id_map = [(x[0], x[1]) for x in id_map if x[0] in existingImages]
minId, maxId = min([x[1] for x in id_map]), max([x[1] for x in id_map])
idNum = None
if len(args) > 4:
idNum = int(args[4])
rev_map = {}
for x in id_map:
if not x[1] in rev_map:
rev_map[x[1]] = []
rev_map[x[1]].append(x[0])
print('Loading Object Detector')
det = ObjectDetector(objdetmodel)
det.SCORE_THRESHOLD = 0.7
det.loadModel()
# Warming up
det.getBoundingBoxes(readImageFromFile(os.path.join(folder,
rev_map[0][0])))
det.getBoundingBoxes(readImageFromFile(os.path.join(folder,
rev_map[0][0])))
print('Loading Object Identifier')
idn = SvmIdentifier(modelPath, det)
idn.loadModel()
if not idNum is None and not idn.isPresent(idNum):
print(
'Provided Id {} is not present in trained model, will choose random Id'
)
