Python fast_rcnn.config.cfg.RNG_SEED Examples

The following are 29 code examples of fast_rcnn.config.cfg.RNG_SEED(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module fast_rcnn.config.cfg , or try the search function .
Example #1
Source File: train_svms.py    From SubCNN with MIT License 6 votes vote down vote up 
def __init__(self, cls, dim, feature_scale=1.0,
                 C=0.001, B=10.0, pos_weight=2.0):
        self.pos = np.zeros((0, dim), dtype=np.float32)
        self.neg = np.zeros((0, dim), dtype=np.float32)
        self.B = B
        self.C = C
        self.cls = cls
        self.pos_weight = pos_weight
        self.dim = dim
        self.feature_scale = feature_scale
        self.svm = svm.LinearSVC(C=C, class_weight={1: 2, -1: 1},
                                 intercept_scaling=B, verbose=1,
                                 penalty='l2', loss='l1',
                                 random_state=cfg.RNG_SEED, dual=True)
        self.pos_cur = 0
        self.num_neg_added = 0
        self.retrain_limit = 2000
        self.evict_thresh = -1.1
        self.loss_history = []
Example #2
Source File: train_svms.py    From face-py-faster-rcnn with MIT License 6 votes vote down vote up 
def __init__(self, cls, dim, feature_scale=1.0,
                 C=0.001, B=10.0, pos_weight=2.0):
        self.pos = np.zeros((0, dim), dtype=np.float32)
        self.neg = np.zeros((0, dim), dtype=np.float32)
        self.B = B
        self.C = C
        self.cls = cls
        self.pos_weight = pos_weight
        self.dim = dim
        self.feature_scale = feature_scale
        self.svm = svm.LinearSVC(C=C, class_weight={1: 2, -1: 1},
                                 intercept_scaling=B, verbose=1,
                                 penalty='l2', loss='l1',
                                 random_state=cfg.RNG_SEED, dual=True)
        self.pos_cur = 0
        self.num_neg_added = 0
        self.retrain_limit = 2000
        self.evict_thresh = -1.1
        self.loss_history = []
Example #3
Source File: train_svms.py    From caffe-faster-rcnn-resnet-fpn with MIT License 6 votes vote down vote up 
def __init__(self, cls, dim, feature_scale=1.0,
                 C=0.001, B=10.0, pos_weight=2.0):
        self.pos = np.zeros((0, dim), dtype=np.float32)
        self.neg = np.zeros((0, dim), dtype=np.float32)
        self.B = B
        self.C = C
        self.cls = cls
        self.pos_weight = pos_weight
        self.dim = dim
        self.feature_scale = feature_scale
        self.svm = svm.LinearSVC(C=C, class_weight={1: 2, -1: 1},
                                 intercept_scaling=B, verbose=1,
                                 penalty='l2', loss='l1',
                                 random_state=cfg.RNG_SEED, dual=True)
        self.pos_cur = 0
        self.num_neg_added = 0
        self.retrain_limit = 2000
        self.evict_thresh = -1.1
        self.loss_history = []
Example #4
Source File: train_svms.py    From faster-rcnn-resnet with MIT License 6 votes vote down vote up 
def __init__(self, cls, dim, feature_scale=1.0,
                 C=0.001, B=10.0, pos_weight=2.0):
        self.pos = np.zeros((0, dim), dtype=np.float32)
        self.neg = np.zeros((0, dim), dtype=np.float32)
        self.B = B
        self.C = C
        self.cls = cls
        self.pos_weight = pos_weight
        self.dim = dim
        self.feature_scale = feature_scale
        self.svm = svm.LinearSVC(C=C, class_weight={1: 2, -1: 1},
                                 intercept_scaling=B, verbose=1,
                                 penalty='l2', loss='l1',
                                 random_state=cfg.RNG_SEED, dual=True)
        self.pos_cur = 0
        self.num_neg_added = 0
        self.retrain_limit = 2000
        self.evict_thresh = -1.1
        self.loss_history = []
Example #5
Source File: train_svms.py    From py-R-FCN with MIT License 6 votes vote down vote up 
def __init__(self, cls, dim, feature_scale=1.0,
                 C=0.001, B=10.0, pos_weight=2.0):
        self.pos = np.zeros((0, dim), dtype=np.float32)
        self.neg = np.zeros((0, dim), dtype=np.float32)
        self.B = B
        self.C = C
        self.cls = cls
        self.pos_weight = pos_weight
        self.dim = dim
        self.feature_scale = feature_scale
        self.svm = svm.LinearSVC(C=C, class_weight={1: 2, -1: 1},
                                 intercept_scaling=B, verbose=1,
                                 penalty='l2', loss='l1',
                                 random_state=cfg.RNG_SEED, dual=True)
        self.pos_cur = 0
        self.num_neg_added = 0
        self.retrain_limit = 2000
        self.evict_thresh = -1.1
        self.loss_history = []
Example #6
Source File: train_svms.py    From uai-sdk with Apache License 2.0 6 votes vote down vote up 
