4                                                                                | Scale = 8                                                                                |
+|------|------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|
+| 0    | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-0-1.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-0-2.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-0-4.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-0-8.jpg) |
+| 1    | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-1-1.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-1-2.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-1-4.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-1-8.jpg) |
+| 2    | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-2-1.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-2-2.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-2-4.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-2-8.jpg) |
+| 3    | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-3-1.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-3-2.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-3-4.jpg) | ![](https://raw.githubusercontent.com/thi-ng/umbrella/develop/assets/pixel/nmap-3-8.jpg) |
+
+```ts
+import { floatBuffer, normalMap, FLOAT_GRAY, RGB888 } from "@thi.ng/pixel";
+import { asPPM, read } from "@thi.ng/pixel-io-netpbm";
+
+// read source image into a single channel floating point buffer
+const src = floatBuffer(read(readFileSync("noise.pgm")), FLOAT_GRAY);
+
+// create normal map (w/ default options)
+const nmap = normalMap(src, { step: 0, scale: 1 });
+
+// pixel lookup (vectors are stored _un_normalized)
+nmap.getAt(10, 10);
+// Float32Array(3) [ -0.019607841968536377, -0.04313725233078003, 1 ]
+
+// save as 24bit PBM, conversion to RGB int format first
+writeFileSync("noise-normal.ppm", asPPM(nmap.as(RGB888)));
+```
+
 ### Status
@@ -145,3 +223,3 @@
 
-Package sizes (gzipped, pre-treeshake): ESM: 5.35 KB / CJS: 5.57 KB / UMD: 5.52 KB
+Package sizes (gzipped, pre-treeshake): ESM: 7.18 KB / CJS: 7.45 KB / UMD: 7.29 KB
 
@@ -148,0 +226,0 @@ ## Dependencies

utils.d.ts

@@ -32,2 +32,8 @@ import { Fn, Fn2, FnN, TypedArray, UIntArray } from "@thi.ng/api";
 export declare const transformABGR: (pix: UIntArray, format: PackedFormat, fn: Fn<number, number>) => void;
+/** @internal */
+export declare const asVec: (x: number | [number, number]) => number[];
+/** @internal */
+export declare const asIntVec: (x: number | [number, number]) => number[];
+/** @internal */
+export declare const range: (n: number) => Uint8Array;
 //# sourceMappingURL=utils.d.ts.map

utils.js

 import { assert } from "@thi.ng/api";
+import { isNumber } from "@thi.ng/checks";
 import { clamp } from "@thi.ng/math";
@@ -60,1 +61,10 @@ /** @internal */
 };
+/** @internal */
+export const asVec = (x) => isNumber(x) ? [x, x] : x;
+/** @internal */
+export const asIntVec = (x) => {
+    const v = asVec(x);
+    return [v[0] | 0, v[1] | 0];
+};
+/** @internal */
+export const range = (n) => new Uint8Array(n).map((_, i) => i);

New alerts

Uses eval

Supply chain risk

Package uses dynamic code execution (e.g., eval()), which is a dangerous practice. This can prevent the code from running in certain environments and increases the risk that the code may contain exploits or malicious behavior.

Found 1 instance in 1 package

Fixed alerts

Uses eval

Supply chain risk

Package uses dynamic code execution (e.g., eval()), which is a dangerous practice. This can prevent the code from running in certain environments and increases the risk that the code may contain exploits or malicious behavior.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

309270

increased by28.21%

Number of package files

68

increased by9.68%

Lines of code

3673

increased by30.8%

Number of lines in readme file

333

increased by30.59%

Worsened metrics

Number of medium supply chain risk alerts

15

increased by25%

Dependency changes

• [e-mail]/api@^7.1.1

• [e-mail]/binary@^2.2.1

• [e-mail]/checks@^2.9.2

• [e-mail]/math@^3.2.2

• [e-mail]/porter-duff@^0.1.40