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Commit 22301079 by vincent
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make padToSquare padding order append first when size is uneven + fixed issue…

make padToSquare padding order append first when size is uneven + fixed issue when dimensions differ by 1 only
parent d68e8485
Showing with 113 additions and 29 deletions
build/padToSquare.js
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("@tensorflow/tfjs-core");
var utils_1 = require("./utils");
/**
* Pads the smaller dimension of an image tensor with zeros, such that width === height.
*
......@@ -17,16 +16,24 @@ function padToSquare(imgTensor, isCenterImage) {
return imgTensor;
}
var dimDiff = Math.abs(height - width);
var paddingAmount = Math.floor(dimDiff * (isCenterImage ? 0.5 : 1));
var paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1));
var paddingAxis = height > width ? 2 : 1;
var getPaddingTensorShape = function (isRoundUp) {
if (isRoundUp === void 0) { isRoundUp = false; }
var createPaddingTensor = function (paddingAmount) {
var paddingTensorShape = imgTensor.shape.slice();
paddingTensorShape[paddingAxis] = paddingAmount + (isRoundUp ? 1 : 0);
return paddingTensorShape;
paddingTensorShape[paddingAxis] = paddingAmount;
return tf.fill(paddingTensorShape, 0);
};
var tensorsToStack = (isCenterImage ? [tf.fill(getPaddingTensorShape(!utils_1.isEven(dimDiff)), 0)] : [])
.concat([imgTensor, tf.fill(getPaddingTensorShape(), 0)]);
var paddingTensorAppend = createPaddingTensor(paddingAmount);
var remainingPaddingAmount = dimDiff - paddingTensorAppend.shape[paddingAxis];
var paddingTensorPrepend = isCenterImage && remainingPaddingAmount
? createPaddingTensor(remainingPaddingAmount)
: null;
var tensorsToStack = [
paddingTensorPrepend,
imgTensor,
paddingTensorAppend
]
.filter(function (t) { return t !== null; });
return tf.concat(tensorsToStack, paddingAxis);
});
}
......
build/padToSquare.js.map
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\ No newline at end of file
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\ No newline at end of file
dist/face-api.js
......@@ -785,16 +785,24 @@
return imgTensor;
}
var dimDiff = Math.abs(height - width);
var paddingAmount = Math.floor(dimDiff * (isCenterImage ? 0.5 : 1));
var paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1));
var paddingAxis = height > width ? 2 : 1;
var getPaddingTensorShape = function (isRoundUp) {
if (isRoundUp === void 0) { isRoundUp = false; }
var createPaddingTensor = function (paddingAmount) {
var paddingTensorShape = imgTensor.shape.slice();
paddingTensorShape[paddingAxis] = paddingAmount + (isRoundUp ? 1 : 0);
return paddingTensorShape;
paddingTensorShape[paddingAxis] = paddingAmount;
return fill(paddingTensorShape, 0);
};
var tensorsToStack = (isCenterImage ? [fill(getPaddingTensorShape(!isEven(dimDiff)), 0)] : [])
.concat([imgTensor, fill(getPaddingTensorShape(), 0)]);
var paddingTensorAppend = createPaddingTensor(paddingAmount);
var remainingPaddingAmount = dimDiff - paddingTensorAppend.shape[paddingAxis];
var paddingTensorPrepend = isCenterImage && remainingPaddingAmount
? createPaddingTensor(remainingPaddingAmount)
: null;
var tensorsToStack = [
paddingTensorPrepend,
imgTensor,
paddingTensorAppend
]
.filter(function (t) { return t !== null; });
return concat(tensorsToStack, paddingAxis);
});
}
......
