def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the trainer."""
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
if args.weights is not None:
config["solver"]["weights"] = args.weights
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
net = apollocaffe.ApolloNet()
image_mean = load_image_mean_from_binproto(config['data']["idl_mean"])
fake_input_en = {"image": np.zeros((1, 3, 227, 227))}
forward(net, fake_input_en, deploy=True)
if config["solver"]["weights"]:
net.load(config["solver"]["weights"])
else:
raise Exception('weights file is not provided!')
run_socket(net, 13502, image_mean)
def main():
parser = apollocaffe.base_parser()
parser.add_argument("--config", required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
train(config)
def main():
parser = apollocaffe.base_parser()
parser.add_argument("--config", required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
evaluate(config)
def main():
parser = apollocaffe.base_parser()
parser.add_argument("--config", required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
list_add=data_root+'list_all_test.txt'
list_crop_add=data_root+'list_det_crop_align_filled.txt'
feat_add=data_root+'feat1.txt'
train_gt=np.loadtxt(list_add, dtype={'names': ('name', ), 'formats': ('S200', )})
train_crop_gt=np.loadtxt(list_crop_add, dtype={'names': ('name', 'label'), 'formats': ('S200', 'i4')})
train_feat=np.loadtxt(feat_add)
train_feat_list=[]
train_label_list=[]
assert(len(train_crop_gt)==train_feat.shape[0])
im_list=train_crop_gt['name'];
for k in xrange(len(im_list)):
im_list[k]=im_list[k].split('/')[-1][0:-7]
im_list_uniq=list(set(im_list))
for s in im_list_uniq:
idx=s==train_crop_gt['name']
feat=train_feat[idx,:]
train_feat_list.append(feat)
train_label_list.append(s)
feat_add2=data_root+'feat2.txt'
train_feat2=np.loadtxt(feat_add2)#.reshape((-1,1))
train_feat_list2=[]
assert(len(train_crop_gt)==train_feat2.shape[0])
for s in im_list_uniq:
idx=s==im_list
feat2=train_feat2[idx,:]
train_feat_list2.append(feat2)
holistic_feat_add=data_root+'feat_centrist_test_d1024.txt'
holistic_feat=np.loadtxt(holistic_feat_add)
scene_feat_list=[]
for k,s in enumerate(im_list_uniq):
idx=s.split('/')[-1]==train_gt['name']
assert(idx.sum()==1)
scene_feat_list.append(holistic_feat[idx,:])
test_data={'feats': train_feat_list, 'feats2': train_feat_list2, 'labels': train_label_list, 'scene_feats': scene_feat_list, 'current_idx': 0}
evaluate(config, test_data)
def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the test."""
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
print ("Test config file is " + config["data"]["test_idl"] )
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(0) # gpu
test(config)
def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the test."""
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
print("Test config file is " + config["data"]["test_idl"])
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(0) # gpu
test(config)
def main():
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
if args.weights is not None:
config["solver"]["weights"] = args.weights
config["solver"]["start_iter"] = args.start_iter
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
train(config)
def main():
parser = apollocaffe.base_parser()
parser.add_argument("--config", required=True)
args = parser.parse_args()
config = json.load(open(args.config, "r"))
if args.weights is not None:
config["solver"]["weights"] = args.weights
config["solver"]["start_iter"] = args.start_iter
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
train(config)
def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the trainer."""
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
if args.weights is not None:
config["solver"]["weights"] = args.weights
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
deploy(config)
def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the trainer."""
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
if args.weights is not None:
config["solver"]["weights"] = args.weights
config["solver"]["start_iter"] = args.start_iter
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
train(config)
def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the trainer."""
parser = apollocaffe.base_parser()
parser.add_argument('--config', required=True)
args = parser.parse_args()
config = json.load(open(args.config, 'r'))
if args.weights is not None:
config["solver"]["weights"] = args.weights
config["solver"]["start_iter"] = args.start_iter
apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
apollocaffe.set_cpp_loglevel(args.loglevel)
print json.dumps(config['solver'], indent=4, sort_keys=True)
print json.dumps(config['MMD'], indent=4, sort_keys=True)
train(config)
def main():
"""Sets up all the configurations for apollocaffe, and ReInspect
and runs the trainer."""
parser = apollocaffe.base_parser()
parser.add_argument('--datasize', required=True)
parser.add_argument('--batchsize', required=True)
parser.add_argument('--numIter', required=True)
args = parser.parse_args()
# config = json.load(open(args.config, 'r'))
# if args.weights is not None:
# config["solver"]["weights"] = args.weights
# config["solver"]["start_iter"] = args.start_iter
# apollocaffe.set_random_seed(config["solver"]["random_seed"])
apollocaffe.set_device(args.gpu)
datasize = int(args.datasize)
batchsize = int(args.batchsize)
numIter = int(args.numIter)
# apollocaffe.set_cpp_loglevel(args.loglevel)
train(datasize, batchsize, numIter)
import os
import json
import apollocaffe
from apollocaffe.layers import (Concat, Dropout, LstmUnit, InnerProduct,
NumpyData, Softmax, SoftmaxWithLoss, Wordvec)
batch_size = 32
vocab_size = 256
zero_symbol = vocab_size - 1
dimension = 250
base_lr = 0.15
clip_gradients = 10
i_temperature = 1.5
parser = apollocaffe.base_parser()
parser.add_argument('--data_source', type=str)
args = parser.parse_args()
apollocaffe.set_device(args.gpu)
apollocaffe.set_random_seed(0)
def get_data():
if args.data_source:
data_source = args.data_source
else:
data_source = '%s/reddit_ml.txt' % os.path.dirname(
os.path.realpath(__file__))
if not os.path.exists(data_source):
raise IOError(
'You must download the data with ./examples/apollocaffe/char_model/get_char.sh'
import os
import json
import apollocaffe
from apollocaffe.layers import (Concat, Dropout, LstmUnit, InnerProduct, NumpyData,
Softmax, SoftmaxWithLoss, Wordvec)
batch_size = 32
vocab_size = 256
zero_symbol = vocab_size - 1
dimension = 250
base_lr = 0.15
clip_gradients = 10
i_temperature = 1.5
parser = apollocaffe.base_parser()
parser.add_argument('--data_source', type=str)
args = parser.parse_args()
apollocaffe.set_device(args.gpu)
apollocaffe.set_random_seed(0)
def get_data():
if args.data_source:
data_source = args.data_source
else:
data_source = '%s/reddit_ml.txt' % os.path.dirname(os.path.realpath(__file__))
if not os.path.exists(data_source):
raise IOError('You must download the data with ./examples/apollocaffe/char_model/get_char.sh')
epoch = 0
while True: