change double quotes to single quote in print
parent
356a677cd3
commit
26a9400609
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@ -11,10 +11,10 @@ import warnings
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try:
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from torchreid.eval_cylib.eval_metrics_cy import evaluate_cy
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IS_CYTHON_AVAI = True
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print("Using Cython evaluation code as the backend")
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print('Using Cython evaluation code as the backend')
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except ImportError:
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IS_CYTHON_AVAI = False
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warnings.warn("Cython evaluation is UNAVAILABLE, which is highly recommended")
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warnings.warn('Cython evaluation is UNAVAILABLE, which is highly recommended')
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def eval_cuhk03(distmat, q_pids, g_pids, q_camids, g_camids, max_rank):
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@ -27,7 +27,7 @@ def eval_cuhk03(distmat, q_pids, g_pids, q_camids, g_camids, max_rank):
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if num_g < max_rank:
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max_rank = num_g
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print("Note: number of gallery samples is quite small, got {}".format(num_g))
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print('Note: number of gallery samples is quite small, got {}'.format(num_g))
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indices = np.argsort(distmat, axis=1)
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matches = (g_pids[indices] == q_pids[:, np.newaxis]).astype(np.int32)
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@ -82,7 +82,7 @@ def eval_cuhk03(distmat, q_pids, g_pids, q_camids, g_camids, max_rank):
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all_AP.append(AP)
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num_valid_q += 1.
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assert num_valid_q > 0, "Error: all query identities do not appear in gallery"
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assert num_valid_q > 0, 'Error: all query identities do not appear in gallery'
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all_cmc = np.asarray(all_cmc).astype(np.float32)
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all_cmc = all_cmc.sum(0) / num_valid_q
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@ -99,7 +99,7 @@ def eval_market1501(distmat, q_pids, g_pids, q_camids, g_camids, max_rank):
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if num_g < max_rank:
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max_rank = num_g
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print("Note: number of gallery samples is quite small, got {}".format(num_g))
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print('Note: number of gallery samples is quite small, got {}'.format(num_g))
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indices = np.argsort(distmat, axis=1)
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matches = (g_pids[indices] == q_pids[:, np.newaxis]).astype(np.int32)
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@ -140,7 +140,7 @@ def eval_market1501(distmat, q_pids, g_pids, q_camids, g_camids, max_rank):
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AP = tmp_cmc.sum() / num_rel
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all_AP.append(AP)
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assert num_valid_q > 0, "Error: all query identities do not appear in gallery"
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assert num_valid_q > 0, 'Error: all query identities do not appear in gallery'
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all_cmc = np.asarray(all_cmc).astype(np.float32)
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all_cmc = all_cmc.sum(0) / num_valid_q
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