def test_net(imageset, year, root_path, devkit_path, prefix, epoch, ctx):
"""
wrapper for detector
:param imageset: image set to test on
:param year: year of image set
:param root_path: 'data' folder path
:param devkit_path: 'VOCdevkit' folder path
:param prefix: new model prefix
:param epoch: new model epoch
:param ctx: context to evaluate in
:return: None
"""
# set up logger
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# load testing data
voc, roidb = load_test_roidb(imageset, year, root_path, devkit_path)
test_data = ROIIter(roidb,
ctx=ctx,
batch_size=1,
shuffle=False,
mode='test')
# load model
args, auxs = load_param(prefix, epoch, convert=True, ctx=ctx)
# load symbol
sym = get_symbol_vgg_test()
# detect
detector = Detector(sym, ctx, args, auxs)
pred_eval(detector, test_data, voc, vis=False)
def test_rcnn(imageset, year, root_path, devkit_path, prefix, epoch, ctx, vis=False, has_rpn=True, proposal='rpn',
end2end=False):
# load symbol and testing data
if has_rpn:
# sym = get_vgg_test()
config.TRAIN.AGNOSTIC = True
config.END2END = 1
config.PIXEL_MEANS = np.array([[[0,0,0]]])
sym = resnext_101(num_class=21)
config.TEST.HAS_RPN = True
config.TEST.RPN_PRE_NMS_TOP_N = 6000
config.TEST.RPN_POST_NMS_TOP_N = 300
voc, roidb = load_gt_roidb(imageset, year, root_path, devkit_path)
else:
sym = get_vgg_rcnn_test()
voc, roidb = eval('load_test_' + proposal + '_roidb')(imageset, year, root_path, devkit_path)
# get test data iter
test_data = ROIIter(roidb, batch_size=1, shuffle=False, mode='test')
# load model
args, auxs, _ = load_param(prefix, epoch, convert=True, ctx=ctx)
# detect
detector = Detector(sym, ctx, args, auxs)
pred_eval(detector, test_data, voc, vis=vis)
def get_net(prefix, epoch, ctx):
config.TRAIN.AGNOSTIC = True
args, auxs, num_class = load_param(prefix, epoch, convert=True, ctx=ctx)
sym = resnext_101(num_class=num_class)
#sym = resnet_50(num_class=num_class)
detector = Detector(sym, ctx, args, auxs)
return detector
def test_rcnn(imageset,
year,
root_path,
devkit_path,
prefix,
epoch,
ctx,
vis=False,
has_rpn=True,
proposal='rpn'):
# load symbol and testing data
if has_rpn:
sym = get_vgg_test()
config.TEST.HAS_RPN = True
config.TEST.RPN_PRE_NMS_TOP_N = 6000
config.TEST.RPN_POST_NMS_TOP_N = 300
voc, roidb = load_gt_roidb(imageset, year, root_path, devkit_path)
else:
sym = get_vgg_rcnn_test()
voc, roidb = eval('load_test_' + proposal + '_roidb')(imageset, year,
root_path,
devkit_path)
# get test data iter
test_data = ROIIter(roidb, batch_size=1, shuffle=False, mode='test')
# load model
args, auxs, _ = load_param(prefix, epoch, convert=True, ctx=ctx)
# detect
detector = Detector(sym, ctx, args, auxs)
pred_eval(detector, test_data, voc, vis=vis)
def test_net(imageset, year, root_path, devkit_path, prefix, epoch, ctx, vis):
# set up logger
logger = logging.getLogger()
logger.setLevel(logging.INFO)
# load testing data
voc, roidb = load_test_rpn_roidb(imageset, year, root_path, devkit_path)
test_data = ROIIter(roidb, batch_size=1, shuffle=False, mode='test')
# load model
args, auxs = load_param(prefix, epoch, convert=True, ctx=ctx)
# load symbol
sym = get_vgg_rcnn_test()
# detect
detector = Detector(sym, ctx, args, auxs)
pred_eval(detector, test_data, voc, vis=vis)
def get_net(prefix, epoch, ctx):
args, auxs, num_class = load_param(prefix, epoch, convert=True, ctx=ctx)
sym = get_vgg_test(num_classes=num_class)
detector = Detector(sym, ctx, args, auxs)
return detector
def get_net(prefix, epoch, ctx):
args, auxs = load_param(prefix, epoch, convert=True, ctx=ctx)
sym = get_vgg_rcnn_test()
detector = Detector(sym, ctx, args, auxs)
return detector