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 += 'setenv(\'LC_ALL\',\'C\'); 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 evaluate_detections(self, all_boxes, output_dir): comp_id = self._write_inria_results_file(all_boxes) self._do_matlab_eval(comp_id, output_dir) def competition_mode(self, on): if on: self.config['use_salt'] = False self.config['cleanup'] = False else: self.config['use_salt'] = True self.config['cleanup'] = True if __name__ == '__main__': d = datasets.inria('train', '') res = d.roidb from IPython import embed; embed()
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('--------------------------------------------------------------') def competition_mode(self, on): if on: self.config['use_salt'] = False self.config['cleanup'] = False else: self.config['use_salt'] = True self.config['cleanup'] = True if __name__ == '__main__': d = datasets.inria('train', '') pdb.set_trace() res = d.roidb from IPython import embed embed()
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 += 'setenv(\'LC_ALL\',\'C\'); 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 evaluate_detections(self, all_boxes, output_dir): comp_id = self._write_inria_results_file(all_boxes, output_dir) #self._do_matlab_eval(comp_id, output_dir) def competition_mode(self, on): if on: self.config['use_salt'] = False self.config['cleanup'] = False else: self.config['use_salt'] = True self.config['cleanup'] = True if __name__ == '__main__': d = datasets.inria('train', 'test') res = d.roidb from IPython import embed embed()