def main():
workspace.GlobalInit(['caffe2', '--caffe2_log_level=0'])
args = parse_args()
logger.info('Called with args:')
logger.info(args)
if args.cfg_file is not None:
merge_cfg_from_file(args.cfg_file)
if args.opts is not None:
merge_cfg_from_list(args.opts)
cfg.NUM_GPUS = 1
assert_and_infer_cfg()
logger.info('Conerting model with config:')
logger.info(pprint.pformat(cfg))
assert not cfg.MODEL.KEYPOINTS_ON, "Keypoint model not supported."
assert not cfg.MODEL.MASK_ON, "Mask model not supported."
assert not cfg.FPN.FPN_ON, "FPN not supported."
assert not cfg.RETINANET.RETINANET_ON, "RetinaNet model not supported."
# load model from cfg
model, blobs = load_model(args)
net = core.Net('')
net.Proto().op.extend(copy.deepcopy(model.net.Proto().op))
net.Proto().external_input.extend(
copy.deepcopy(model.net.Proto().external_input))
net.Proto().external_output.extend(
copy.deepcopy(model.net.Proto().external_output))
net.Proto().type = args.net_execution_type
net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4
# Reset the device_option, change to unscope name and replace python operators
convert_net(args, net.Proto(), blobs)
# add operators for bbox
add_bbox_ops(args, net, blobs)
if args.fuse_af:
print('Fusing affine channel...')
net, blobs = mutils.fuse_net_affine(
net, blobs)
if args.use_nnpack:
mutils.update_mobile_engines(net.Proto())
# generate init net
empty_blobs = ['data', 'im_info']
init_net = gen_init_net(net, blobs, empty_blobs)
if args.device == 'gpu':
[net, init_net] = convert_model_gpu(args, net, init_net)
net.Proto().name = args.net_name
init_net.Proto().name = args.net_name + "_init"
if args.test_img is not None:
verify_model(args, [net, init_net], args.test_img)
_save_models(net, init_net, args)
def main():
workspace.GlobalInit(['caffe2', '--caffe2_log_level=0'])
args = parse_args()
logger.info('Called with args:')
logger.info(args)
if args.cfg_file is not None:
merge_cfg_from_file(args.cfg_file)
if args.opts is not None:
merge_cfg_from_list(args.opts)
cfg.NUM_GPUS = 1
assert_and_infer_cfg()
logger.info('Conerting model with config:')
logger.info(pprint.pformat(cfg))
assert not cfg.MODEL.KEYPOINTS_ON, "Keypoint model not supported."
assert not cfg.MODEL.MASK_ON, "Mask model not supported."
assert not cfg.FPN.FPN_ON, "FPN not supported."
assert not cfg.RETINANET.RETINANET_ON, "RetinaNet model not supported."
# load model from cfg
model, blobs = load_model(args)
net = core.Net('')
net.Proto().op.extend(copy.deepcopy(model.net.Proto().op))
net.Proto().external_input.extend(
copy.deepcopy(model.net.Proto().external_input))
net.Proto().external_output.extend(
copy.deepcopy(model.net.Proto().external_output))
net.Proto().type = args.net_execution_type
net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4
# Reset the device_option, change to unscope name and replace python operators
convert_net(args, net.Proto(), blobs)
# add operators for bbox
add_bbox_ops(args, net, blobs)
if args.fuse_af:
print('Fusing affine channel...')
net, blobs = mutils.fuse_net_affine(
net, blobs)
if args.use_nnpack:
mutils.update_mobile_engines(net.Proto())
# generate init net
empty_blobs = ['data', 'im_info']
init_net = gen_init_net(net, blobs, empty_blobs)
if args.device == 'gpu':
[net, init_net] = convert_model_gpu(args, net, init_net)
net.Proto().name = args.net_name
init_net.Proto().name = args.net_name + "_init"
if args.test_img is not None:
verify_model(args, [net, init_net], args.test_img)
_save_models(net, init_net, args)
def convert_main_net(args, main_net, blobs):
net = core.Net('')
net.Proto().op.extend(copy.deepcopy(main_net.op))
net.Proto().external_input.extend(copy.deepcopy(main_net.external_input))
net.Proto().external_output.extend(copy.deepcopy(main_net.external_output))
net.Proto().type = args.net_execution_type
net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4
convert_tools.convert_net(args, net.Proto(), blobs)
convert_tools.add_bbox_ops(args, net, blobs)
if args.fuse_af:
print('Fusing affine channel...')
