def __init__(self, model_config, weightfile, yolo):
super(DarknetParser, self).__init__()
if not os.path.exists(model_config):
raise ValueError(
'Darknet model config [{}] can not be found!'.format(
model_config))
if weightfile:
self.weight_loaded = True
fp = open(weightfile, 'rb')
header = np.fromfile(fp, count=4, dtype=np.int32)
self.buf = np.fromfile(fp, dtype=np.float32)
print("weights buf size: {}".format(self.buf.size))
fp.close()
if yolo == "1":
self.start = 1 #yolov2
else:
self.start = 0 #yolov3 resnet
model = parse_cfg(model_config)
self.dk_graph = DarknetGraph(model)
self.dk_graph.build()
def __init__(self, model_config, weightfile):
super(DarknetParser, self).__init__()
if not os.path.exists(model_config):
raise ValueError(
'Darknet model config [{}] can not be found!'.format(
model_config))
# model = _cntk.Function.load(model)
# print(model_config)
if weightfile:
# print(weight)
self.weight_loaded = True
# net_info = cfg2prototxt(model_config)
# print(net_info)
# save_prototxt(net_info , 'resnet50.prototxt', region=False)
# net = caffe.Net('resnet50.prototxt', caffe.TEST)
# params = net.params
# print(params)
fp = open(weightfile, 'rb')
header = np.fromfile(fp, count=4, dtype=np.int32)
self.buf = np.fromfile(fp, dtype=np.float32)
print(self.buf.size)
fp.close()
self.start = 1
model = parse_cfg(model_config)
# print(model)
self.dk_graph = DarknetGraph(model)
self.dk_graph.build()