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human
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Code Issues Packages Projects Releases Wiki Activity

enhanced automated test coverage

pull/193/head
Vladimir Mandic 2021-09-20 09:42:34 -04:00
parent cadbadf52e
commit 66428abc12
24 changed files with 851 additions and 886 deletions
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3
CHANGELOG.md
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@ -9,8 +9,9 @@
## Changelog ## Changelog
### **HEAD -> main** 2021/09/18 mandic00@live.com ### **HEAD -> main** 2021/09/19 mandic00@live.com
- added configuration validation
- prevent validation failed on some model combinations - prevent validation failed on some model combinations
- webgl exception handling - webgl exception handling

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demo/facematch/faces.json
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39
dist/human.esm-nobundle.js vendored
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@ -4462,8 +4462,11 @@ function canvas(width, height) {
} }
function process2(input, config3) { function process2(input, config3) {
let tensor3; let tensor3;
if (!input) if (!input) {
throw new Error("input is missing"); if (config3.debug)
log("input is missing");
return { tensor: null, canvas: null };
}
if (!(input instanceof tfjs_esm_exports.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) { if (!(input instanceof tfjs_esm_exports.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) {
throw new Error("input type is not recognized"); throw new Error("input type is not recognized");
} }
@ -4474,13 +4477,15 @@ function process2(input, config3) {
throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`); throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`);
} else { } else {
if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) { if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
log("input stream is not ready"); if (config3.debug)
log("input stream is not ready");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0; const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0;
const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0; const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0;
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
log("cannot determine input dimensions"); if (config3.debug)
log("cannot determine input dimensions");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
let targetWidth = originalWidth; let targetWidth = originalWidth;
@ -10061,22 +10066,16 @@ async function predict11(input) {
tfjs_esm_exports.dispose(resizeOutput); tfjs_esm_exports.dispose(resizeOutput);
return data; return data;
} }
const overlay = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const overlay = canvas(width, height);
overlay.width = width;
overlay.height = height;
if (tfjs_esm_exports.browser) if (tfjs_esm_exports.browser)
await tfjs_esm_exports.browser.toPixels(resizeOutput, overlay); await tfjs_esm_exports.browser.toPixels(resizeOutput, overlay);
tfjs_esm_exports.dispose(resizeOutput); tfjs_esm_exports.dispose(resizeOutput);
const alphaCanvas = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const alphaCanvas = canvas(width, height);
alphaCanvas.width = width;
alphaCanvas.height = height;
const ctxAlpha = alphaCanvas.getContext("2d"); const ctxAlpha = alphaCanvas.getContext("2d");
ctxAlpha.filter = "blur(8px"; ctxAlpha.filter = "blur(8px";
await ctxAlpha.drawImage(overlay, 0, 0); await ctxAlpha.drawImage(overlay, 0, 0);
const alpha = ctxAlpha.getImageData(0, 0, width, height).data; const alpha = ctxAlpha.getImageData(0, 0, width, height).data;
const original = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const original = canvas(width, height);
original.width = width;
original.height = height;
const ctx = original.getContext("2d"); const ctx = original.getContext("2d");
if (input.canvas) if (input.canvas)
await ctx.drawImage(input.canvas, 0, 0); await ctx.drawImage(input.canvas, 0, 0);
@ -10096,17 +10095,20 @@ async function process5(input, background, config3) {
if (!model9) if (!model9)
await load12(config3); await load12(config3);
const img = process2(input, config3); const img = process2(input, config3);
const tmp = process2(background, config3);
if (!img.canvas || !tmp.canvas) {
if (config3.debug)
log("segmentation cannot process input or background");
return null;
}
const alpha = await predict11(img); const alpha = await predict11(img);
tfjs_esm_exports.dispose(img.tensor); tfjs_esm_exports.dispose(img.tensor);
if (background && alpha) { if (background && alpha) {
const tmp = process2(background, config3);
const bg = tmp.canvas; const bg = tmp.canvas;
tfjs_esm_exports.dispose(tmp.tensor); tfjs_esm_exports.dispose(tmp.tensor);
const fg = img.canvas; const fg = img.canvas;
const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data; const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data;
const c = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(fg.width, fg.height) : document.createElement("canvas"); const c = canvas(fg.width, fg.height);
c.width = fg.width;
c.height = fg.height;
const ctx = c.getContext("2d"); const ctx = c.getContext("2d");
ctx.globalCompositeOperation = "copy"; ctx.globalCompositeOperation = "copy";
ctx.drawImage(bg, 0, 0, c.width, c.height); ctx.drawImage(bg, 0, 0, c.width, c.height);
@ -12388,7 +12390,8 @@ var Human = class {
this.analyze("End Segmentation:"); this.analyze("End Segmentation:");
} }
if (!img.tensor) { if (!img.tensor) {
log("could not convert input to tensor"); if (this.config.debug)
log("could not convert input to tensor");
resolve({ error: "could not convert input to tensor" }); resolve({ error: "could not convert input to tensor" });
return; return;
} }