def __init__(self, cls, dim, feature_scale=1.0,
                 C=0.001, B=10.0, pos_weight=2.0):
        self.pos = np.zeros((0, dim), dtype=np.float32)
        self.neg = np.zeros((0, dim), dtype=np.float32)
        self.B = B
        self.C = C
        self.cls = cls
        self.pos_weight = pos_weight
        self.dim = dim
        self.feature_scale = feature_scale
        self.svm = svm.LinearSVC(C=C, class_weight={1: 2, -1: 1},
                                 intercept_scaling=B, verbose=1,
                                 penalty='l2', loss='l1',
                                 random_state=cfg.RNG_SEED, dual=True)
        self.pos_cur = 0
        self.num_neg_added = 0
        self.retrain_limit = 2000
        self.evict_thresh = -1.1
        self.loss_history = []
Example #7
Source File: train_faster_rcnn_alt_opt.py    From py-R-FCN with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #8
Source File: layer.py    From caffe-faster-rcnn-resnet-fpn with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #9
Source File: train_faster_rcnn_alt_opt.py    From caffe-faster-rcnn-resnet-fpn with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #10
Source File: layer.py    From oicr with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #11
Source File: layer.py    From py-R-FCN with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #12
Source File: train_rfcn_alt_opt_5stage.py    From py-R-FCN with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #13
Source File: layer.py    From SubCNN with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #14
Source File: train_stage1_fast_rcnn.py    From faster-rcnn-scenarios with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #15
Source File: generate_proposals.py    From faster-rcnn-scenarios with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #16
Source File: train_stage2_rpn.py    From faster-rcnn-scenarios with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #17
Source File: train.py    From faster-rcnn-scenarios with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #18
Source File: layer.py    From SubCNN with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #19
Source File: layer.py    From dpl with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #20
Source File: layer.py    From face-magnet with Apache License 2.0 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes, gpu_id=0):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self.gpu_id = gpu_id
        np.random.seed(gpu_id)
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #21
Source File: train_faster_rcnn_alt_opt.py    From uai-sdk with Apache License 2.0 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #22
Source File: train_rfcn_alt_opt_5stage.py    From uai-sdk with Apache License 2.0 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #23
Source File: train_faster_rcnn_alt_opt.py    From uai-sdk with Apache License 2.0 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #24
Source File: layer.py    From uai-sdk with Apache License 2.0 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #25
Source File: train.py    From scene-graph-TF-release with MIT License 5 votes vote down vote up 
def train_net(network_name, imdb, roidb, output_dir, tf_log, pretrained_model=None, max_iters=200000):
    config = tf.ConfigProto()
    config.allow_soft_placement=True
    # config.gpu_options.allow_growth=True
    with tf.Session(config=config) as sess:
        tf.set_random_seed(cfg.RNG_SEED)
        trainer = Trainer(sess, network_name, imdb, roidb, output_dir, tf_log, pretrained_model=pretrained_model)
        trainer.train_model(sess, max_iters)
Example #26
Source File: train_faster_rcnn_alt_opt.py    From faster-rcnn-resnet with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #27
Source File: layer.py    From faster-rcnn-resnet with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)
Example #28
Source File: train_faster_rcnn_alt_opt.py    From face-py-faster-rcnn with MIT License 5 votes vote down vote up 
def _init_caffe(cfg):
    """Initialize pycaffe in a training process.
    """

    import caffe
    # fix the random seeds (numpy and caffe) for reproducibility
    np.random.seed(cfg.RNG_SEED)
    caffe.set_random_seed(cfg.RNG_SEED)
    # set up caffe
    caffe.set_mode_gpu()
    caffe.set_device(cfg.GPU_ID)
Example #29
Source File: layer.py    From face-py-faster-rcnn with MIT License 5 votes vote down vote up 
def __init__(self, queue, roidb, num_classes):
        super(BlobFetcher, self).__init__()
        self._queue = queue
        self._roidb = roidb
        self._num_classes = num_classes
        self._perm = None
        self._cur = 0
        self._shuffle_roidb_inds()
        # fix the random seed for reproducibility
        np.random.seed(cfg.RNG_SEED)