我们从Python开源项目中，提取了以下18个代码示例，用于说明如何使用datasets.MATLAB。
def _do_matlab_eval(self, comp_id, output_dir='output'): rm_results = self.config['cleanup'] path = os.path.join(os.path.dirname(__file__), 'VOCdevkit-matlab-wrapper') cmd = 'cd {} && '.format(path) cmd += '{:s} -nodisplay -nodesktop '.format(datasets.MATLAB) cmd += '-r "dbstop if error; ' cmd += 'voc_eval(\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\',{:d}); quit;"' \ .format(self._devkit_path, comp_id, self._image_set, output_dir, int(rm_results)) print('Running:\n{}'.format(cmd)) status = subprocess.call(cmd, shell=True)
def _do_matlab_eval(self, comp_id, output_dir='output'): rm_results = self.config['cleanup'] path = os.path.join(os.path.dirname(__file__), 'VOCdevkit-matlab-wrapper') cmd = 'cd {} && '.format(path) cmd += '{:s} -nodisplay -nodesktop '.format(datasets.MATLAB) cmd += '-r "dbstop if error; ' cmd += 'voc_eval(\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\',{:d}); quit;"' \ .format(self._pascal_path + '/VOCdevkit' + self._year, comp_id, self._image_set, output_dir, int(rm_results)) print('Running:\n{}'.format(cmd)) status = subprocess.call(cmd, shell=True) # evaluate detection results
def _do_matlab_eval(self, comp_id, output_dir='output'): rm_results = self.config['cleanup'] path = os.path.join(os.path.dirname(__file__), 'VOCdevkit-matlab-wrapper') cmd = 'cd {} && '.format(path) cmd += '{:s} -nodisplay -nodesktop '.format(datasets.MATLAB) cmd += '-r "dbstop if error; ' cmd += 'detection_eval(\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\'); quit;"' \ .format(self._devkit_path, comp_id, self._image_set, output_dir,'KITTI_val_list.txt', 'KITTI_gt_val.txt') print('Running:\n{}'.format(cmd)) status = subprocess.call(cmd, shell=True)
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('--------------------------------------------------------------')