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dist/human.esm-nobundle.js.map vendored
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dist/human.esm.js vendored
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@ -64519,8 +64519,11 @@ function canvas(width, height) {
} }
function process2(input2, config3) { function process2(input2, config3) {
let tensor2; let tensor2;
if (!input2) if (!input2) {
throw new Error("input is missing"); if (config3.debug)
log("input is missing");
return { tensor: null, canvas: null };
}
if (!(input2 instanceof Tensor) && !(typeof Image !== "undefined" && input2 instanceof Image) && !(typeof env2.Canvas !== "undefined" && input2 instanceof env2.Canvas) && !(typeof ImageData !== "undefined" && input2 instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input2 instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input2 instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input2 instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input2 instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input2 instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input2 instanceof OffscreenCanvas)) { if (!(input2 instanceof Tensor) && !(typeof Image !== "undefined" && input2 instanceof Image) && !(typeof env2.Canvas !== "undefined" && input2 instanceof env2.Canvas) && !(typeof ImageData !== "undefined" && input2 instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input2 instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input2 instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input2 instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input2 instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input2 instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input2 instanceof OffscreenCanvas)) {
throw new Error("input type is not recognized"); throw new Error("input type is not recognized");
} }
@ -64531,13 +64534,15 @@ function process2(input2, config3) {
throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input2.shape}`); throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input2.shape}`);
} else { } else {
if (typeof input2["readyState"] !== "undefined" && input2["readyState"] <= 2) { if (typeof input2["readyState"] !== "undefined" && input2["readyState"] <= 2) {
log("input stream is not ready"); if (config3.debug)
log("input stream is not ready");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
const originalWidth = input2["naturalWidth"] || input2["videoWidth"] || input2["width"] || input2["shape"] && input2["shape"][1] > 0; const originalWidth = input2["naturalWidth"] || input2["videoWidth"] || input2["width"] || input2["shape"] && input2["shape"][1] > 0;
const originalHeight = input2["naturalHeight"] || input2["videoHeight"] || input2["height"] || input2["shape"] && input2["shape"][2] > 0; const originalHeight = input2["naturalHeight"] || input2["videoHeight"] || input2["height"] || input2["shape"] && input2["shape"][2] > 0;
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
log("cannot determine input dimensions"); if (config3.debug)
log("cannot determine input dimensions");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
let targetWidth = originalWidth; let targetWidth = originalWidth;
@ -70118,22 +70123,16 @@ async function predict11(input2) {
dispose(resizeOutput); dispose(resizeOutput);
return data; return data;
} }
const overlay = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const overlay = canvas(width, height);
overlay.width = width;
overlay.height = height;
if (browser_exports) if (browser_exports)
await browser_exports.toPixels(resizeOutput, overlay); await browser_exports.toPixels(resizeOutput, overlay);
dispose(resizeOutput); dispose(resizeOutput);
const alphaCanvas = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const alphaCanvas = canvas(width, height);
alphaCanvas.width = width;
alphaCanvas.height = height;
const ctxAlpha = alphaCanvas.getContext("2d"); const ctxAlpha = alphaCanvas.getContext("2d");
ctxAlpha.filter = "blur(8px"; ctxAlpha.filter = "blur(8px";
await ctxAlpha.drawImage(overlay, 0, 0); await ctxAlpha.drawImage(overlay, 0, 0);
const alpha = ctxAlpha.getImageData(0, 0, width, height).data; const alpha = ctxAlpha.getImageData(0, 0, width, height).data;
const original = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const original = canvas(width, height);
original.width = width;
original.height = height;
const ctx = original.getContext("2d"); const ctx = original.getContext("2d");
if (input2.canvas) if (input2.canvas)
await ctx.drawImage(input2.canvas, 0, 0); await ctx.drawImage(input2.canvas, 0, 0);
@ -70153,17 +70152,20 @@ async function process5(input2, background, config3) {
if (!model10) if (!model10)
await load12(config3); await load12(config3);
const img = process2(input2, config3); const img = process2(input2, config3);
const tmp = process2(background, config3);
if (!img.canvas || !tmp.canvas) {
if (config3.debug)
log("segmentation cannot process input or background");
return null;
}
const alpha = await predict11(img); const alpha = await predict11(img);
dispose(img.tensor); dispose(img.tensor);
if (background && alpha) { if (background && alpha) {
const tmp = process2(background, config3);
const bg = tmp.canvas; const bg = tmp.canvas;
dispose(tmp.tensor); dispose(tmp.tensor);
const fg = img.canvas; const fg = img.canvas;
const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data; const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data;
const c = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(fg.width, fg.height) : document.createElement("canvas"); const c = canvas(fg.width, fg.height);
c.width = fg.width;
c.height = fg.height;
const ctx = c.getContext("2d"); const ctx = c.getContext("2d");
ctx.globalCompositeOperation = "copy"; ctx.globalCompositeOperation = "copy";
ctx.drawImage(bg, 0, 0, c.width, c.height); ctx.drawImage(bg, 0, 0, c.width, c.height);
@ -72445,7 +72447,8 @@ var Human = class {
this.analyze("End Segmentation:"); this.analyze("End Segmentation:");
} }
if (!img.tensor) { if (!img.tensor) {
log("could not convert input to tensor"); if (this.config.debug)
log("could not convert input to tensor");
resolve({ error: "could not convert input to tensor" }); resolve({ error: "could not convert input to tensor" });
return; return;
} }

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dist/human.esm.js.map vendored
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dist/human.js vendored
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dist/human.node-gpu.js vendored
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@ -4496,8 +4496,11 @@ function canvas(width, height) {
} }
function process2(input, config3) { function process2(input, config3) {
let tensor3; let tensor3;
if (!input) if (!input) {
throw new Error("input is missing"); if (config3.debug)
log("input is missing");
return { tensor: null, canvas: null };
}
if (!(input instanceof tf3.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) { if (!(input instanceof tf3.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) {
throw new Error("input type is not recognized"); throw new Error("input type is not recognized");
} }
@ -4508,13 +4511,15 @@ function process2(input, config3) {
throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`); throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`);
} else { } else {
if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) { if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
log("input stream is not ready"); if (config3.debug)
log("input stream is not ready");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0; const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0;
const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0; const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0;
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
log("cannot determine input dimensions"); if (config3.debug)
log("cannot determine input dimensions");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
let targetWidth = originalWidth; let targetWidth = originalWidth;
@ -10120,22 +10125,16 @@ async function predict11(input) {
tf19.dispose(resizeOutput); tf19.dispose(resizeOutput);
return data; return data;
} }
const overlay = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const overlay = canvas(width, height);
overlay.width = width;
overlay.height = height;
if (tf19.browser) if (tf19.browser)
await tf19.browser.toPixels(resizeOutput, overlay); await tf19.browser.toPixels(resizeOutput, overlay);
tf19.dispose(resizeOutput); tf19.dispose(resizeOutput);
const alphaCanvas = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const alphaCanvas = canvas(width, height);
alphaCanvas.width = width;
alphaCanvas.height = height;
const ctxAlpha = alphaCanvas.getContext("2d"); const ctxAlpha = alphaCanvas.getContext("2d");
ctxAlpha.filter = "blur(8px"; ctxAlpha.filter = "blur(8px";
await ctxAlpha.drawImage(overlay, 0, 0); await ctxAlpha.drawImage(overlay, 0, 0);
const alpha = ctxAlpha.getImageData(0, 0, width, height).data; const alpha = ctxAlpha.getImageData(0, 0, width, height).data;
const original = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const original = canvas(width, height);
original.width = width;
original.height = height;
const ctx = original.getContext("2d"); const ctx = original.getContext("2d");
if (input.canvas) if (input.canvas)
await ctx.drawImage(input.canvas, 0, 0); await ctx.drawImage(input.canvas, 0, 0);
@ -10155,17 +10154,20 @@ async function process5(input, background, config3) {
if (!model9) if (!model9)
await load12(config3); await load12(config3);
const img = process2(input, config3); const img = process2(input, config3);
const tmp = process2(background, config3);
if (!img.canvas || !tmp.canvas) {
if (config3.debug)
log("segmentation cannot process input or background");
return null;
}
const alpha = await predict11(img); const alpha = await predict11(img);
tf19.dispose(img.tensor); tf19.dispose(img.tensor);
if (background && alpha) { if (background && alpha) {
const tmp = process2(background, config3);
const bg = tmp.canvas; const bg = tmp.canvas;
tf19.dispose(tmp.tensor); tf19.dispose(tmp.tensor);
const fg = img.canvas; const fg = img.canvas;
const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data; const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data;
const c = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(fg.width, fg.height) : document.createElement("canvas"); const c = canvas(fg.width, fg.height);
c.width = fg.width;
c.height = fg.height;
const ctx = c.getContext("2d"); const ctx = c.getContext("2d");
ctx.globalCompositeOperation = "copy"; ctx.globalCompositeOperation = "copy";
ctx.drawImage(bg, 0, 0, c.width, c.height); ctx.drawImage(bg, 0, 0, c.width, c.height);
@ -12451,7 +12453,8 @@ var Human = class {
this.analyze("End Segmentation:"); this.analyze("End Segmentation:");
} }
if (!img.tensor) { if (!img.tensor) {
log("could not convert input to tensor"); if (this.config.debug)
log("could not convert input to tensor");
resolve({ error: "could not convert input to tensor" }); resolve({ error: "could not convert input to tensor" });
return; return;
} }

