gx

chenyc

2025-02-12 ea42ff3ebee1eeb3fb29423aa848a249441db81c

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
/**
 * @license
 * Copyright 2021 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
import * as tf from '../../index';
import { ALL_ENVS, describeWithFlags } from '../../jasmine_util';
import { expectArraysClose } from '../../test_util';
describeWithFlags('grayscaleToRGB', ALL_ENVS, () => {
    it('should convert (1,1,3,1) images into (1,1,3,3)', async () => {
        const grayscale = tf.tensor4d([1.0, 2.0, 3.0], [1, 1, 3, 1]);
        const rgb = tf.image.grayscaleToRGB(grayscale);
        const rgbData = await rgb.data();
        const expected = [1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0];
        expect(rgb.shape).toEqual([1, 1, 3, 3]);
        expectArraysClose(rgbData, expected);
    });
    it('should convert (1,2,1) images into (1,2,3)', async () => {
        const grayscale = tf.tensor3d([1.6, 2.4], [1, 2, 1]);
        const rgb = tf.image.grayscaleToRGB(grayscale);
        const rgbData = await rgb.data();
        const expected = [1.6, 1.6, 1.6, 2.4, 2.4, 2.4];
        expect(rgb.shape).toEqual([1, 2, 3]);
        expectArraysClose(rgbData, expected);
    });
    it('should convert (2,1) images into (2,3)', async () => {
        const grayscale = tf.tensor2d([16, 24], [2, 1]);
        const rgb = tf.image.grayscaleToRGB(grayscale);
        const rgbData = await rgb.data();
        const expected = [16, 16, 16, 24, 24, 24];
        expect(rgb.shape).toEqual([2, 3]);
        expectArraysClose(rgbData, expected);
    });
    it('should convert [[[191], [3]]] array into (1,2,3) images', async () => {
        const grayscale = [[[191], [3]]];
        const rgb = tf.image.grayscaleToRGB(grayscale);
        const rgbData = await rgb.data();
        const expected = [191, 191, 191, 3, 3, 3];
        expect(rgb.shape).toEqual([1, 2, 3]);
        expectArraysClose(rgbData, expected);
    });
    it('should throw an error because of input last dim is not 1', () => {
        const grayscale = tf.tensor4d([1.0, 1.0, 2.0, 2.0, 3.0, 3.0], [1, 1, 3, 2]);
        expect(() => tf.image.grayscaleToRGB(grayscale))
            .toThrowError(/last dimension of a grayscale image should be size 1/);
    });
    it('should throw an error because of image\'s rank is less than 2', () => {
        const grayscale = tf.tensor1d([1, 2, 3]);
        expect(() => tf.image.grayscaleToRGB(grayscale))
            .toThrowError(/images must be at least rank 2/);
    });
});
//# sourceMappingURL=data:application/json;base64,{"version":3,"file":"grayscale_to_rgb_test.js","sourceRoot":"","sources":["../../../../../../../tfjs-core/src/ops/image/grayscale_to_rgb_test.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,KAAK,EAAE,MAAM,aAAa,CAAC;AAClC,OAAO,EAAC,QAAQ,EAAE,iBAAiB,EAAC,MAAM,oBAAoB,CAAC;AAE/D,OAAO,EAAC,iBAAiB,EAAC,MAAM,iBAAiB,CAAC;AAElD,iBAAiB,CAAC,gBAAgB,EAAE,QAAQ,EAAE,GAAG,EAAE;IACjD,EAAE,CAAC,gDAAgD,EAAE,KAAK,IAAI,EAAE;QAC9D,MAAM,SAAS,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,GAAG,EAAE,GAAG,EAAE,GAAG,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAE7D,MAAM,GAAG,GAAG,EAAE,CAAC,KAAK,CAAC,cAAc,CAAC,SAAS,CAAC,CAAC;QAC/C,MAAM,OAAO,GAAG,MAAM,GAAG,CAAC,IAAI,EAAE,CAAC;QAEjC,MAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,CAAC,CAAC;QAE/D,MAAM,CAAC,GAAG,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACxC,iBAAiB,CAAC,OAAO,EAAE,QAAQ,CAAC,CAAC;IACvC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,4CAA4C,EAAE,KAAK,IAAI,EAAE;QAC1D,MAAM,SAAS,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,GAAG,EAAE,GAAG,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAErD,MAAM,GAAG,GAAG,EAAE,CAAC,KAAK,CAAC,cAAc,CAAC,SAAS,CAAC,CAAC;QAC/C,MAAM,OAAO,GAAG,MAAM,GAAG,CAAC,IAAI,EAAE,CAAC;QAEjC,MAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,CAAC,CAAC;QAEhD,MAAM,CAAC,GAAG,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACrC,iBAAiB,CAAC,OAAO,EAAE,QAAQ,CAAC,CAAC;IACvC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