pascal_voc.py 文件源码

def _do_python_eval(self, output_dir = 'output'):
        annopath = os.path.join(
            self._devkit_path,
            'VOC' + self._year,
            'Annotations',
            '{:s}.xml')
        imagesetfile = os.path.join(
            self._devkit_path,
            'VOC' + self._year,
            'ImageSets',
            'Main',
            self._image_set + '.txt')
        cachedir = os.path.join(self._devkit_path, 'annotations_cache')
        aps = []
        # The PASCAL VOC metric changed in 2010
        use_07_metric = True if int(self._year) < 2010 else False
        print 'VOC07 metric? ' + ('Yes' if use_07_metric else 'No')
        if not os.path.isdir(output_dir):
            os.mkdir(output_dir)
        for i, cls in enumerate(self._classes):
            if cls == '__background__':
                continue
            filename = self._get_voc_results_file_template().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'), 'w') 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('Recompute with `./tools/reval.py --matlab ...` for your paper.')
        print('-- Thanks, The Management')
        print('--------------------------------------------------------------')