39
dist/human.node-wasm.js vendored
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@ -4497,8 +4497,11 @@ function canvas(width, height) {
} }
function process2(input, config3) { function process2(input, config3) {
let tensor3; let tensor3;
if (!input) if (!input) {
throw new Error("input is missing"); if (config3.debug)
log("input is missing");
return { tensor: null, canvas: null };
}
if (!(input instanceof tf3.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) { if (!(input instanceof tf3.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) {
throw new Error("input type is not recognized"); throw new Error("input type is not recognized");
} }
@ -4509,13 +4512,15 @@ function process2(input, config3) {
throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`); throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`);
} else { } else {
if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) { if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
log("input stream is not ready"); if (config3.debug)
log("input stream is not ready");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0; const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0;
const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0; const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0;
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
log("cannot determine input dimensions"); if (config3.debug)
log("cannot determine input dimensions");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
let targetWidth = originalWidth; let targetWidth = originalWidth;
@ -10121,22 +10126,16 @@ async function predict11(input) {
tf19.dispose(resizeOutput); tf19.dispose(resizeOutput);
return data; return data;
} }
const overlay = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const overlay = canvas(width, height);
overlay.width = width;
overlay.height = height;
if (tf19.browser) if (tf19.browser)
await tf19.browser.toPixels(resizeOutput, overlay); await tf19.browser.toPixels(resizeOutput, overlay);
tf19.dispose(resizeOutput); tf19.dispose(resizeOutput);
const alphaCanvas = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const alphaCanvas = canvas(width, height);
alphaCanvas.width = width;
alphaCanvas.height = height;
const ctxAlpha = alphaCanvas.getContext("2d"); const ctxAlpha = alphaCanvas.getContext("2d");
ctxAlpha.filter = "blur(8px"; ctxAlpha.filter = "blur(8px";
await ctxAlpha.drawImage(overlay, 0, 0); await ctxAlpha.drawImage(overlay, 0, 0);
const alpha = ctxAlpha.getImageData(0, 0, width, height).data; const alpha = ctxAlpha.getImageData(0, 0, width, height).data;
const original = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const original = canvas(width, height);
original.width = width;
original.height = height;
const ctx = original.getContext("2d"); const ctx = original.getContext("2d");
if (input.canvas) if (input.canvas)
await ctx.drawImage(input.canvas, 0, 0); await ctx.drawImage(input.canvas, 0, 0);
@ -10156,17 +10155,20 @@ async function process5(input, background, config3) {
if (!model9) if (!model9)
await load12(config3); await load12(config3);
const img = process2(input, config3); const img = process2(input, config3);
const tmp = process2(background, config3);
if (!img.canvas || !tmp.canvas) {
if (config3.debug)
log("segmentation cannot process input or background");
return null;
}
const alpha = await predict11(img); const alpha = await predict11(img);
tf19.dispose(img.tensor); tf19.dispose(img.tensor);
if (background && alpha) { if (background && alpha) {
const tmp = process2(background, config3);
const bg = tmp.canvas; const bg = tmp.canvas;
tf19.dispose(tmp.tensor); tf19.dispose(tmp.tensor);
const fg = img.canvas; const fg = img.canvas;
const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data; const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data;
const c = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(fg.width, fg.height) : document.createElement("canvas"); const c = canvas(fg.width, fg.height);
c.width = fg.width;
c.height = fg.height;
const ctx = c.getContext("2d"); const ctx = c.getContext("2d");
ctx.globalCompositeOperation = "copy"; ctx.globalCompositeOperation = "copy";
ctx.drawImage(bg, 0, 0, c.width, c.height); ctx.drawImage(bg, 0, 0, c.width, c.height);
@ -12452,7 +12454,8 @@ var Human = class {
this.analyze("End Segmentation:"); this.analyze("End Segmentation:");
} }
if (!img.tensor) { if (!img.tensor) {
log("could not convert input to tensor"); if (this.config.debug)
log("could not convert input to tensor");
resolve({ error: "could not convert input to tensor" }); resolve({ error: "could not convert input to tensor" });
return; return;
} }

