if class_names is None:
num_class = 2
else:
num_class = len(class_names)
if num_class > 2:
for i in xrange(1, num_class):
cocoGt = COCO(annFile)
cocoDt = cocoGt.loadRes(resFile)
cocoEval = COCOeval(cocoGt, cocoDt, annType)
cocoEval.params.maxDets = [1, 10, 100]
cocoEval.params.useCats = 1
cocoEval.params.catIds = [i]
cocoEval.evaluate()
print 'Evaluation results for class {}!'.format(class_names[i])
if choice['filter'] == 1:
cocoEval.calarap()
cocoEval.filter_image(maxDets=1000)
elif choice['print'] == 1:
cocoEval.accumulate()
cocoEval.summarize(print_curve='yes')
elif choice['summarize'] == 1:
cocoEval.accumulate()
cocoEval.summarize()
cocoGt = COCO(annFile)
cocoDt = cocoGt.loadRes(resFile)
cocoEval = COCOeval(cocoGt, cocoDt, annType)
cocoEval.params.maxDets = [1, 10, 100]
cocoEval.params.useCats = 1
cocoEval.evaluate()
print 'Evaluation results all class!'
if choice['filter'] == 1:
