def __init__(self, dataset, train_dataset, cls, dets, detname):
"""
Expects cached detections in Table format to be passed in.
The dets should not have the 'cls_ind' column, as they should all be of the
same class.
"""
Detector.__init__(self,dataset,train_dataset,cls,detname)
self.dets = dets
# TODO: hack for csc_X
suffix = detname[4:]
if self.detname=='dpm':
self.classif = DPMClassifier()
else:
self.classif = CSCClassifier(suffix, cls, train_dataset, dataset)
def compute_score(self, image, oracle=False, dets=None):
"""
Return the 0/1 decision of whether the cls of this detector is present in
the image, given the detections table.
If oracle=True, returns the correct answer (look up the ground truth).
"""
if oracle:
return Detector.compute_score(self, image, oracle)
if not dets:
img_ind = self.dataset.get_img_ind(image)
dets = self.dets.filter_on_column('img_ind',img_ind)
scores = dets.subset_arr('score')
score = self.classif.classify_image(scores)
dt = 0
# TODO: figure out the dt situation above
return (score,dt)
def test_subclass(self):
d = Detector(self.train_dataset, self.train_dataset, 'dog')
assert(isinstance(d, Detector))