39
dist/human.node.js vendored
View File

@ -4496,8 +4496,11 @@ function canvas(width, height) {
} }
function process2(input, config3) { function process2(input, config3) {
let tensor3; let tensor3;
if (!input) if (!input) {
throw new Error("input is missing"); if (config3.debug)
log("input is missing");
return { tensor: null, canvas: null };
}
if (!(input instanceof tf3.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) { if (!(input instanceof tf3.Tensor) && !(typeof Image !== "undefined" && input instanceof Image) && !(typeof env.Canvas !== "undefined" && input instanceof env.Canvas) && !(typeof ImageData !== "undefined" && input instanceof ImageData) && !(typeof ImageBitmap !== "undefined" && input instanceof ImageBitmap) && !(typeof HTMLImageElement !== "undefined" && input instanceof HTMLImageElement) && !(typeof HTMLMediaElement !== "undefined" && input instanceof HTMLMediaElement) && !(typeof HTMLVideoElement !== "undefined" && input instanceof HTMLVideoElement) && !(typeof HTMLCanvasElement !== "undefined" && input instanceof HTMLCanvasElement) && !(typeof OffscreenCanvas !== "undefined" && input instanceof OffscreenCanvas)) {
throw new Error("input type is not recognized"); throw new Error("input type is not recognized");
} }
@ -4508,13 +4511,15 @@ function process2(input, config3) {
throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`); throw new Error(`input tensor shape must be [1, height, width, 3] and instead was ${input.shape}`);
} else { } else {
if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) { if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
log("input stream is not ready"); if (config3.debug)
log("input stream is not ready");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0; const originalWidth = input["naturalWidth"] || input["videoWidth"] || input["width"] || input["shape"] && input["shape"][1] > 0;
const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0; const originalHeight = input["naturalHeight"] || input["videoHeight"] || input["height"] || input["shape"] && input["shape"][2] > 0;
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
log("cannot determine input dimensions"); if (config3.debug)
log("cannot determine input dimensions");
return { tensor: null, canvas: inCanvas }; return { tensor: null, canvas: inCanvas };
} }
let targetWidth = originalWidth; let targetWidth = originalWidth;
@ -10120,22 +10125,16 @@ async function predict11(input) {
tf19.dispose(resizeOutput); tf19.dispose(resizeOutput);
return data; return data;
} }
const overlay = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const overlay = canvas(width, height);
overlay.width = width;
overlay.height = height;
if (tf19.browser) if (tf19.browser)
await tf19.browser.toPixels(resizeOutput, overlay); await tf19.browser.toPixels(resizeOutput, overlay);
tf19.dispose(resizeOutput); tf19.dispose(resizeOutput);
const alphaCanvas = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const alphaCanvas = canvas(width, height);
alphaCanvas.width = width;
alphaCanvas.height = height;
const ctxAlpha = alphaCanvas.getContext("2d"); const ctxAlpha = alphaCanvas.getContext("2d");
ctxAlpha.filter = "blur(8px"; ctxAlpha.filter = "blur(8px";
await ctxAlpha.drawImage(overlay, 0, 0); await ctxAlpha.drawImage(overlay, 0, 0);
const alpha = ctxAlpha.getImageData(0, 0, width, height).data; const alpha = ctxAlpha.getImageData(0, 0, width, height).data;
const original = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(width, height) : document.createElement("canvas"); const original = canvas(width, height);
original.width = width;
original.height = height;
const ctx = original.getContext("2d"); const ctx = original.getContext("2d");
if (input.canvas) if (input.canvas)
await ctx.drawImage(input.canvas, 0, 0); await ctx.drawImage(input.canvas, 0, 0);
@ -10155,17 +10154,20 @@ async function process5(input, background, config3) {
if (!model9) if (!model9)
await load12(config3); await load12(config3);
const img = process2(input, config3); const img = process2(input, config3);
const tmp = process2(background, config3);
if (!img.canvas || !tmp.canvas) {
if (config3.debug)
log("segmentation cannot process input or background");
return null;
}
const alpha = await predict11(img); const alpha = await predict11(img);
tf19.dispose(img.tensor); tf19.dispose(img.tensor);
if (background && alpha) { if (background && alpha) {
const tmp = process2(background, config3);
const bg = tmp.canvas; const bg = tmp.canvas;
tf19.dispose(tmp.tensor); tf19.dispose(tmp.tensor);
const fg = img.canvas; const fg = img.canvas;
const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data; const fgData = (_a = fg.getContext("2d")) == null ? void 0 : _a.getImageData(0, 0, fg.width, fg.height).data;
const c = typeof OffscreenCanvas !== "undefined" ? new OffscreenCanvas(fg.width, fg.height) : document.createElement("canvas"); const c = canvas(fg.width, fg.height);
c.width = fg.width;
c.height = fg.height;
const ctx = c.getContext("2d"); const ctx = c.getContext("2d");
ctx.globalCompositeOperation = "copy"; ctx.globalCompositeOperation = "copy";
ctx.drawImage(bg, 0, 0, c.width, c.height); ctx.drawImage(bg, 0, 0, c.width, c.height);
@ -12451,7 +12453,8 @@ var Human = class {
this.analyze("End Segmentation:"); this.analyze("End Segmentation:");
} }
if (!img.tensor) { if (!img.tensor) {
log("could not convert input to tensor"); if (this.config.debug)
log("could not convert input to tensor");
resolve({ error: "could not convert input to tensor" }); resolve({ error: "could not convert input to tensor" });
return; return;
} }

2
package.json
View File

@ -66,7 +66,7 @@
"@tensorflow/tfjs-layers": "^3.9.0", "@tensorflow/tfjs-layers": "^3.9.0",
"@tensorflow/tfjs-node": "^3.9.0", "@tensorflow/tfjs-node": "^3.9.0",
"@tensorflow/tfjs-node-gpu": "^3.9.0", "@tensorflow/tfjs-node-gpu": "^3.9.0",
"@types/node": "^16.9.3", "@types/node": "^16.9.4",
"@typescript-eslint/eslint-plugin": "^4.31.1", "@typescript-eslint/eslint-plugin": "^4.31.1",
"@typescript-eslint/parser": "^4.31.1", "@typescript-eslint/parser": "^4.31.1",
"@vladmandic/build": "^0.5.2", "@vladmandic/build": "^0.5.2",

2
src/human.ts
View File

@ -442,7 +442,7 @@ export class Human {
} }
if (!img.tensor) { if (!img.tensor) {
log('could not convert input to tensor'); if (this.config.debug) log('could not convert input to tensor');
resolve({ error: 'could not convert input to tensor' }); resolve({ error: 'could not convert input to tensor' });
return; return;
} }

