def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print(args)
if args.sample_stride != -1:
config.TEST.sample_stride = args.sample_stride
if args.key_frame_interval != -1:
config.TEST.KEY_FRAME_INTERVAL = args.key_frame_interval
if args.video_shuffle:
config.TEST.video_shuffle = args.video_shuffle
logger, final_output_path, tb_log_path = create_logger(config.output_path, config.log_path, args.cfg,
config.dataset.test_image_set)
trained_model = os.path.join(final_output_path, '..', '_'.join(
[iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix)
test_epoch = config.TEST.test_epoch
if args.test_pretrained:
trained_model = args.test_pretrained
test_epoch = 0
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path,
config.dataset.dataset_path, config.dataset.motion_iou_path,
ctx,
trained_model,
test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh,
logger=logger, output_path=final_output_path,
enable_detailed_eval=config.dataset.enable_detailed_eval)
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path, _ = create_logger(config.output_path,
config.log_path, args.cfg,
config.dataset.test_image_set)
test_rcnn(config,
config.dataset.dataset,
config.dataset.test_image_set,
config.dataset.root_path,
config.dataset.dataset_path,
config.dataset.motion_iou_path,
ctx,
os.path.join(
final_output_path, '..', '_'.join(
[iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix),
config.TEST.test_epoch,
args.vis,
args.ignore_cache,
args.shuffle,
config.TEST.HAS_RPN,
config.dataset.proposal,
args.thresh,
logger=logger,
output_path=final_output_path,
enable_detailed_eval=config.dataset.enable_detailed_eval)
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg,
config.dataset.test_image_set)
# test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
# ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
# args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
test_rcnn(config,
config.dataset.dataset,
config.dataset.test_image_set,
config.dataset.root_path,
config.dataset.dataset_path,
ctx,
os.path.join('./model', 'rfcn_vid'),
0,
args.vis,
args.ignore_cache,
args.shuffle,
config.TEST.HAS_RPN,
config.dataset.proposal,
args.thresh,
logger=logger,
output_path=final_output_path,
use_philly=args.usePhilly)
def main():
#ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
ctx = [mx.gpu(0), mx.gpu(1), mx.gpu(2), mx.gpu(3)]
print args
#gpu_nums = [int(i) for i in config.gpus.split(',')]
gpu_nums = [0, 1, 2, 3]
nms_dets = gpu_nms_wrapper(config.TEST.NMS, gpu_nums[0])
logger, final_output_path = create_logger(config.output_path, args.cfg,
config.dataset.test_image_set)
output_path = os.path.join(
final_output_path, '..',
'+'.join([iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix)
test_rcnn(config,
config.dataset.dataset,
config.dataset.test_image_set,
config.dataset.root_path,
config.dataset.dataset_path,
ctx,
output_path,
config.TEST.test_epoch,
args.vis,
args.ignore_cache,
args.shuffle,
config.TEST.HAS_RPN,
config.dataset.proposal,
args.thresh,
logger=logger,
output_path=final_output_path,
nms_dets=nms_dets,
is_docker=args.is_docker)
def main():
# ctx为gpu(...)，其中配置项在yaml配置文件中
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
# print('ctx:', ctx)
print args
# config.output_path在yaml文件中定义，cfg为对应的yaml文件路径
logger, final_output_path = create_logger(config.output_path, args.cfg,
config.dataset.test_image_set)
# config.dataset.dataset=ImageNetVID
test_rcnn(config,
config.dataset.dataset,
config.dataset.test_image_set,
config.dataset.root_path,
config.dataset.dataset_path,
config.dataset.motion_iou_path,
ctx,
os.path.join(
final_output_path, '..', '_'.join(
[iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix),
config.TEST.test_epoch,
args.vis,
args.ignore_cache,
args.shuffle,
config.TEST.HAS_RPN,
config.dataset.proposal,
args.thresh,
logger=logger,
output_path=final_output_path,
enable_detailed_eval=config.dataset.enable_detailed_eval)
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg,
config.dataset.test_image_set)
print "test with params in epoch " + str(config.TEST.test_epoch)
test_rcnn(config,
config.dataset.dataset,
config.dataset.test_image_set,
config.dataset.root_path,
config.dataset.dataset_path,
ctx,
os.path.join(
final_output_path, '..', '_'.join(
[iset for iset in config.dataset.image_set.split('+')]),
config.TRAIN.model_prefix),
config.TEST.test_epoch,
args.vis,
args.ignore_cache,
args.shuffle,
config.TEST.HAS_RPN,
config.dataset.proposal,
args.thresh,
logger=logger,
output_path=final_output_path)
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
def main():
import mxnet as mx
import mxnet.ndarray as nd
nd.zeros((1, 3, 600, 1000), mx.gpu(0), dtype=float)
print('GPU ok')
ctx = [mx.gpu(0)]
print(args)
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set,
config.dataset.root_path, config.dataset.dataset_path,
ctx, os.path.join('model', config.TRAIN.model_prefix), config.TEST.test_epoch,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN,
config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
def main():
ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')]
output_dir = "/tmp/res"
if not os.path.exists(output_dir):
os.mkdir(output_dir)
print args
logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set)
sets = "/media/indoordesk/653ce34c-0c14-4427-8029-be7afe6d1989/test_sets/ImageSets"
sets = "/data2/test_sets/ImageSets"
#for epoc in range(1, 30):
maps = []
#for epoc in range(1, 30):
for file_name in os.listdir(sets):
if "_eval" in file_name:
continue
logger.info("About to test with images:" + file_name)
print ("About to test with images:" + file_name)
try:
res = test_rcnn(config, config.dataset.dataset, file_name.replace(".txt", ""), config.dataset.root_path, config.dataset.dataset_path, config.dataset.motion_iou_path,
ctx, join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), epoc,
args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path,
enable_detailed_eval=config.dataset.enable_detailed_eval)
with open(join(output_dir, file_name), "a") as f:
f.write('epoc: %s res: %s \n' % (epoc, res))
except Exception as e:
logger.error(e)
print e
print maps
