def net_visualization(network=None,
num_classes=None,
data_shape=None,
train=None,
output_dir=None,
print_net=False,
net=None):
# if you specify your net, this means that you are calling this function from somewhere else..
if net is None:
if not train:
net = symbol_factory.get_symbol(network,
data_shape,
num_classes=num_classes)
else:
net = symbol_factory.get_symbol_train(network,
data_shape,
num_classes=num_classes)
if not train:
a = mx.viz.plot_network(net, shape={"data": (1, 3, data_shape, data_shape)}, \
node_attrs={"shape": 'rect', "fixedsize": 'false'})
filename = "ssd_" + network + '_' + str(data_shape) + '_' + 'test'
else:
a = mx.viz.plot_network(net, shape=None, \
node_attrs={"shape": 'rect', "fixedsize": 'false'})
filename = "ssd_" + network + '_' + 'train'
a.render(os.path.join(output_dir, filename))
if print_net:
print(net.tojson())
def get_ssd_symbol(network, batch_size):
image_shape = (3,299,299)
if 'resnet' in network:
image_shape = (3, 224, 224)
base_name = network.split('.')[-1]
sym = symbol_factory.get_symbol(network, 20)
return (sym, [('data', (batch_size,)+image_shape)])
def net_visualization(network=None,
num_classes=None,
data_shape=None,
train=None,
output_dir=None,
print_net=False,
net=None):
# if you specify your net, this means that you are calling this function from somewhere else..
if net is None:
if not train:
net = symbol_factory.get_symbol(network, data_shape, num_classes=num_classes)
else:
net = symbol_factory.get_symbol_train(network, data_shape, num_classes=num_classes)
if not train:
a = mx.viz.plot_network(net, shape={"data": (1, 3, data_shape, data_shape)}, \
node_attrs={"shape": 'rect', "fixedsize": 'false'})
filename = "ssd_" + network + '_' + str(data_shape)+'_'+'test'
else:
a = mx.viz.plot_network(net, shape=None, \
node_attrs={"shape": 'rect', "fixedsize": 'false'})
filename = "ssd_" + network + '_' + 'train'
a.render(os.path.join(output_dir, filename))
if print_net:
print(net.tojson())
def get_ssd_symbol(network, batch_size):
image_shape = (3,299,299)
if 'resnet' in network:
image_shape = (3, 224, 224)
base_name = network.split('.')[-1]
sym = symbol_factory.get_symbol(network, 1000)
with open('ssd.json', 'w') as f:
f.write(sym.tojson())
f.close()
return (sym, [('data', (batch_size,)+image_shape)])
def net_visualization(network=None,
num_classes=None,
data_shape=None,
train=None,
output_dir=None,
print_net=False,
net=None):
# if you specify your net, this means that you are calling this function from somewhere else..
if net is None:
if not train:
net = symbol_factory.get_symbol(network, data_shape, num_classes=num_classes)
else:
net = symbol_factory.get_symbol_train(network, data_shape, num_classes=num_classes)
parser.add_argument('--network',
type=str,
default='vgg16_reduced',
help='the cnn to use')
parser.add_argument('--num-classes',
type=int,
default=20,
help='the number of classes')
parser.add_argument('--data-shape',
type=int,
default=300,
help='set image\'s shape')
parser.add_argument('--train',
action='store_true',
default=False,
help='show train net')
args = parser.parse_args()
if not args.train:
net = symbol_factory.get_symbol(args.network,
args.data_shape,
num_classes=args.num_classes)
a = mx.viz.plot_network(net, shape={"data":(1,3,args.data_shape,args.data_shape)}, \
node_attrs={"shape":'rect', "fixedsize":'false'})
a.render("ssd_" + args.network + '_' + str(args.data_shape))
else:
net = symbol_factory.get_symbol_train(args.network,
args.data_shape,
num_classes=args.num_classes)
print(net.tojson())
from __future__ import print_function
import find_mxnet
import mxnet as mx
import argparse
import sys, os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'symbol'))
import symbol_factory
parser = argparse.ArgumentParser(description='network visualization')
parser.add_argument('--network', type=str, default='vgg16_reduced',
help = 'the cnn to use')
parser.add_argument('--num-classes', type=int, default=20,
help='the number of classes')
parser.add_argument('--data-shape', type=int, default=300,
help='set image\'s shape')
parser.add_argument('--train', action='store_true', default=False, help='show train net')
args = parser.parse_args()
if not args.train:
net = symbol_factory.get_symbol(args.network, args.data_shape, num_classes=args.num_classes)
a = mx.viz.plot_network(net, shape={"data":(1,3,args.data_shape,args.data_shape)}, \
node_attrs={"shape":'rect', "fixedsize":'false'})
a.render("ssd_" + args.network + '_' + str(args.data_shape))
else:
net = symbol_factory.get_symbol_train(args.network, args.data_shape, num_classes=args.num_classes)
print(net.tojson())