12
src/image/image.ts
View File

@ -39,9 +39,13 @@ export function canvas(width, height): HTMLCanvasElement | OffscreenCanvas {
// process input image and return tensor // process input image and return tensor
// input can be tensor, imagedata, htmlimageelement, htmlvideoelement // input can be tensor, imagedata, htmlimageelement, htmlvideoelement
// input is resized and run through imagefx filter // input is resized and run through imagefx filter
export function process(input: Input, config: Config): { tensor: Tensor | null, canvas: OffscreenCanvas | HTMLCanvasElement } { export function process(input: Input, config: Config): { tensor: Tensor | null, canvas: OffscreenCanvas | HTMLCanvasElement | null } {
let tensor; let tensor;
if (!input) throw new Error('input is missing'); if (!input) {
// throw new Error('input is missing');
if (config.debug) log('input is missing');
return { tensor: null, canvas: null }; // video may become temporarily unavailable due to onresize
}
// sanity checks since different browsers do not implement all dom elements // sanity checks since different browsers do not implement all dom elements
if ( if (
!(input instanceof tf.Tensor) !(input instanceof tf.Tensor)
@ -64,13 +68,13 @@ export function process(input: Input, config: Config): { tensor: Tensor | null,
} else { } else {
// check if resizing will be needed // check if resizing will be needed
if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) { if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) {
log('input stream is not ready'); if (config.debug) log('input stream is not ready');
return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize
} }
const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0)); const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));
const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0)); const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
log('cannot determine input dimensions'); if (config.debug) log('cannot determine input dimensions');
return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize
} }
let targetWidth = originalWidth; let targetWidth = originalWidth;

26
src/segmentation/segmentation.ts
View File

@ -67,25 +67,19 @@ export async function predict(input: { tensor: Tensor | null, canvas: OffscreenC
return data; // we're running in nodejs so return alpha array as-is return data; // we're running in nodejs so return alpha array as-is
} }
const overlay = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(width, height) : document.createElement('canvas'); const overlay = image.canvas(width, height);
overlay.width = width;
overlay.height = height;
if (tf.browser) await tf.browser.toPixels(resizeOutput, overlay); if (tf.browser) await tf.browser.toPixels(resizeOutput, overlay);
tf.dispose(resizeOutput); tf.dispose(resizeOutput);
// get alpha channel data // get alpha channel data
const alphaCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(width, height) : document.createElement('canvas'); // need one more copy since input may already have gl context so 2d context fails const alphaCanvas = image.canvas(width, height);
alphaCanvas.width = width;
alphaCanvas.height = height;
const ctxAlpha = alphaCanvas.getContext('2d') as CanvasRenderingContext2D; const ctxAlpha = alphaCanvas.getContext('2d') as CanvasRenderingContext2D;
ctxAlpha.filter = 'blur(8px'; ctxAlpha.filter = 'blur(8px';
await ctxAlpha.drawImage(overlay, 0, 0); await ctxAlpha.drawImage(overlay, 0, 0);
const alpha = ctxAlpha.getImageData(0, 0, width, height).data; const alpha = ctxAlpha.getImageData(0, 0, width, height).data;
// get original canvas merged with overlay // get original canvas merged with overlay
const original = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(width, height) : document.createElement('canvas'); // need one more copy since input may already have gl context so 2d context fails const original = image.canvas(width, height);
original.width = width;
original.height = height;
const ctx = original.getContext('2d') as CanvasRenderingContext2D; const ctx = original.getContext('2d') as CanvasRenderingContext2D;
if (input.canvas) await ctx.drawImage(input.canvas, 0, 0); if (input.canvas) await ctx.drawImage(input.canvas, 0, 0);
// https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/globalCompositeOperation // best options are: darken, color-burn, multiply // https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/globalCompositeOperation // best options are: darken, color-burn, multiply
@ -105,19 +99,21 @@ export async function process(input: Input, background: Input | undefined, confi
busy = true; busy = true;
if (!model) await load(config); if (!model) await load(config);
const img = image.process(input, config); const img = image.process(input, config);
const tmp = image.process(background, config);
if (!img.canvas || !tmp.canvas) {
if (config.debug) log('segmentation cannot process input or background');
return null;
}
const alpha = await predict(img); const alpha = await predict(img);
tf.dispose(img.tensor); tf.dispose(img.tensor);
if (background && alpha) { if (background && alpha) {
const tmp = image.process(background, config); const bg = tmp.canvas as HTMLCanvasElement;
const bg = tmp.canvas;
tf.dispose(tmp.tensor); tf.dispose(tmp.tensor);
const fg = img.canvas; const fg = img.canvas as HTMLCanvasElement;
const fgData = fg.getContext('2d')?.getImageData(0, 0, fg.width, fg.height).data as Uint8ClampedArray; const fgData = fg.getContext('2d')?.getImageData(0, 0, fg.width, fg.height).data as Uint8ClampedArray;
const c = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(fg.width, fg.height) : document.createElement('canvas'); const c = image.canvas(fg.width, fg.height);
c.width = fg.width;
c.height = fg.height;
const ctx = c.getContext('2d') as CanvasRenderingContext2D; const ctx = c.getContext('2d') as CanvasRenderingContext2D;
ctx.globalCompositeOperation = 'copy'; // reset ctx.globalCompositeOperation = 'copy'; // reset

