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Open Source Computer Vision Library
https://opencv.org/
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408 lines
13 KiB
408 lines
13 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html. |
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QUnit.module('Core', {}); |
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QUnit.test('test_operations_on_arrays', function(assert) { |
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// Transpose |
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{ |
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let mat1 = cv.Mat.eye(9, 7, cv.CV_8UC3); |
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let mat2 = new cv.Mat(); |
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cv.transpose(mat1, mat2); |
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// Verify result. |
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let size = mat2.size(); |
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assert.equal(mat2.channels(), 3); |
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assert.equal(size.height, 7); |
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assert.equal(size.width, 9); |
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} |
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// Concat |
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{ |
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let mat = cv.Mat.ones({height: 10, width: 5}, cv.CV_8UC3); |
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let mat2 = cv.Mat.eye({height: 10, width: 5}, cv.CV_8UC3); |
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let mat3 = cv.Mat.eye({height: 10, width: 5}, cv.CV_8UC3); |
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let out = new cv.Mat(); |
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let input = new cv.MatVector(); |
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input.push_back(mat); |
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input.push_back(mat2); |
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input.push_back(mat3); |
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cv.vconcat(input, out); |
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// Verify result. |
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let size = out.size(); |
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assert.equal(out.channels(), 3); |
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assert.equal(size.height, 30); |
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assert.equal(size.width, 5); |
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assert.equal(out.elemSize1(), 1); |
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cv.hconcat(input, out); |
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// Verify result. |
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size = out.size(); |
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assert.equal(out.channels(), 3); |
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assert.equal(size.height, 10); |
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assert.equal(size.width, 15); |
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assert.equal(out.elemSize1(), 1); |
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input.delete(); |
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out.delete(); |
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} |
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// Min, Max |
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{ |
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let data1 = new Uint8Array([1, 2, 3, 4, 5, 6, 7, 8, 9]); |
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let data2 = new Uint8Array([0, 4, 0, 8, 0, 12, 0, 16, 0]); |
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let expectedMin = new Uint8Array([0, 2, 0, 4, 0, 6, 0, 8, 0]); |
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let expectedMax = new Uint8Array([1, 4, 3, 8, 5, 12, 7, 16, 9]); |
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let dataPtr = cv._malloc(3*3*1); |
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let dataPtr2 = cv._malloc(3*3*1); |
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let dataHeap = new Uint8Array(cv.HEAPU8.buffer, dataPtr, 3*3*1); |
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dataHeap.set(new Uint8Array(data1.buffer)); |
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let dataHeap2 = new Uint8Array(cv.HEAPU8.buffer, dataPtr2, 3*3*1); |
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dataHeap2.set(new Uint8Array(data2.buffer)); |
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let mat1 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr, 0); |
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let mat2 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr2, 0); |
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let mat3 = new cv.Mat(); |
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cv.min(mat1, mat2, mat3); |
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// Verify result. |
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let size = mat2.size(); |
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assert.equal(mat2.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(mat3.data, expectedMin); |
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cv.max(mat1, mat2, mat3); |
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// Verify result. |
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size = mat2.size(); |
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assert.equal(mat2.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(mat3.data, expectedMax); |
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cv._free(dataPtr); |
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cv._free(dataPtr2); |
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} |
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// Bitwise operations |
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{ |
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let data1 = new Uint8Array([0, 1, 2, 4, 8, 16, 32, 64, 128]); |
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let data2 = new Uint8Array([255, 255, 255, 255, 255, 255, 255, 255, 255]); |
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let expectedAnd = new Uint8Array([0, 1, 2, 4, 8, 16, 32, 64, 128]); |
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let expectedOr = new Uint8Array([255, 255, 255, 255, 255, 255, 255, 255, 255]); |
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let expectedXor = new Uint8Array([255, 254, 253, 251, 247, 239, 223, 191, 127]); |
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let expectedNot = new Uint8Array([255, 254, 253, 251, 247, 239, 223, 191, 127]); |
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let dataPtr = cv._malloc(3*3*1); |
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let dataPtr2 = cv._malloc(3*3*1); |
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let dataHeap = new Uint8Array(cv.HEAPU8.buffer, dataPtr, 3*3*1); |
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dataHeap.set(new Uint8Array(data1.buffer)); |
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let dataHeap2 = new Uint8Array(cv.HEAPU8.buffer, dataPtr2, 3*3*1); |
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dataHeap2.set(new Uint8Array(data2.buffer)); |
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let mat1 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr, 0); |
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let mat2 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr2, 0); |
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let mat3 = new cv.Mat(); |
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let none = new cv.Mat(); |
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cv.bitwise_not(mat1, mat3, none); |
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// Verify result. |
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let size = mat3.size(); |
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assert.equal(mat3.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(mat3.data, expectedNot); |
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cv.bitwise_and(mat1, mat2, mat3, none); |
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// Verify result. |
