def _createEvaluator(self, annoPath):
if self.config['use_salt']: self._salt = str(uuid.uuid4())
else: self._salt = None
cachedir = self._cachedir
if not osp.isdir(cachedir):
os.makedirs(cachedir)
return bboxEvaluator(self._datasetName, self.classes, self._compID,
"_" + self._salt, cachedir, self._imageSetPath,
self._image_index, annoPath, self.load_annotation)
def _createEvaluator(self,compID):
if self.config['use_salt']: self._salt = str(uuid.uuid4())
else: self._salt = None
cachedir = os.path.join(self._path_root,\
'annotations_cache',\
self._image_set)
if not osp.isdir(cachedir):
os.makedirs(cachedir)
return bboxEvaluator(self._datasetName,self.classes,
compID, "_" + self._salt,
cachedir, self._imageSetPath)
def _createEvaluator(self, annoPath):
if self.config['use_salt']: self._salt = str(uuid.uuid4())
else: self._salt = None
cachedir = self._cachedir
if not osp.isdir(cachedir):
os.makedirs(cachedir)
if cfg.TASK == 'object_detection':
return bboxEvaluator(self._datasetName, self.classes, self._compID,
self._salt, cachedir, self._imageSetPath,
self._image_index, annoPath,
self.load_annotation)
elif cfg.TASK == 'classification':
return classificationEvaluator(self._datasetName, self.classes,
self._compID, self._salt, cachedir,
self._imageSetPath,
self._image_index, annoPath,
self.load_annotation)
else:
print("\n\n\nNo Evaluator Included\n\n\n")
return None
path = osp.join(prefix_path, "widths.dat")
np.savetxt(path, widths, fmt='%.18e', delimiter=' ')
path = osp.join(prefix_path, "heights.dat")
np.savetxt(path, heights, fmt='%.18e', delimiter=' ')
_compID, _salt, _imageSet, cls = getResultsFileFormatFromFilename(
txtFilename)
print(_compID, _salt, _imageSet, cls)
print(imdb._image_index[:10])
print(imdb.name)
print(imdb._cachedir)
bbEval = bboxEvaluator(imdb.name,
imdb.classes,
_compID,
_salt,
imdb._cachedir,
imdb._imageSetPath,
imdb._image_index,
cfgData['PATH_TO_ANNOTATIONS'],
imdb.load_annotation,
onlyCls=cls)
bbEval._pathResults = '/'.join(txtFilename.split("/")[:-1]) + "/"
bbEval._imageSet = _imageSet
bbEval._do_python_eval("./output/txtEval/")
'''
argparse.ArgumentParser
Input: (description='Generate an Imdb Report'), Output: parser
get_repo_imdb
input: (imdb_name), output: imdb
get_training_roidb