92
test/build.log
View File

@ -1,68 +1,24 @@
2021-09-19 13:55:00 INFO:  @vladmandic/human version 2.2.2 2021-09-20 09:41:09 INFO:  @vladmandic/human version 2.2.2
2021-09-19 13:55:00 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0 2021-09-20 09:41:09 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
2021-09-19 13:55:00 INFO:  Application: {"name":"@vladmandic/human","version":"2.2.2"} 2021-09-20 09:41:09 INFO:  Application: {"name":"@vladmandic/human","version":"2.2.2"}
2021-09-19 13:55:00 INFO:  Environment: {"profile":"production","config":"build.json","tsconfig":true,"eslintrc":true,"git":true} 2021-09-20 09:41:09 INFO:  Environment: {"profile":"production","config":"build.json","tsconfig":true,"eslintrc":true,"git":true}
2021-09-19 13:55:00 INFO:  Toolchain: {"build":"0.5.2","esbuild":"0.12.28","typescript":"4.4.3","typedoc":"0.22.4","eslint":"7.32.0"} 2021-09-20 09:41:09 INFO:  Toolchain: {"build":"0.5.2","esbuild":"0.12.28","typescript":"4.4.3","typedoc":"0.22.4","eslint":"7.32.0"}
2021-09-19 13:55:00 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 2021-09-20 09:41:09 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2021-09-19 13:55:00 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]} 2021-09-20 09:41:09 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]}
2021-09-19 13:55:00 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1416} 2021-09-20 09:41:09 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1416}
2021-09-19 13:55:01 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":50,"inputBytes":481770,"outputBytes":408805} 2021-09-20 09:41:09 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":50,"inputBytes":481478,"outputBytes":408546}
2021-09-19 13:55:01 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1424} 2021-09-20 09:41:09 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1424}
2021-09-19 13:55:01 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":50,"inputBytes":481778,"outputBytes":408809} 2021-09-20 09:41:09 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":50,"inputBytes":481486,"outputBytes":408550}
2021-09-19 13:55:01 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1491} 2021-09-20 09:41:09 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1491}
2021-09-19 13:55:01 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":50,"inputBytes":481845,"outputBytes":408881} 2021-09-20 09:41:09 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":50,"inputBytes":481553,"outputBytes":408622}
2021-09-19 13:55:01 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1631} 2021-09-20 09:41:09 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1631}
2021-09-19 13:55:01 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":3088,"outputBytes":793} 2021-09-20 09:41:09 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":3088,"outputBytes":793}
2021-09-19 13:55:01 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":50,"inputBytes":481147,"outputBytes":410098} 2021-09-20 09:41:09 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":50,"inputBytes":480855,"outputBytes":409839}
2021-09-19 13:55:01 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":3088,"outputBytes":2376809} 2021-09-20 09:41:10 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":3088,"outputBytes":2376809}
2021-09-19 13:55:01 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":50,"inputBytes":2857163,"outputBytes":1409412} 2021-09-20 09:41:10 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":50,"inputBytes":2856871,"outputBytes":1409130}
2021-09-19 13:55:02 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":50,"inputBytes":2857163,"outputBytes":2614017} 2021-09-20 09:41:11 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":50,"inputBytes":2856871,"outputBytes":2613758}
2021-09-19 13:55:18 STATE: Typings: {"input":"src/human.ts","output":"types","files":94} 2021-09-20 09:41:27 STATE: Typings: {"input":"src/human.ts","output":"types","files":94}
2021-09-19 13:55:23 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":29,"generated":true} 2021-09-20 09:41:32 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":29,"generated":true}
2021-09-19 13:55:51 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":83,"errors":0,"warnings":0} 2021-09-20 09:41:58 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":83,"errors":0,"warnings":0}
2021-09-19 13:55:52 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 2021-09-20 09:41:58 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2021-09-19 13:55:52 INFO:  Done... 2021-09-20 09:41:58 INFO:  Done...
2021-09-19 14:14:35 INFO:  @vladmandic/human version 2.2.2
2021-09-19 14:14:35 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
2021-09-19 14:14:35 INFO:  Application: {"name":"@vladmandic/human","version":"2.2.2"}
2021-09-19 14:14:35 INFO:  Environment: {"profile":"development","config":"build.json","tsconfig":true,"eslintrc":true,"git":true}
2021-09-19 14:14:35 INFO:  Toolchain: {"build":"0.5.2","esbuild":"0.12.28","typescript":"4.4.3","typedoc":"0.22.4","eslint":"7.32.0"}
2021-09-19 14:14:35 INFO:  Build: {"profile":"development","steps":["serve","watch","compile"]}
2021-09-19 14:14:35 STATE: WebServer: {"ssl":false,"port":10030,"root":"."}
2021-09-19 14:14:35 STATE: WebServer: {"ssl":true,"port":10031,"root":".","sslKey":"node_modules/@vladmandic/build/cert/https.key","sslCrt":"node_modules/@vladmandic/build/cert/https.crt"}
2021-09-19 14:14:35 STATE: Watch: {"locations":["src/**","README.md","src/**/*","tfjs/**/*"]}
2021-09-19 14:14:35 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1416}
2021-09-19 14:14:35 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":50,"inputBytes":481782,"outputBytes":408817}
2021-09-19 14:14:35 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1424}
2021-09-19 14:14:35 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":50,"inputBytes":481790,"outputBytes":408821}
2021-09-19 14:14:35 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1491}
2021-09-19 14:14:35 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":50,"inputBytes":481857,"outputBytes":408893}
2021-09-19 14:14:35 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1631}
2021-09-19 14:14:35 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":3088,"outputBytes":793}
2021-09-19 14:14:35 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":50,"inputBytes":481159,"outputBytes":410110}
2021-09-19 14:14:36 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":3088,"outputBytes":2376809}
2021-09-19 14:14:36 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":50,"inputBytes":2857175,"outputBytes":1409415}
2021-09-19 14:14:37 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":50,"inputBytes":2857175,"outputBytes":2614029}
2021-09-19 14:14:37 INFO:  Listening...
2021-09-19 14:15:02 INFO:  @vladmandic/human version 2.2.2
2021-09-19 14:15:02 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
2021-09-19 14:15:02 INFO:  Application: {"name":"@vladmandic/human","version":"2.2.2"}
2021-09-19 14:15:02 INFO:  Environment: {"profile":"development","config":"build.json","tsconfig":true,"eslintrc":true,"git":true}
2021-09-19 14:15:02 INFO:  Toolchain: {"build":"0.5.2","esbuild":"0.12.28","typescript":"4.4.3","typedoc":"0.22.4","eslint":"7.32.0"}
2021-09-19 14:15:02 INFO:  Build: {"profile":"development","steps":["serve","watch","compile"]}
2021-09-19 14:15:02 STATE: WebServer: {"ssl":false,"port":10030,"root":"."}
2021-09-19 14:15:02 STATE: WebServer: {"ssl":true,"port":10031,"root":".","sslKey":"node_modules/@vladmandic/build/cert/https.key","sslCrt":"node_modules/@vladmandic/build/cert/https.crt"}
2021-09-19 14:15:02 STATE: Watch: {"locations":["src/**","README.md","src/**/*","tfjs/**/*"]}
2021-09-19 14:15:02 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1416}
2021-09-19 14:15:02 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":50,"inputBytes":481794,"outputBytes":408829}
2021-09-19 14:15:02 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1424}
2021-09-19 14:15:02 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":50,"inputBytes":481802,"outputBytes":408833}
2021-09-19 14:15:02 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1491}
2021-09-19 14:15:02 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":50,"inputBytes":481869,"outputBytes":408905}
2021-09-19 14:15:02 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1631}
2021-09-19 14:15:02 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":3088,"outputBytes":793}
2021-09-19 14:15:02 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":50,"inputBytes":481171,"outputBytes":410122}
2021-09-19 14:15:02 STATE: Compile: {"name":"tfjs/browser/esm/bundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":8,"inputBytes":3088,"outputBytes":2376809}
2021-09-19 14:15:03 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":50,"inputBytes":2857187,"outputBytes":1409418}
2021-09-19 14:15:03 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":50,"inputBytes":2857187,"outputBytes":2614041}
2021-09-19 14:15:03 INFO:  Listening...

