def __init__(self, solver_prototxt, output_dir, pretrained_model=None):
self.output_dir = output_dir
self.solver = caffe.SGDSolver(solver_prototxt)
if pretrained_model is not None:
print('Loading pretrained model '
'weights from {:s}').format(pretrained_model)
self.solver.net.copy_from(pretrained_model)
self.solver_param = caffe_pb2.SolverParameter()
with open(solver_prototxt, 'rt') as f:
pb2.text_format.Merge(f.read(), self.solver_param)
# --------------------------------------------------------
# Seg-FCN for Dragon
# Copyright (c) 2017 SeetaTech
# Written by Ting Pan
# --------------------------------------------------------
""" Test a FCN-8s(PASCAL VOC) network """
import dragon.vm.caffe as caffe
import score
import numpy as np
weights = 'snapshot/train_iter_100000.caffemodel'
if __name__ == '__main__':
# init
caffe.set_mode_gpu()
caffe.set_device(0)
solver = caffe.SGDSolver('solver.prototxt')
solver.net.copy_from(weights)
# scoring
val = np.loadtxt('../data/seg11valid.txt', dtype=str)
score.seg_tests(solver, 'D:/seg', val)
# --------------------------------------------------------
# Cifar-10 for Dragon
# Copyright(c) 2017 SeetaTech
# Written by Ting Pan
# --------------------------------------------------------
""" Train a cifar-10 net """
import dragon.vm.caffe as caffe
if __name__ == '__main__':
# init
caffe.set_mode_gpu()
# solve
solver = caffe.SGDSolver('cifar10_full_solver.prototxt')
solver.step(70000)
solver.snapshot()
# --------------------------------------------------------
# Cifar-10 for Dragon
# Copyright(c) 2017 SeetaTech
# Written by Ting Pan
# --------------------------------------------------------
""" Train a cifar-10 net """
import dragon.vm.caffe as caffe
if __name__ == '__main__':
# init
caffe.set_mode_gpu()
# solve
solver = caffe.SGDSolver('cifar10_quick_solver.prototxt')
solver.step(5000)
solver.snapshot()