net, blobs = mutils.fuse_net_affine(net, blobs)
if args.use_nnpack:
mutils.update_mobile_engines(net.Proto())
empty_blobs = ['data', 'im_info']
init_net = convert_tools.gen_init_net(net, blobs, empty_blobs)
if args.device == 'gpu':
[net, init_net] = convert_tools.convert_model_gpu(args, net, init_net)
net.Proto().name = args.net_name
init_net.Proto().name = args.net_name + '_init'
save_model(net.Proto(), init_net.Proto(), args.out_dir)
def convert_main_net(args, main_net, blobs):
net = core.Net('')
net.Proto().op.extend(copy.deepcopy(main_net.op))
net.Proto().external_input.extend(copy.deepcopy(main_net.external_input))
net.Proto().external_output.extend(copy.deepcopy(main_net.external_output))
net.Proto().type = args.net_execution_type
net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4
convert_tools.convert_net(args, net.Proto(), blobs)
convert_tools.add_bbox_ops(args, net, blobs)
if args.fuse_af:
print ('Fusing affine channel...')
net, blobs = mutils.fuse_net_affine(net, blobs)
if args.use_nnpack:
mutils.update_mobile_engines(net.Proto())
empty_blobs = ['data', 'im_info']
init_net = convert_tools.gen_init_net(net, blobs, empty_blobs)
if args.device == 'gpu':
[net, init_net] = convert_tools.convert_model_gpu(args, net, init_net)
net.Proto().name = args.net_name
init_net.Proto().name = args.net_name + '_init'
save_model(net.Proto(), init_net.Proto(), args.out_dir)
def main():
workspace.GlobalInit(["caffe2", "--caffe2_log_level=0"])
args = parse_args()
logger.info("Called with args:")
logger.info(args)
if args.cfg_file is not None:
merge_cfg_from_file(args.cfg_file)
if args.opts is not None:
merge_cfg_from_list(args.opts)
cfg.NUM_GPUS = 1
assert_and_infer_cfg()
logger.info("Converting model with config:")
logger.info(pprint.pformat(cfg))
# script will stop when it can't find an operator rather
# than stopping based on these flags
#
# assert not cfg.MODEL.KEYPOINTS_ON, "Keypoint model not supported."
# assert not cfg.MODEL.MASK_ON, "Mask model not supported."
# assert not cfg.FPN.FPN_ON, "FPN not supported."
# assert not cfg.RETINANET.RETINANET_ON, "RetinaNet model not supported."
# load model from cfg
model, blobs = load_model(args)
net = core.Net("")
net.Proto().op.extend(copy.deepcopy(model.net.Proto().op))
net.Proto().external_input.extend(
copy.deepcopy(model.net.Proto().external_input))
net.Proto().external_output.extend(
copy.deepcopy(model.net.Proto().external_output))
net.Proto().type = args.net_execution_type
net.Proto().num_workers = 1 if args.net_execution_type == "simple" else 4
# Reset the device_option, change to unscope name and replace python operators
convert_net(args, net.Proto(), blobs)
# add operators for bbox
add_bbox_ops(args, net, blobs)
if args.fuse_af:
print("Fusing affine channel...")
net, blobs = mutils.fuse_net_affine(net, blobs)
if args.use_nnpack:
mutils.update_mobile_engines(net.Proto())
# generate init net
empty_blobs = ["data", "im_info"]
init_net = gen_init_net(net, blobs, empty_blobs)
if args.device == "gpu":
[net, init_net] = convert_model_gpu(args, net, init_net)
net.Proto().name = args.net_name
init_net.Proto().name = args.net_name + "_init"
if args.test_img is not None:
verify_model(args, [net, init_net], args.test_img)
if args.logdb == 1:
output_file = os.path.join(args.out_dir, "model.logfiledb")
_export_to_logfiledb(args, net, init_net, empty_blobs, output_file)
else:
_save_models(net, init_net, args)