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Commit ae447fae by vincent
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check in latest build

parent 623ab304
Showing with 54 additions and 40 deletions
build/NetInput.js
...@@ -22,6 +22,14 @@ var NetInput = /** @class */ (function () { ...@@ -22,6 +22,14 @@ var NetInput = /** @class */ (function () {
// TODO: make sure not to dispose original tensors passed in by the user // TODO: make sure not to dispose original tensors passed in by the user
return tf.clone(input); return tf.clone(input);
} }
if (isTensor_1.isTensor4D(input)) {
var shape = input.shape;
var batchSize = shape[0];
if (batchSize !== 1) {
throw new Error("NetInput - tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array");
}
return input.reshape(shape.slice(1));
}
return tf.fromPixels(input instanceof HTMLCanvasElement ? input : utils_1.createCanvasFromMedia(input)); return tf.fromPixels(input instanceof HTMLCanvasElement ? input : utils_1.createCanvasFromMedia(input));
}); });
} }
......
build/NetInput.js.map
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\ No newline at end of file \ No newline at end of file
build/extractFaces.js
...@@ -31,6 +31,9 @@ function extractFaces(input, detections) { ...@@ -31,6 +31,9 @@ function extractFaces(input, detections) {
return [4 /*yield*/, utils_1.imageTensorToCanvas(netInput.inputs[0])]; return [4 /*yield*/, utils_1.imageTensorToCanvas(netInput.inputs[0])];
case 2: case 2:
canvas = _a.sent(); canvas = _a.sent();
if (netInput.isManaged) {
netInput.dispose();
}
_a.label = 3; _a.label = 3;
case 3: case 3:
ctx = utils_1.getContext2dOrThrow(canvas); ctx = utils_1.getContext2dOrThrow(canvas);
......
build/extractFaces.js.map
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\ No newline at end of file \ No newline at end of file
build/toNetInput.js
...@@ -37,26 +37,20 @@ function toNetInput(inputs, manageCreatedInput) { ...@@ -37,26 +37,20 @@ function toNetInput(inputs, manageCreatedInput) {
throw new Error('toNetInput - empty array passed as input'); throw new Error('toNetInput - empty array passed as input');
} }
getIdxHint = function (idx) { return Array.isArray(inputs) ? " at input index " + idx + ":" : ''; }; getIdxHint = function (idx) { return Array.isArray(inputs) ? " at input index " + idx + ":" : ''; };
inputArray = inputArgArray inputArray = inputArgArray.map(utils_1.resolveInput);
.map(utils_1.resolveInput) inputArray.forEach(function (input, i) {
.map(function (input, i) { if (!isMediaElement_1.isMediaElement(input) && !isTensor_1.isTensor3D(input) && !isTensor_1.isTensor4D(input)) {
if (typeof inputArgArray[i] === 'string') {
throw new Error("toNetInput -" + getIdxHint(i) + " string passed, but could not resolve HTMLElement for element id " + inputArgArray[i]);
}
throw new Error("toNetInput -" + getIdxHint(i) + " expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id");
}
if (isTensor_1.isTensor4D(input)) { if (isTensor_1.isTensor4D(input)) {
// if tf.Tensor4D is passed in the input array, the batch size has to be 1 // if tf.Tensor4D is passed in the input array, the batch size has to be 1
var batchSize = input.shape[0]; var batchSize = input.shape[0];
if (batchSize !== 1) { if (batchSize !== 1) {
throw new Error("toNetInput -" + getIdxHint(i) + " tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array"); throw new Error("toNetInput -" + getIdxHint(i) + " tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array");
} }
// to tf.Tensor3D
return input.reshape(input.shape.slice(1));
}
return input;
});
inputArray.forEach(function (input, i) {
if (!isMediaElement_1.isMediaElement(input) && !isTensor_1.isTensor3D(input)) {
if (typeof inputArgArray[i] === 'string') {
throw new Error("toNetInput -" + getIdxHint(i) + " string passed, but could not resolve HTMLElement for element id " + inputArgArray[i]);
}
throw new Error("toNetInput -" + getIdxHint(i) + " expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id");
} }
}); });
// wait for all media elements being loaded // wait for all media elements being loaded
......
build/toNetInput.js.map
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\ No newline at end of file \ No newline at end of file
build/utils.js
...@@ -106,15 +106,17 @@ function bufferToImage(buf) { ...@@ -106,15 +106,17 @@ function bufferToImage(buf) {
exports.bufferToImage = bufferToImage; exports.bufferToImage = bufferToImage;
function imageTensorToCanvas(imgTensor, canvas) { function imageTensorToCanvas(imgTensor, canvas) {
return tslib_1.__awaiter(this, void 0, void 0, function () { return tslib_1.__awaiter(this, void 0, void 0, function () {
var targetCanvas, _a, height, width, numChannels; var targetCanvas, _a, height, width, numChannels, imgTensor3D;
return tslib_1.__generator(this, function (_b) { return tslib_1.__generator(this, function (_b) {
switch (_b.label) { switch (_b.label) {
case 0: case 0:
targetCanvas = canvas || document.createElement('canvas'); targetCanvas = canvas || document.createElement('canvas');
_a = imgTensor.shape.slice(isTensor_1.isTensor4D(imgTensor) ? 1 : 0), height = _a[0], width = _a[1], numChannels = _a[2]; _a = imgTensor.shape.slice(isTensor_1.isTensor4D(imgTensor) ? 1 : 0), height = _a[0], width = _a[1], numChannels = _a[2];
return [4 /*yield*/, tf.toPixels(imgTensor.as3D(height, width, numChannels).toInt(), targetCanvas)]; imgTensor3D = tf.tidy(function () { return imgTensor.as3D(height, width, numChannels).toInt(); });
return [4 /*yield*/, tf.toPixels(imgTensor3D, targetCanvas)];
case 1: case 1:
_b.sent(); _b.sent();
imgTensor3D.dispose();
return [2 /*return*/, targetCanvas]; return [2 /*return*/, targetCanvas];
} }
}); });
......