dist/face-api.js.map
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dist/face-api.min.js
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src/padToSquare.ts
......@@ -21,17 +21,28 @@ export function padToSquare(
}
const dimDiff = Math.abs(height - width)
const paddingAmount = Math.floor(dimDiff * (isCenterImage ? 0.5 : 1))
const paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1))
const paddingAxis = height > width ? 2 : 1
const getPaddingTensorShape = (isRoundUp: boolean = false): number[] => {
const createPaddingTensor = (paddingAmount: number): tf.Tensor => {
const paddingTensorShape = imgTensor.shape.slice()
paddingTensorShape[paddingAxis] = paddingAmount + (isRoundUp ? 1 : 0)
return paddingTensorShape
paddingTensorShape[paddingAxis] = paddingAmount
return tf.fill(paddingTensorShape, 0)
}
const tensorsToStack = (isCenterImage ? [tf.fill(getPaddingTensorShape(!isEven(dimDiff)), 0)] : [])
.concat([imgTensor, tf.fill(getPaddingTensorShape(), 0)]) as tf.Tensor4D[]
const paddingTensorAppend = createPaddingTensor(paddingAmount)
const remainingPaddingAmount = dimDiff - paddingTensorAppend.shape[paddingAxis]
const paddingTensorPrepend = isCenterImage && remainingPaddingAmount
? createPaddingTensor(remainingPaddingAmount)
: null
const tensorsToStack = [
paddingTensorPrepend,
imgTensor,
paddingTensorAppend
]
.filter(t => t !== null) as tf.Tensor4D[]
return tf.concat(tensorsToStack, paddingAxis)
})
}
\ No newline at end of file
test/tests/padToSquare.test.ts
......@@ -7,7 +7,7 @@ describe('padToSquare', () => {
describe('even size', () => {
it('is padded to square', () => tf.tidy(() => {
it('is padded to square by 2 columns', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(24).fill(1), [1, 4, 2, 3])
const result = padToSquare(imgTensor)
......@@ -21,7 +21,7 @@ describe('padToSquare', () => {
expect(paddedCols[3].dataSync()).toEqual(zeros(12))
}))
it('is padded to square and centered', () => tf.tidy(() => {
it('is padded to square by 2 columns and centered', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(24).fill(1), [1, 4, 2, 3])
const result = padToSquare(imgTensor, true)
......@@ -35,11 +35,39 @@ describe('padToSquare', () => {
expect(paddedCols[3].dataSync()).toEqual(zeros(12))
}))
it('is padded to square by 1 column', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(36).fill(1), [1, 4, 3, 3])
const result = padToSquare(imgTensor)
expect(result.shape).toEqual([1, 4, 4, 3])
const paddedCols = tf.unstack(result, 2)
expect(paddedCols.length).toEqual(4)
expect(paddedCols[0].dataSync()).toEqual(ones(12))
expect(paddedCols[1].dataSync()).toEqual(ones(12))
expect(paddedCols[2].dataSync()).toEqual(ones(12))
expect(paddedCols[3].dataSync()).toEqual(zeros(12))
}))
it('is padded to square by 1 column and centered', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(36).fill(1), [1, 4, 3, 3])
const result = padToSquare(imgTensor, true)
expect(result.shape).toEqual([1, 4, 4, 3])
const paddedCols = tf.unstack(result, 2)
expect(paddedCols.length).toEqual(4)
expect(paddedCols[0].dataSync()).toEqual(ones(12))
expect(paddedCols[1].dataSync()).toEqual(ones(12))
expect(paddedCols[2].dataSync()).toEqual(ones(12))
expect(paddedCols[3].dataSync()).toEqual(zeros(12))
}))
})
describe('uneven size', () => {
it('is padded to square', () => tf.tidy(() => {
it('is padded to square by 3 columns', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(30).fill(1), [1, 5, 2, 3])
const result = padToSquare(imgTensor)
......@@ -54,17 +82,46 @@ describe('padToSquare', () => {
expect(paddedCols[4].dataSync()).toEqual(zeros(15))
}))
it('is padded to square and centered', () => tf.tidy(() => {
it('is padded to square by 3 columns and centered', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(30).fill(1), [1, 5, 2, 3])
const result = padToSquare(imgTensor, true)
expect(result.shape).toEqual([1, 5, 5, 3])
const data = result.dataSync()
const paddedCols = tf.unstack(result, 2)
expect(paddedCols.length).toEqual(5)
expect(paddedCols[0].dataSync()).toEqual(zeros(15))
expect(paddedCols[1].dataSync()).toEqual(zeros(15))
expect(paddedCols[1].dataSync()).toEqual(ones(15))
expect(paddedCols[2].dataSync()).toEqual(ones(15))
expect(paddedCols[3].dataSync()).toEqual(zeros(15))
expect(paddedCols[4].dataSync()).toEqual(zeros(15))
}))
it('is padded to square by 1 column', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(60).fill(1), [1, 5, 4, 3])
const result = padToSquare(imgTensor)
expect(result.shape).toEqual([1, 5, 5, 3])
const paddedCols = tf.unstack(result, 2)
expect(paddedCols.length).toEqual(5)
expect(paddedCols[0].dataSync()).toEqual(ones(15))
expect(paddedCols[1].dataSync()).toEqual(ones(15))
expect(paddedCols[2].dataSync()).toEqual(ones(15))
expect(paddedCols[3].dataSync()).toEqual(ones(15))
expect(paddedCols[4].dataSync()).toEqual(zeros(15))
}))
it('is padded to square by 1 column and centered', () => tf.tidy(() => {
const imgTensor = tf.tensor4d(Array(60).fill(1), [1, 5, 4, 3])
const result = padToSquare(imgTensor, true)
expect(result.shape).toEqual([1, 5, 5, 3])
const paddedCols = tf.unstack(result, 2)
expect(paddedCols.length).toEqual(5)
expect(paddedCols[0].dataSync()).toEqual(ones(15))
expect(paddedCols[1].dataSync()).toEqual(ones(15))
expect(paddedCols[2].dataSync()).toEqual(ones(15))
expect(paddedCols[3].dataSync()).toEqual(ones(15))
expect(paddedCols[4].dataSync()).toEqual(zeros(15))
......
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