--- a
+++ b/test.py
@@ -0,0 +1,80 @@
+from datetime import datetime
+import numpy as np
+import argparse
+
+from model.initialization import initialization
+from model.utils import evaluation
+from config import conf
+
+
+def boolean_string(s):
+    if s.upper() not in {'FALSE', 'TRUE'}:
+        raise ValueError('Not a valid boolean string')
+    return s.upper() == 'TRUE'
+
+
+parser = argparse.ArgumentParser(description='Test')
+parser.add_argument('--iter', default='80000', type=int,
+                    help='iter: iteration of the checkpoint to load. Default: 80000')
+parser.add_argument('--batch_size', default='1', type=int,
+                    help='batch_size: batch size for parallel test. Default: 1')
+parser.add_argument('--cache', default=False, type=boolean_string,
+                    help='cache: if set as TRUE all the test data will be loaded at once'
+                         ' before the transforming start. Default: FALSE')
+opt = parser.parse_args()
+
+
+# Exclude identical-view cases
+def de_diag(acc, each_angle=False):
+    result = np.sum(acc - np.diag(np.diag(acc)), 1) / 10.0
+    if not each_angle:
+        result = np.mean(result)
+    return result
+
+
+m = initialization(conf, test=opt.cache)[0]
+
+# load model checkpoint of iteration opt.iter
+print('Loading the model of iteration %d...' % opt.iter)
+m.load(opt.iter)
+print('Transforming...')
+time = datetime.now()
+test = m.transform('test', opt.batch_size)
+print('Evaluating...')
+acc = evaluation(test, conf['data'])
+print('Evaluation complete. Cost:', datetime.now() - time)
+
+# Print rank-1 accuracy of the best model
+# e.g.
+# ===Rank-1 (Include identical-view cases)===
+# NM: 95.405,     BG: 88.284,     CL: 72.041
+for i in range(1):
+    print('===Rank-%d (Include identical-view cases)===' % (i + 1))
+    print('NM: %.3f,\tBG: %.3f,\tCL: %.3f' % (
+        np.mean(acc[0, :, :, i]),
+        np.mean(acc[1, :, :, i]),
+        np.mean(acc[2, :, :, i])))
+
+# Print rank-1 accuracy of the best model，excluding identical-view cases
+# e.g.
+# ===Rank-1 (Exclude identical-view cases)===
+# NM: 94.964,     BG: 87.239,     CL: 70.355
+for i in range(1):
+    print('===Rank-%d (Exclude identical-view cases)===' % (i + 1))
+    print('NM: %.3f,\tBG: %.3f,\tCL: %.3f' % (
+        de_diag(acc[0, :, :, i]),
+        de_diag(acc[1, :, :, i]),
+        de_diag(acc[2, :, :, i])))
+
+# Print rank-1 accuracy of the best model (Each Angle)
+# e.g.
+# ===Rank-1 of each angle (Exclude identical-view cases)===
+# NM: [90.80 97.90 99.40 96.90 93.60 91.70 95.00 97.80 98.90 96.80 85.80]
+# BG: [83.80 91.20 91.80 88.79 83.30 81.00 84.10 90.00 92.20 94.45 79.00]
+# CL: [61.40 75.40 80.70 77.30 72.10 70.10 71.50 73.50 73.50 68.40 50.00]
+np.set_printoptions(precision=2, floatmode='fixed')
+for i in range(1):
+    print('===Rank-%d of each angle (Exclude identical-view cases)===' % (i + 1))
+    print('NM:', de_diag(acc[0, :, :, i], True))
+    print('BG:', de_diag(acc[1, :, :, i], True))
+    print('CL:', de_diag(acc[2, :, :, i], True))