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Open Source Computer Vision Library
https://opencv.org/
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206 lines
5.2 KiB
206 lines
5.2 KiB
#!/usr/bin/env python |
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"""Algorithm serialization test.""" |
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from __future__ import print_function |
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import base64 |
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import json |
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import tempfile |
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import os |
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import cv2 as cv |
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import numpy as np |
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from tests_common import NewOpenCVTests |
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class MyData: |
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def __init__(self): |
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self.A = 97 |
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self.X = np.pi |
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self.name = 'mydata1234' |
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def write(self, fs, name): |
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fs.startWriteStruct(name, cv.FileNode_MAP|cv.FileNode_FLOW) |
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fs.write('A', self.A) |
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fs.write('X', self.X) |
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fs.write('name', self.name) |
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fs.endWriteStruct() |
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def read(self, node): |
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if (not node.empty()): |
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self.A = int(node.getNode('A').real()) |
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self.X = node.getNode('X').real() |
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self.name = node.getNode('name').string() |
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else: |
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self.A = self.X = 0 |
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self.name = '' |
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class filestorage_io_test(NewOpenCVTests): |
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strings_data = ['image1.jpg', 'Awesomeness', '../data/baboon.jpg'] |
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R0 = np.eye(3,3) |
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T0 = np.zeros((3,1)) |
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def write_data(self, fname): |
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fs = cv.FileStorage(fname, cv.FileStorage_WRITE) |
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R = self.R0 |
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T = self.T0 |
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m = MyData() |
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fs.write('iterationNr', 100) |
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fs.startWriteStruct('strings', cv.FileNode_SEQ) |
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for elem in self.strings_data: |
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fs.write('', elem) |
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fs.endWriteStruct() |
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fs.startWriteStruct('Mapping', cv.FileNode_MAP) |
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fs.write('One', 1) |
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fs.write('Two', 2) |
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fs.endWriteStruct() |
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fs.write('R_MAT', R) |
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fs.write('T_MAT', T) |
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m.write(fs, 'MyData') |
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fs.release() |
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def read_data_and_check(self, fname): |
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fs = cv.FileStorage(fname, cv.FileStorage_READ) |
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n = fs.getNode('iterationNr') |
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itNr = int(n.real()) |
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self.assertEqual(itNr, 100) |
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n = fs.getNode('strings') |
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self.assertTrue(n.isSeq()) |
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self.assertEqual(n.size(), len(self.strings_data)) |
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for i in range(n.size()): |
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self.assertEqual(n.at(i).string(), self.strings_data[i]) |
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n = fs.getNode('Mapping') |
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self.assertEqual(int(n.getNode('Two').real()), 2) |
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self.assertEqual(int(n.getNode('One').real()), 1) |
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R = fs.getNode('R_MAT').mat() |
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T = fs.getNode('T_MAT').mat() |
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self.assertEqual(cv.norm(R, self.R0, cv.NORM_INF), 0) |
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self.assertEqual(cv.norm(T, self.T0, cv.NORM_INF), 0) |
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m0 = MyData() |
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m = MyData() |
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m.read(fs.getNode('MyData')) |
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self.assertEqual(m.A, m0.A) |
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self.assertEqual(m.X, m0.X) |
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self.assertEqual(m.name, m0.name) |
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n = fs.getNode('NonExisting') |
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self.assertTrue(n.isNone()) |
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fs.release() |
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def run_fs_test(self, ext): |
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fd, fname = tempfile.mkstemp(prefix="opencv_python_sample_filestorage", suffix=ext) |
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os.close(fd) |
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self.write_data(fname) |
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self.read_data_and_check(fname) |
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os.remove(fname) |
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def test_xml(self): |
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self.run_fs_test(".xml") |
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def test_yml(self): |
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self.run_fs_test(".yml") |
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def test_json(self): |
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self.run_fs_test(".json") |
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def test_base64(self): |
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fd, fname = tempfile.mkstemp(prefix="opencv_python_sample_filestorage_base64", suffix=".json") |
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os.close(fd) |
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np.random.seed(42) |
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self.write_base64_json(fname) |
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os.remove(fname) |
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@staticmethod |
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def get_normal_2d_mat(): |
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rows = 10 |
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cols = 20 |
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cn = 3 |
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image = np.zeros((rows, cols, cn), np.uint8) |
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image[:] = (1, 2, 127) |
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for i in range(rows): |
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for j in range(cols): |
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image[i, j, 1] = (i + j) % 256 |
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return image |
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@staticmethod |
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def get_normal_nd_mat(): |
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shape = (2, 2, 1, 2) |
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cn = 4 |
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image = np.zeros(shape + (cn,), np.float64) |
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image[:] = (0.888, 0.111, 0.666, 0.444) |
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return image |
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@staticmethod |
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def get_empty_2d_mat(): |
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shape = (0, 0) |
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cn = 1 |
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image = np.zeros(shape + (cn,), np.uint8) |
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return image |
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@staticmethod |
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def get_random_mat(): |
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rows = 8 |
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cols = 16 |
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cn = 1 |
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image = np.random.rand(rows, cols, cn) |
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return image |
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@staticmethod |
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def decode(data): |
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# strip $base64$ |
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encoded = data[8:] |
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if len(encoded) == 0: |
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return b'' |
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# strip info about datatype and padding |
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return base64.b64decode(encoded)[24:] |
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def write_base64_json(self, fname): |
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fs = cv.FileStorage(fname, cv.FileStorage_WRITE_BASE64) |
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mats = {'normal_2d_mat': self.get_normal_2d_mat(), |
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'normal_nd_mat': self.get_normal_nd_mat(), |
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'empty_2d_mat': self.get_empty_2d_mat(), |
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'random_mat': self.get_random_mat()} |
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for name, mat in mats.items(): |
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fs.write(name, mat) |
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fs.release() |
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data = {} |
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with open(fname) as file: |
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data = json.load(file) |
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for name, mat in mats.items(): |
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buffer = b'' |
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if mat.size != 0: |
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if hasattr(mat, 'tobytes'): |
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buffer = mat.tobytes() |
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else: |
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buffer = mat.tostring() |
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self.assertEqual(buffer, self.decode(data[name]['data'])) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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