build/utils.js.map
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\ No newline at end of file \ No newline at end of file
dist/face-api.js
...@@ -494,15 +494,17 @@ ...@@ -494,15 +494,17 @@
} }
function imageTensorToCanvas(imgTensor, canvas) { function imageTensorToCanvas(imgTensor, canvas) {
return __awaiter$1(this, void 0, void 0, function () { return __awaiter$1(this, void 0, void 0, function () {
var targetCanvas, _a, height, width, numChannels; var targetCanvas, _a, height, width, numChannels, imgTensor3D;
return __generator$1(this, function (_b) { return __generator$1(this, function (_b) {
switch (_b.label) { switch (_b.label) {
case 0: case 0:
targetCanvas = canvas || document.createElement('canvas'); targetCanvas = canvas || document.createElement('canvas');
_a = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0), height = _a[0], width = _a[1], numChannels = _a[2]; _a = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0), height = _a[0], width = _a[1], numChannels = _a[2];
return [4 /*yield*/, toPixels(imgTensor.as3D(height, width, numChannels).toInt(), targetCanvas)]; imgTensor3D = tidy(function () { return imgTensor.as3D(height, width, numChannels).toInt(); });
return [4 /*yield*/, toPixels(imgTensor3D, targetCanvas)];
case 1: case 1:
_b.sent(); _b.sent();
imgTensor3D.dispose();
return [2 /*return*/, targetCanvas]; return [2 /*return*/, targetCanvas];
} }
}); });
...@@ -526,6 +528,14 @@ ...@@ -526,6 +528,14 @@
// TODO: make sure not to dispose original tensors passed in by the user // TODO: make sure not to dispose original tensors passed in by the user
return clone(input); return clone(input);
} }
if (isTensor4D(input)) {
var shape = input.shape;
var batchSize = shape[0];
if (batchSize !== 1) {
throw new Error("NetInput - tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array");
}
return input.reshape(shape.slice(1));
}
return fromPixels(input instanceof HTMLCanvasElement ? input : createCanvasFromMedia(input)); return fromPixels(input instanceof HTMLCanvasElement ? input : createCanvasFromMedia(input));
}); });
} }
...@@ -815,26 +825,20 @@ ...@@ -815,26 +825,20 @@
throw new Error('toNetInput - empty array passed as input'); throw new Error('toNetInput - empty array passed as input');
} }
getIdxHint = function (idx) { return Array.isArray(inputs) ? " at input index " + idx + ":" : ''; }; getIdxHint = function (idx) { return Array.isArray(inputs) ? " at input index " + idx + ":" : ''; };
inputArray = inputArgArray inputArray = inputArgArray.map(resolveInput);
.map(resolveInput) inputArray.forEach(function (input, i) {
.map(function (input, i) { if (!isMediaElement(input) && !isTensor3D(input) && !isTensor4D(input)) {
if (typeof inputArgArray[i] === 'string') {
throw new Error("toNetInput -" + getIdxHint(i) + " string passed, but could not resolve HTMLElement for element id " + inputArgArray[i]);
}
throw new Error("toNetInput -" + getIdxHint(i) + " expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id");
}
if (isTensor4D(input)) { if (isTensor4D(input)) {
// if tf.Tensor4D is passed in the input array, the batch size has to be 1 // if tf.Tensor4D is passed in the input array, the batch size has to be 1
var batchSize = input.shape[0]; var batchSize = input.shape[0];
if (batchSize !== 1) { if (batchSize !== 1) {
throw new Error("toNetInput -" + getIdxHint(i) + " tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array"); throw new Error("toNetInput -" + getIdxHint(i) + " tf.Tensor4D with batchSize " + batchSize + " passed, but not supported in input array");
} }
// to tf.Tensor3D
return input.reshape(input.shape.slice(1));
}
return input;
});
inputArray.forEach(function (input, i) {
if (!isMediaElement(input) && !isTensor3D(input)) {
if (typeof inputArgArray[i] === 'string') {
throw new Error("toNetInput -" + getIdxHint(i) + " string passed, but could not resolve HTMLElement for element id " + inputArgArray[i]);
}
throw new Error("toNetInput -" + getIdxHint(i) + " expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id");
} }
}); });
// wait for all media elements being loaded // wait for all media elements being loaded
...@@ -875,6 +879,9 @@ ...@@ -875,6 +879,9 @@
return [4 /*yield*/, imageTensorToCanvas(netInput.inputs[0])]; return [4 /*yield*/, imageTensorToCanvas(netInput.inputs[0])];
case 2: case 2:
canvas = _a.sent(); canvas = _a.sent();
if (netInput.isManaged) {
netInput.dispose();
}
_a.label = 3; _a.label = 3;
case 3: case 3:
ctx = getContext2dOrThrow(canvas); ctx = getContext2dOrThrow(canvas);
......
dist/face-api.js.map
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dist/face-api.min.js
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