,wCAAwC,EAAE,KAAK,IAAI,EAAE;QACtD,MAAM,SAAS,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,EAAE,EAAE,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAEhD,MAAM,GAAG,GAAG,EAAE,CAAC,KAAK,CAAC,cAAc,CAAC,SAAS,CAAC,CAAC;QAC/C,MAAM,OAAO,GAAG,MAAM,GAAG,CAAC,IAAI,EAAE,CAAC;QAEjC,MAAM,QAAQ,GAAG,CAAC,EAAE,EAAE,EAAE,EAAE,EAAE,EAAE,EAAE,EAAE,EAAE,EAAE,EAAE,CAAC,CAAC;QAE1C,MAAM,CAAC,GAAG,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAClC,iBAAiB,CAAC,OAAO,EAAE,QAAQ,CAAC,CAAC;IACvC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,yDAAyD,EAAE,KAAK,IAAI,EAAE;QACvE,MAAM,SAAS,GAAG,CAAC,CAAC,CAAC,GAAG,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;QAEjC,MAAM,GAAG,GAAG,EAAE,CAAC,KAAK,CAAC,cAAc,CAAC,SAAS,CAAC,CAAC;QAC/C,MAAM,OAAO,GAAG,MAAM,GAAG,CAAC,IAAI,EAAE,CAAC;QAEjC,MAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC;QAE1C,MAAM,CAAC,GAAG,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACrC,iBAAiB,CAAC,OAAO,EAAE,QAAQ,CAAC,CAAC;IACvC,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,0DAA0D,EAAE,GAAG,EAAE;QAClE,MAAM,SAAS,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,EAAE,GAAG,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAE5E,MAAM,CAAC,GAAG,EAAE,CAAC,EAAE,CAAC,KAAK,CAAC,cAAc,CAAC,SAAS,CAAC,CAAC;aAC3C,YAAY,CAAC,sDAAsD,CAAC,CAAC;IAC5E,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,+DAA+D,EAAE,GAAG,EAAE;QACvE,MAAM,SAAS,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAwB,CAAC;QAEhE,MAAM,CAAC,GAAG,EAAE,CAAC,EAAE,CAAC,KAAK,CAAC,cAAc,CAAC,SAAS,CAAC,CAAC;aAC3C,YAAY,CAAC,gCAAgC,CAAC,CAAC;IACtD,CAAC,CAAC,CAAC;AACL,CAAC,CAAC,CAAC","sourcesContent":["/**\n * @license\n * Copyright 2021 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport * as tf from '../../index';\nimport {ALL_ENVS, describeWithFlags} from '../../jasmine_util';\nimport {Tensor2D} from '../../tensor';\nimport {expectArraysClose} from '../../test_util';\n\ndescribeWithFlags('grayscaleToRGB', ALL_ENVS, () => {\n  it('should convert (1,1,3,1) images into (1,1,3,3)', async () => {\n    const grayscale = tf.tensor4d([1.0, 2.0, 3.0], [1, 1, 3, 1]);\n\n    const rgb = tf.image.grayscaleToRGB(grayscale);\n    const rgbData = await rgb.data();\n\n    const expected = [1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0];\n\n    expect(rgb.shape).toEqual([1, 1, 3, 3]);\n    expectArraysClose(rgbData, expected);\n  });\n\n  it('should convert (1,2,1) images into (1,2,3)', async () => {\n    const grayscale = tf.tensor3d([1.6, 2.4], [1, 2, 1]);\n\n    const rgb = tf.image.grayscaleToRGB(grayscale);\n    const rgbData = await rgb.data();\n\n    const expected = [1.6, 1.6, 1.6, 2.4, 2.4, 2.4];\n\n    expect(rgb.shape).toEqual([1, 2, 3]);\n    expectArraysClose(rgbData, expected);\n  });\n\n  it('should convert (2,1) images into (2,3)', async () => {\n    const grayscale = tf.tensor2d([16, 24], [2, 1]);\n\n    const rgb = tf.image.grayscaleToRGB(grayscale);\n    const rgbData = await rgb.data();\n\n    const expected = [16, 16, 16, 24, 24, 24];\n\n    expect(rgb.shape).toEqual([2, 3]);\n    expectArraysClose(rgbData, expected);\n  });\n\n  it('should convert [[[191], [3]]] array into (1,2,3) images', async () => {\n    const grayscale = [[[191], [3]]];\n\n    const rgb = tf.image.grayscaleToRGB(grayscale);\n    const rgbData = await rgb.data();\n\n    const expected = [191, 191, 191, 3, 3, 3];\n\n    expect(rgb.shape).toEqual([1, 2, 3]);\n    expectArraysClose(rgbData, expected);\n  });\n\n  it('should throw an error because of input last dim is not 1', () => {\n    const grayscale = tf.tensor4d([1.0, 1.0, 2.0, 2.0, 3.0, 3.0], [1, 1, 3, 2]);\n\n    expect(() => tf.image.grayscaleToRGB(grayscale))\n        .toThrowError(/last dimension of a grayscale image should be size 1/);\n  });\n\n  it('should throw an error because of image\\'s rank is less than 2', () => {\n    const grayscale = tf.tensor1d([1, 2, 3]) as unknown as Tensor2D;\n\n    expect(() => tf.image.grayscaleToRGB(grayscale))\n        .toThrowError(/images must be at least rank 2/);\n  });\n});\n"]}