mirror of
https://github.com/opencv/opencv_contrib.git
synced 2025-10-16 22:35:51 +08:00
ac62d70f97
* Minor fixes * Start adding correspondence finding * Added finding of correspondences using GPC * New evaluation tool for GPC * Changed default parameters * Display ground truth in the evaluation tool * Added training tool for MPI Sintel dataset * Added the training tool for Middlebury dataset * Added some OpenCL optimization * Added explanatory notes * Minor improvements: time measurements + little ocl optimization * Added demos * Fixed warnings * Make parameter struct assignable * Fix warning * Proper command line argument usage * Prettified training tool, added parameters * Fixed VS warning * Fixed VS warning * Using of compressed forest.yml.gz files by default to save space * Added OpenCL flag to the evaluation tool * Updated documentation * Major speed and memory improvements: 1) Added new (optional) type of patch descriptors which are much faster. Retraining with option --descriptor-type=1 is required. 2) Got rid of hash table for descriptors, less memory usage. * Fixed various floating point errors related to precision. SIMD for dot product, forest traversing is a little bit faster now. * Tolerant floating point comparison * Triplets * Added comment * Choosing negative sample among nearest neighbors * Fix warning * Usage of parallel_for_() in critical places. Performance improvments. * Simulated annealing heuristic * Moved OpenCL kernel to separate file * Moved implementation to source file * Added basic accuracy tests for GPC and PCAFlow * Fixing warnings * Test accuracy constraints were too strict * Test accuracy constraints were too strict * Make tests more lightweight
59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
import argparse
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import glob
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import os
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import subprocess
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def execute(cmd):
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popen = subprocess.Popen(cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE)
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for stdout_line in iter(popen.stdout.readline, ''):
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print(stdout_line.rstrip())
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for stderr_line in iter(popen.stderr.readline, ''):
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print(stderr_line.rstrip())
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popen.stdout.close()
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popen.stderr.close()
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return_code = popen.wait()
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if return_code != 0:
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raise subprocess.CalledProcessError(return_code, cmd)
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def main():
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parser = argparse.ArgumentParser(
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description='Train Global Patch Collider using Middlebury dataset')
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parser.add_argument(
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'--bin_path',
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help='Path to the training executable (example_optflow_gpc_train)',
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required=True)
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parser.add_argument('--dataset_path',
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help='Path to the directory with frames',
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required=True)
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parser.add_argument('--gt_path',
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help='Path to the directory with ground truth flow',
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required=True)
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parser.add_argument('--descriptor_type',
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help='Descriptor type',
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type=int,
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default=0)
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args = parser.parse_args()
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seq = glob.glob(os.path.join(args.dataset_path, '*'))
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seq.sort()
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input_files = []
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for s in seq:
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if os.path.isdir(s):
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seq_name = os.path.basename(s)
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frames = glob.glob(os.path.join(s, 'frame*.png'))
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frames.sort()
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assert (len(frames) == 2)
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assert (os.path.basename(frames[0]) == 'frame10.png')
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assert (os.path.basename(frames[1]) == 'frame11.png')
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gt_flow = os.path.join(args.gt_path, seq_name, 'flow10.flo')
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if os.path.isfile(gt_flow):
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input_files += [frames[0], frames[1], gt_flow]
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execute([args.bin_path, '--descriptor-type=%d' % args.descriptor_type] + input_files)
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if __name__ == '__main__':
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main()
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