75
test/test-main.js
View File

@ -1,3 +1,4 @@
const fs = require('fs');
const process = require('process'); const process = require('process');
const canvasJS = require('canvas'); const canvasJS = require('canvas');
@ -165,6 +166,13 @@ async function test(Human, inputConfig) {
else log('error', 'failed: configuration default validation', invalid); else log('error', 'failed: configuration default validation', invalid);
delete config.invalid; delete config.invalid;
// test model loading
await human.load();
const models = Object.keys(human.models).map((model) => ({ name: model, loaded: (human.models[model] !== null) }));
const loaded = models.filter((model) => model.loaded);
if (models.length === 14 && loaded.length === 7) log('state', 'passed: models loaded', models.length, loaded.length);
else log('error', 'failed: models loaded', models.length, loaded.length);
// test warmup sequences // test warmup sequences
await testInstance(human); await testInstance(human);
config.warmup = 'none'; config.warmup = 'none';
@ -175,28 +183,73 @@ async function test(Human, inputConfig) {
res = await testWarmup(human, 'default'); res = await testWarmup(human, 'default');
if (!res || res?.face?.length !== 1 || res?.body?.length !== 1 || res?.hand?.length !== 0 || res?.gesture?.length !== 3) log('error', 'failed: warmup face result mismatch', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length); if (!res || res?.face?.length !== 1 || res?.body?.length !== 1 || res?.hand?.length !== 0 || res?.gesture?.length !== 3) log('error', 'failed: warmup face result mismatch', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length);
else log('state', 'passed: warmup face result match'); else log('state', 'passed: warmup face result match');
config.warmup = 'body'; config.warmup = 'body';
res = await testWarmup(human, 'default'); res = await testWarmup(human, 'default');
if (!res || res?.face?.length !== 1 || res?.body?.length !== 1 || res?.hand?.length !== 0 || res?.gesture?.length !== 3) log('error', 'failed: warmup body result mismatch', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length); if (!res || res?.face?.length !== 1 || res?.body?.length !== 1 || res?.hand?.length !== 0 || res?.gesture?.length !== 3) log('error', 'failed: warmup body result mismatch', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length);
else log('state', 'passed: warmup body result match'); else log('state', 'passed: warmup body result match');
// test default config // test default config async
log('info', 'test default'); log('info', 'test default');
human.reset(); human.reset();
config.async = true;
config.cacheSensitivity = 0; config.cacheSensitivity = 0;
res = await testDetect(human, 'samples/ai-body.jpg', 'default'); res = await testDetect(human, 'samples/ai-body.jpg', 'default');
if (!res || res?.face?.length !== 1 || res?.face[0].gender !== 'female') log('error', 'failed: default result face mismatch', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length); if (!res || res?.face?.length !== 1 || res?.face[0].gender !== 'female') log('error', 'failed: default result face mismatch', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length);
else log('state', 'passed: default result face match'); else log('state', 'passed: default result face match');
// test default config // test default config sync
log('info', 'test sync'); log('info', 'test sync');
human.reset(); human.reset();
config.async = false; config.async = false;
config.cacheSensitivity = 0;
res = await testDetect(human, 'samples/ai-body.jpg', 'default'); res = await testDetect(human, 'samples/ai-body.jpg', 'default');
if (!res || res?.face?.length !== 1 || res?.face[0].gender !== 'female') log('error', 'failed: default sync', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length); if (!res || res?.face?.length !== 1 || res?.face[0].gender !== 'female') log('error', 'failed: default sync', res?.face?.length, res?.body?.length, res?.hand?.length, res?.gesture?.length);
else log('state', 'passed: default sync'); else log('state', 'passed: default sync');
// test image processing
const img1 = await human.image(null);
const img2 = await human.image(await getImage(human, 'samples/ai-face.jpg'));
if (!img1 || !img2 || img1.tensor !== null || img2.tensor?.shape?.length !== 4) log('error', 'failed: image input', img1?.tensor?.shape, img2?.tensor?.shape);
else log('state', 'passed: image input', img1?.tensor?.shape, img2?.tensor?.shape);
// test null input
res = await human.detect(null);
if (!res || !res.error) log('error', 'failed: invalid input', res);
else log('state', 'passed: invalid input', res);
// test face similarity
log('info', 'test face similarity');
human.reset();
config.async = false;
config.cacheSensitivity = 0;
let res1 = await testDetect(human, 'samples/ai-face.jpg', 'default');
let res2 = await testDetect(human, 'samples/ai-body.jpg', 'default');
let res3 = await testDetect(human, 'samples/ai-upper.jpg', 'default');
const desc1 = res1 && res1.face && res1.face[0] && res1.face[0].embedding ? [...res1.face[0].embedding] : null;
const desc2 = res2 && res2.face && res2.face[0] && res2.face[0].embedding ? [...res2.face[0].embedding] : null;
const desc3 = res3 && res3.face && res3.face[0] && res3.face[0].embedding ? [...res3.face[0].embedding] : null;
if (!desc1 || !desc2 || !desc3 || desc1.length !== 1024 || desc2.length !== 1024 || desc3.length !== 1024) log('error', 'failed: face descriptor', desc1?.length, desc2?.length, desc3?.length);
else log('state', 'passed: face descriptor');
res1 = Math.round(100 * human.similarity(desc1, desc2));
res2 = Math.round(100 * human.similarity(desc1, desc3));
res3 = Math.round(100 * human.similarity(desc2, desc3));
if (res1 !== 51 || res2 !== 49 || res3 !== 53) log('error', 'failed: face match ', res1, res2, res3);
else log('state', 'passed: face match');
// test face matching
log('info', 'test face matching');
let db = [];
try {
db = JSON.parse(fs.readFileSync('demo/facematch/faces.json').toString());
} catch { /***/ }
if (db.length < 100) log('error', 'failed: face database ', db.length);
else log('state', 'passed: face database', db.length);
res1 = human.match(desc1, db);
res2 = human.match(desc2, db);
res3 = human.match(desc3, db);
if (!res1 || !res1['name'] || !res2 || !res2['name'] || !res3 || !res3['name']) log('error', 'failed: face match ', res1);
else log('state', 'passed: face match', { first: { name: res1.name, similarity: res1.similarity } }, { second: { name: res2.name, similarity: res2.similarity } }, { third: { name: res3.name, similarity: res3.similarity } });
// test object detection // test object detection
log('info', 'test object'); log('info', 'test object');
human.reset(); human.reset();
@ -273,6 +326,22 @@ async function test(Human, inputConfig) {
testDetect(second, 'samples/ai-upper.jpg', 'default'), testDetect(second, 'samples/ai-upper.jpg', 'default'),
]); ]);
// test monkey-patch
human.env.Canvas = canvasJS.Canvas; // monkey-patch human to use external canvas library
const inputImage = await canvasJS.loadImage('samples/ai-face.jpg'); // load image using canvas library
const inputCanvas = new canvasJS.Canvas(inputImage.width, inputImage.height); // create canvas
const ctx = inputCanvas.getContext('2d');
ctx.drawImage(inputImage, 0, 0); // draw input image onto canvas
res = await human.detect(inputCanvas);
if (!res || res?.face?.length !== 1) log('error', 'failed: monkey patch');
else log('state', 'passed: monkey patch');
// test segmentation
res = await human.segmentation(inputCanvas, inputCanvas);
if (!res || !res.width || !res.height) log('error', 'failed: segmentation', res);
else log('state', 'passed: segmentation', [res.width, res.height]);
human.env.Canvas = undefined;
// tests end // tests end
const t1 = process.hrtime.bigint(); const t1 = process.hrtime.bigint();

