Added compute_mAP.cmd for calculation mAP for Pascal VOC 2007 dataset.

Added reval_voc_py3.py and voc_eval_py3.py for Python3.

scripts/reval_voc_py3.py

@@ -0,0 +1,104 @@
+#!/usr/bin/env python
+
+# Adapt from ->
+# --------------------------------------------------------
+# Fast R-CNN
+# Copyright (c) 2015 Microsoft
+# Licensed under The MIT License [see LICENSE for details]
+# Written by Ross Girshick
+# --------------------------------------------------------
+# <- Written by Yaping Sun
+
+"""Reval = re-eval. Re-evaluate saved detections."""
+
+import os, sys, argparse
+import numpy as np
+import _pickle as cPickle
+#import cPickle
+
+from voc_eval_py3 import voc_eval
+
+def parse_args():
+    """
+    Parse input arguments
+    """
+    parser = argparse.ArgumentParser(description='Re-evaluate results')
+    parser.add_argument('output_dir', nargs=1, help='results directory',
+                        type=str)
+    parser.add_argument('--voc_dir', dest='voc_dir', default='data/VOCdevkit', type=str)
+    parser.add_argument('--year', dest='year', default='2017', type=str)
+    parser.add_argument('--image_set', dest='image_set', default='test', type=str)
+
+    parser.add_argument('--classes', dest='class_file', default='data/voc.names', type=str)
+
+    if len(sys.argv) == 1:
+        parser.print_help()
+        sys.exit(1)
+
+    args = parser.parse_args()
+    return args
+
+def get_voc_results_file_template(image_set, out_dir = 'results'):
+    filename = 'comp4_det_' + image_set + '_{:s}.txt'
+    path = os.path.join(out_dir, filename)
+    return path
+
+def do_python_eval(devkit_path, year, image_set, classes, output_dir = 'results'):
+    annopath = os.path.join(
+        devkit_path,
+        'VOC' + year,
+        'Annotations',
+        '{}.xml')
+    imagesetfile = os.path.join(
+        devkit_path,
+        'VOC' + year,
+        'ImageSets',
+        'Main',
+        image_set + '.txt')
+    cachedir = os.path.join(devkit_path, 'annotations_cache')
+    aps = []
+    # The PASCAL VOC metric changed in 2010
+    use_07_metric = True if int(year) < 2010 else False
+    print('VOC07 metric? ' + ('Yes' if use_07_metric else 'No'))
+    print('devkit_path=',devkit_path,', year = ',year)
+
+    if not os.path.isdir(output_dir):
+        os.mkdir(output_dir)
+    for i, cls in enumerate(classes):
+        if cls == '__background__':
+            continue
+        filename = get_voc_results_file_template(image_set).format(cls)
+        rec, prec, ap = voc_eval(
+            filename, annopath, imagesetfile, cls, cachedir, ovthresh=0.5,
+            use_07_metric=use_07_metric)
+        aps += [ap]
+        print('AP for {} = {:.4f}'.format(cls, ap))
+        with open(os.path.join(output_dir, cls + '_pr.pkl'), 'wb') as f:
+            cPickle.dump({'rec': rec, 'prec': prec, 'ap': ap}, f)
+    print('Mean AP = {:.4f}'.format(np.mean(aps)))
+    print('~~~~~~~~')
+    print('Results:')
+    for ap in aps:
+        print('{:.3f}'.format(ap))
+    print('{:.3f}'.format(np.mean(aps)))
+    print('~~~~~~~~')
+    print('')
+    print('--------------------------------------------------------------')
+    print('Results computed with the **unofficial** Python eval code.')
+    print('Results should be very close to the official MATLAB eval code.')
+    print('-- Thanks, The Management')
+    print('--------------------------------------------------------------')
+
+
+
+if __name__ == '__main__':
+    args = parse_args()
+
+    output_dir = os.path.abspath(args.output_dir[0])
+    with open(args.class_file, 'r') as f:
+        lines = f.readlines()
+
+    classes = [t.strip('\n') for t in lines]
+
+    print('Evaluating detections')
+    do_python_eval(args.voc_dir, args.year, args.image_set, classes, output_dir)