mirror of
https://github.com/JDAI-CV/fast-reid.git
synced 2025-06-03 14:50:47 +08:00
80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
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import sys
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import numpy as np
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import timeit
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import os.path as osp
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sys.path.insert(0, osp.dirname(osp.abspath(__file__)) + '/../../..')
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"""
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Test the speed of cython-based evaluation code. The speed improvements
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can be much bigger when using the real reid data, which contains a larger
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amount of query and gallery images.
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Note: you might encounter the following error:
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'AssertionError: Error: all query identities do not appear in gallery'.
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This is normal because the inputs are random numbers. Just try again.
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"""
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print('*** Compare running time ***')
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setup = '''
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import sys
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import os.path as osp
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import numpy as np
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sys.path.insert(0, osp.dirname(osp.abspath(__file__)) + '/../../..')
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from fastreid import evaluation
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num_q = 30
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num_g = 300
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max_rank = 5
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distmat = np.random.rand(num_q, num_g) * 20
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q_pids = np.random.randint(0, num_q, size=num_q)
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g_pids = np.random.randint(0, num_g, size=num_g)
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q_camids = np.random.randint(0, 5, size=num_q)
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g_camids = np.random.randint(0, 5, size=num_g)
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'''
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print('=> Using market1501\'s metric')
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pytime = timeit.timeit(
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'evaluation.evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=False)',
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setup=setup,
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number=20
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)
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cytime = timeit.timeit(
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'evaluation.evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=True)',
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setup=setup,
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number=20
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)
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print('Python time: {} s'.format(pytime))
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print('Cython time: {} s'.format(cytime))
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print('Cython is {} times faster than python\n'.format(pytime / cytime))
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print('=> Using cuhk03\'s metric')
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pytime = timeit.timeit(
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'evaluation.evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_metric_cuhk03=True, use_cython=False)',
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setup=setup,
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number=20
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)
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cytime = timeit.timeit(
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'evaluation.evaluate_rank(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_metric_cuhk03=True, use_cython=True)',
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setup=setup,
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number=20
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)
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print('Python time: {} s'.format(pytime))
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print('Cython time: {} s'.format(cytime))
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print('Cython is {} times faster than python\n'.format(pytime / cytime))
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"""
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print("=> Check precision")
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num_q = 30
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num_g = 300
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max_rank = 5
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distmat = np.random.rand(num_q, num_g) * 20
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q_pids = np.random.randint(0, num_q, size=num_q)
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g_pids = np.random.randint(0, num_g, size=num_g)
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q_camids = np.random.randint(0, 5, size=num_q)
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g_camids = np.random.randint(0, 5, size=num_g)
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cmc, mAP = evaluate(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=False)
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print("Python:\nmAP = {} \ncmc = {}\n".format(mAP, cmc))
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cmc, mAP = evaluate(distmat, q_pids, g_pids, q_camids, g_camids, max_rank, use_cython=True)
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print("Cython:\nmAP = {} \ncmc = {}\n".format(mAP, cmc))
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"""
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