class TestParam:
# detection below min_det_score will be removed in the evaluation
min_det_score = 0.05
# only the top max_det_per_image detecitons will be evaluated
max_det_per_image = 100
# callback, useful in multi-scale testing
process_roidb = lambda x: x
# callback, useful in scale-aware post-processing
process_output = lambda x, y: process_output(x, y)
# the model name and epoch used during test
# by default the last checkpoint is employed
# user can override this with --epoch N when invoking script
class model:
prefix = "experiments/{}/checkpoint".format(General.name)
epoch = OptimizeParam.schedule.end_epoch
class nms:
type = "nms" # or "softnms"
thr = 0.5
# we make use of the coco test toolchain
# if no coco format annotation file is specified
# test script will generate one on the fly from roidb
class coco:
annotation = "data/coco/annotations/instances_minival2014.json"
class TestParam:
min_det_score = 0.05
max_det_per_image = 100
process_roidb = lambda x: x
process_output = lambda x, y: process_output(x, y)
class model:
prefix = "experiments/{}/checkpoint".format(General.name)
epoch = OptimizeParam.schedule.end_epoch
class nms:
type = "nms"
thr = 0.5
class coco:
annotation = "data/coco/annotations/instances_minival2014.json"
