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()