2
test/test-node-wasm.js
View File

@ -27,7 +27,7 @@ const config = {
}, },
hand: { enabled: true, rotation: false }, hand: { enabled: true, rotation: false },
body: { enabled: true }, body: { enabled: true },
object: { enabled: false }, object: { enabled: true },
segmentation: { enabled: true }, segmentation: { enabled: true },
filter: { enabled: false }, filter: { enabled: false },
}; };

5
test/test.js
View File

@ -60,6 +60,7 @@ function logStdIO(ok, test, buffer) {
} }
} }
// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
async function runTest(test) { async function runTest(test) {
log.info(); log.info();
log.info(test, 'start'); log.info(test, 'start');
@ -73,6 +74,7 @@ async function runTest(test) {
}); });
} }
// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
async function runDemo(demo) { async function runDemo(demo) {
log.info(); log.info();
log.info(demo, 'start'); log.info(demo, 'start');
@ -94,7 +96,8 @@ async function testAll() {
process.on('unhandledRejection', (data) => log.error('nodejs unhandled rejection', data)); process.on('unhandledRejection', (data) => log.error('nodejs unhandled rejection', data));
process.on('uncaughtException', (data) => log.error('nodejs unhandled exception', data)); process.on('uncaughtException', (data) => log.error('nodejs unhandled exception', data));
log.info('tests:', tests); log.info('tests:', tests);
for (const demo of demos) await runDemo(demo); log.info('demos:', demos);
// for (const demo of demos) await runDemo(demo);
for (const test of tests) await runTest(test); for (const test of tests) await runTest(test);
log.info(); log.info();
log.info('status:', status); log.info('status:', status);

1173
test/test.log
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4
typedoc/classes/Human.html
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@ -74,9 +74,9 @@
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="enhance" class="tsd-anchor"></a><h3>enhance</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">enhance<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L298">human.ts:298</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead"> </div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="enhance" class="tsd-anchor"></a><h3>enhance</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">enhance<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L298">human.ts:298</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Enhance method performs additional enhacements to face image previously detected for futher processing</p> <p>Enhance method performs additional enhacements to face image previously detected for futher processing</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h4><div><p>Tensor</p> </div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h4><div><p>Tensor</p>
</div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="image" class="tsd-anchor"></a><h3>image</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">image<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L265">human.ts:265</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead"> </div></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="image" class="tsd-anchor"></a><h3>image</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">image<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L265">human.ts:265</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Process input as return canvas and tensor</p> <p>Process input as return canvas and tensor</p>
</div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></h4><div></div><ul class="tsd-parameters"><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span></h5></li><li class="tsd-parameter"><h5>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="init" class="tsd-anchor"></a><h3>init</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">init<span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">void</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L321">human.ts:321</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead"> </div></div><h4 class="tsd-parameters-title">Parameters</h4><ul class="tsd-parameters"><li><h5>input: <a href="../index.html#Input" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li></ul><h4 class="tsd-returns-title">Returns <span class="tsd-signature-symbol">{ </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol">; </span>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol"> }</span></h4><div></div><ul class="tsd-parameters"><li class="tsd-parameter"><h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">OffscreenCanvas</span></h5></li><li class="tsd-parameter"><h5>tensor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">null</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">Tensor</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Rank</span><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></li></ul></section><section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a name="init" class="tsd-anchor"></a><h3>init</h3><ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class"><li class="tsd-signature tsd-kind-icon">init<span class="tsd-signature-symbol">(</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">void</span></li></ul><ul class="tsd-descriptions"><li class="tsd-description"><aside class="tsd-sources"><ul><li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L321">human.ts:321</a></li></ul></aside><div class="tsd-comment tsd-typography"><div class="lead">
<p>Explicit backend initialization</p> <p>Explicit backend initialization</p>
<ul> <ul>
<li>Normally done implicitly during initial load phase</li> <li>Normally done implicitly during initial load phase</li>

2
types/src/human.d.ts vendored
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@ -156,7 +156,7 @@ export declare class Human {
*/ */
image: (input: Input) => { image: (input: Input) => {
tensor: Tensor<import("@tensorflow/tfjs-core").Rank> | null; tensor: Tensor<import("@tensorflow/tfjs-core").Rank> | null;
canvas: OffscreenCanvas | HTMLCanvasElement; canvas: OffscreenCanvas | HTMLCanvasElement | null;
}; };
/** Simmilarity method calculates simmilarity between two provided face descriptors (face embeddings) /** Simmilarity method calculates simmilarity between two provided face descriptors (face embeddings)
* - Calculation is based on normalized Minkowski distance between two descriptors * - Calculation is based on normalized Minkowski distance between two descriptors

2
types/src/image/image.d.ts vendored
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@ -8,7 +8,7 @@ declare type Input = Tensor | ImageData | ImageBitmap | HTMLImageElement | HTMLM
export declare function canvas(width: any, height: any): HTMLCanvasElement | OffscreenCanvas; export declare function canvas(width: any, height: any): HTMLCanvasElement | OffscreenCanvas;
export declare function process(input: Input, config: Config): { export declare function process(input: Input, config: Config): {
tensor: Tensor | null; tensor: Tensor | null;
canvas: OffscreenCanvas | HTMLCanvasElement; canvas: OffscreenCanvas | HTMLCanvasElement | null;
}; };
export declare function skip(config: any, input: Tensor): Promise<boolean>; export declare function skip(config: any, input: Tensor): Promise<boolean>;
export {}; export {};

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types/src/image/image.d.ts.map
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2
types/src/segmentation/segmentation.d.ts.map
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@ -1 +1 @@
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