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()