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size = mat3.size(); |
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assert.equal(mat3.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(mat3.data, expectedAnd); |
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cv.bitwise_or(mat1, mat2, mat3, none); |
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// Verify result. |
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size = mat3.size(); |
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assert.equal(mat3.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(mat3.data, expectedOr); |
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cv.bitwise_xor(mat1, mat2, mat3, none); |
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// Verify result. |
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size = mat3.size(); |
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assert.equal(mat3.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(mat3.data, expectedXor); |
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cv._free(dataPtr); |
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cv._free(dataPtr2); |
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} |
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// Arithmetic operations |
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{ |
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let data1 = new Uint8Array([0, 1, 2, 3, 4, 5, 6, 7, 8]); |
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let data2 = new Uint8Array([0, 2, 4, 6, 8, 10, 12, 14, 16]); |
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let data3 = new Uint8Array([0, 1, 0, 1, 0, 1, 0, 1, 0]); |
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// |data1 - data2| |
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let expectedAbsDiff = new Uint8Array([0, 1, 2, 3, 4, 5, 6, 7, 8]); |
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let expectedAdd = new Uint8Array([0, 3, 6, 9, 12, 15, 18, 21, 24]); |
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const alpha = 4; |
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const beta = -1; |
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const gamma = 3; |
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// 4*data1 - data2 + 3 |
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let expectedWeightedAdd = new Uint8Array([3, 5, 7, 9, 11, 13, 15, 17, 19]); |
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let dataPtr = cv._malloc(3*3*1); |
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let dataPtr2 = cv._malloc(3*3*1); |
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let dataPtr3 = cv._malloc(3*3*1); |
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let dataHeap = new Uint8Array(cv.HEAPU8.buffer, dataPtr, 3*3*1); |
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dataHeap.set(new Uint8Array(data1.buffer)); |
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let dataHeap2 = new Uint8Array(cv.HEAPU8.buffer, dataPtr2, 3*3*1); |
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dataHeap2.set(new Uint8Array(data2.buffer)); |
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let dataHeap3 = new Uint8Array(cv.HEAPU8.buffer, dataPtr3, 3*3*1); |
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dataHeap3.set(new Uint8Array(data3.buffer)); |
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let mat1 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr, 0); |
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let mat2 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr2, 0); |
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let mat3 = new cv.Mat(3, 3, cv.CV_8UC1, dataPtr3, 0); |
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let dst = new cv.Mat(); |
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let none = new cv.Mat(); |
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cv.absdiff(mat1, mat2, dst); |
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// Verify result. |
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let size = dst.size(); |
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assert.equal(dst.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(dst.data, expectedAbsDiff); |
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cv.add(mat1, mat2, dst, none, -1); |
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// Verify result. |
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size = dst.size(); |
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assert.equal(dst.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(dst.data, expectedAdd); |
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cv.addWeighted(mat1, alpha, mat2, beta, gamma, dst, -1); |
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// Verify result. |
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size = dst.size(); |
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assert.equal(dst.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(dst.data, expectedWeightedAdd); |
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// default parameter |
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cv.addWeighted(mat1, alpha, mat2, beta, gamma, dst); |
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// Verify result. |
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size = dst.size(); |
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assert.equal(dst.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqual(dst.data, expectedWeightedAdd); |
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mat1.delete(); |
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mat2.delete(); |
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mat3.delete(); |
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dst.delete(); |
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none.delete(); |
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} |
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// Invert |
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{ |
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let inv1 = new cv.Mat(); |
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let inv2 = new cv.Mat(); |
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let inv3 = new cv.Mat(); |
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let inv4 = new cv.Mat(); |
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let data1 = new Float32Array([1, 0, 0, |
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0, 1, 0, |
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0, 0, 1]); |
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let data2 = new Float32Array([0, 0, 0, |
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0, 5, 0, |
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0, 0, 0]); |
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let data3 = new Float32Array([1, 1, 1, 0, |
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0, 3, 1, 2, |
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2, 3, 1, 0, |
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1, 0, 2, 1]); |
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let data4 = new Float32Array([1, 4, 5, |
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4, 2, 2, |
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5, 2, 2]); |
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let expected1 = new Float32Array([1, 0, 0, |
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0, 1, 0, |
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0, 0, 1]); |
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// Inverse does not exist! |
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let expected3 = new Float32Array([-3, -1/2, 3/2, 1, |
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1, 1/4, -1/4, -1/2, |
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3, 1/4, -5/4, -1/2, |
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-3, 0, 1, 1]); |
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let expected4 = new Float32Array([0, -1, 1, |
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-1, 23/2, -9, |
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1, -9, 7]); |
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let dataPtr1 = cv._malloc(3*3*4); |
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let dataPtr2 = cv._malloc(3*3*4); |
