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1ba7c728a6
[evolution] Stitching for OpenCV 4.0 * stitching: wrap Stitcher::create for bindings * provide method for consistent stitcher usage across languages * samples: add python stitching sample * port cpp stitching sample to python * stitching: consolidate Stitcher create methods * remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API * deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create * stitching: avoid anonymous enum in Stitcher * ORIG_RESOL should be double * add documentatiton * stitching: improve documentation in Stitcher * stitching: expose estimator in Stitcher * remove ABI hack * stitching: drop try_use_gpu flag * OCL will be used automatically through T-API in OCL-enable paths * CUDA won't be used unless user sets CUDA-enabled classes manually * stitching: drop FeaturesFinder * use Feature2D instead of FeaturesFinder * interoperability with features2d module * detach from dependency on xfeatures2d * features2d: fix compute and detect to work with UMat vectors * correctly pass UMats as UMats to allow OCL paths * support vector of UMats as output arg * stitching: use nearest interpolation for resizing masks * fix warnings
48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
#!/usr/bin/env python
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'''
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Stitching sample
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================
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Show how to use Stitcher API from python in a simple way to stitch panoramas
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or scans.
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'''
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from __future__ import print_function
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import cv2 as cv
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import numpy as np
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import argparse
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import sys
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modes = (cv.Stitcher_PANORAMA, cv.Stitcher_SCANS)
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parser = argparse.ArgumentParser(description='Stitching sample.')
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parser.add_argument('--mode',
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type = int, choices = modes, default = cv.Stitcher_PANORAMA,
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help = 'Determines configuration of stitcher. The default is `PANORAMA` (%d), '
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'mode suitable for creating photo panoramas. Option `SCANS` (%d) is suitable '
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'for stitching materials under affine transformation, such as scans.' % modes)
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parser.add_argument('--output', default = 'result.jpg',
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help = 'Resulting image. The default is `result.jpg`.')
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parser.add_argument('img', nargs='+', help = 'input images')
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args = parser.parse_args()
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# read input images
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imgs = []
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for img_name in args.img:
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img = cv.imread(img_name)
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if img is None:
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print("can't read image " + img_name)
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sys.exit(-1)
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imgs.append(img)
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stitcher = cv.Stitcher.create(args.mode)
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status, pano = stitcher.stitch(imgs)
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if status != cv.Stitcher_OK:
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print("Can't stitch images, error code = %d" % status)
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sys.exit(-1)
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cv.imwrite(args.output, pano);
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print("stitching completed successfully. %s saved!" % args.output)
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