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let dataPtr3 = cv._malloc(4*4*4); |
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let dataPtr4 = cv._malloc(3*3*4); |
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let dataHeap = new Float32Array(cv.HEAP32.buffer, dataPtr1, 3*3); |
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dataHeap.set(new Float32Array(data1.buffer)); |
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let dataHeap2 = new Float32Array(cv.HEAP32.buffer, dataPtr2, 3*3); |
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dataHeap2.set(new Float32Array(data2.buffer)); |
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let dataHeap3 = new Float32Array(cv.HEAP32.buffer, dataPtr3, 4*4); |
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dataHeap3.set(new Float32Array(data3.buffer)); |
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let dataHeap4 = new Float32Array(cv.HEAP32.buffer, dataPtr4, 3*3); |
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dataHeap4.set(new Float32Array(data4.buffer)); |
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let mat1 = new cv.Mat(3, 3, cv.CV_32FC1, dataPtr1, 0); |
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let mat2 = new cv.Mat(3, 3, cv.CV_32FC1, dataPtr2, 0); |
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let mat3 = new cv.Mat(4, 4, cv.CV_32FC1, dataPtr3, 0); |
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let mat4 = new cv.Mat(3, 3, cv.CV_32FC1, dataPtr4, 0); |
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QUnit.assert.deepEqualWithTolerance = function( value, expected, tolerance ) { |
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for (let i = 0; i < value.length; i= i+1) { |
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this.pushResult( { |
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result: Math.abs(value[i]-expected[i]) < tolerance, |
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actual: value[i], |
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expected: expected[i], |
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} ); |
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} |
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}; |
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cv.invert(mat1, inv1, 0); |
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// Verify result. |
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let size = inv1.size(); |
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assert.equal(inv1.channels(), 1); |
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assert.equal(size.height, 3); |
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assert.equal(size.width, 3); |
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assert.deepEqualWithTolerance(inv1.data32F, expected1, 0.0001); |
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cv.invert(mat2, inv2, 0); |
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// Verify result. |
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assert.deepEqualWithTolerance(inv3.data32F, expected3, 0.0001); |
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cv.invert(mat3, inv3, 0); |
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// Verify result. |
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size = inv3.size(); |
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assert.equal(inv3.channels(), 1); |
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assert.equal(size.height, 4); |
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assert.equal(size.width, 4); |
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assert.deepEqualWithTolerance(inv3.data32F, expected3, 0.0001); |
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cv.invert(mat3, inv3, 1); |
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// Verify result. |
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assert.deepEqualWithTolerance(inv3.data32F, expected3, 0.0001); |
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cv.invert(mat4, inv4, 2); |
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// Verify result. |
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assert.deepEqualWithTolerance(inv4.data32F, expected4, 0.0001); |
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cv.invert(mat4, inv4, 3); |
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// Verify result. |
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assert.deepEqualWithTolerance(inv4.data32F, expected4, 0.0001); |
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mat1.delete(); |
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mat2.delete(); |
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mat3.delete(); |
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mat4.delete(); |
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inv1.delete(); |
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inv2.delete(); |
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inv3.delete(); |
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inv4.delete(); |
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} |
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//Rotate |
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{ |
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let dst = new cv.Mat(); |
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let src = cv.matFromArray(3, 2, cv.CV_8U, [1,2,3,4,5,6]); |
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cv.rotate(src, dst, cv.ROTATE_90_CLOCKWISE); |
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let size = dst.size(); |
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assert.equal(size.height, 2, "ROTATE_HEIGHT"); |
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assert.equal(size.width, 3, "ROTATE_WIGTH"); |
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let expected = new Uint8Array([5,3,1,6,4,2]); |
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assert.deepEqual(dst.data, expected); |
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dst.delete(); |
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src.delete(); |
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} |
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}); |
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QUnit.test('test_LUT', function(assert) { |
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{ |
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let src = cv.matFromArray(3, 3, cv.CV_8UC1, [255, 128, 0, 0, 128, 255, 1, 2, 254]); |
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let lutTable = []; |
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for (let i = 0; i < 256; i++) |
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{ |
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lutTable[i] = 255 - i; |
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} |
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let lut = cv.matFromArray(1, 256, cv.CV_8UC1, lutTable); |
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let dst = new cv.Mat(); |
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cv.LUT(src, lut, dst); |
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// Verify result. |
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assert.equal(dst.ucharAt(0), 0); |
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assert.equal(dst.ucharAt(1), 127); |
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assert.equal(dst.ucharAt(2), 255); |
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assert.equal(dst.ucharAt(3), 255); |
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assert.equal(dst.ucharAt(4), 127); |
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assert.equal(dst.ucharAt(5), 0); |
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assert.equal(dst.ucharAt(6), 254); |
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assert.equal(dst.ucharAt(7), 253); |
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assert.equal(dst.ucharAt(8), 1); |
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src.delete(); |
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lut.delete(); |
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dst.delete(); |
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} |
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});
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