本文整理匯總了Python中rcnn.processing.nms.gpu_nms_wrapper方法的典型用法代碼示例。如果您正苦於以下問題：Python nms.gpu_nms_wrapper方法的具體用法？Python nms.gpu_nms_wrapper怎麽用？Python nms.gpu_nms_wrapper使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類rcnn.processing.nms的用法示例。
在下文中一共展示了nms.gpu_nms_wrapper方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: __init__
# 需要導入模塊: from rcnn.processing import nms [as 別名]
# 或者: from rcnn.processing.nms import gpu_nms_wrapper [as 別名]
def __init__(self, gpu=0, test_mode=False):
self.ctx_id = gpu
self.ctx = mx.gpu(self.ctx_id)
self.fpn_keys = []
fpn_stride = []
fpn_base_size = []
self._feat_stride_fpn = [32, 16, 8]
for s in self._feat_stride_fpn:
self.fpn_keys.append('stride%s' % s)
fpn_stride.append(int(s))
fpn_base_size.append(16)
self._scales = np.array([32, 16, 8, 4, 2, 1])
self._ratios = np.array([1.0] * len(self._feat_stride_fpn))
self._anchors_fpn = dict(
zip(self.fpn_keys, generate_anchors_fpn(base_size=fpn_base_size, scales=self._scales, ratios=self._ratios)))
self._num_anchors = dict(zip(self.fpn_keys, [anchors.shape[0] for anchors in self._anchors_fpn.values()]))
self._rpn_pre_nms_top_n = 1000
# self._rpn_post_nms_top_n = rpn_post_nms_top_n
# self.score_threshold = 0.05
self.nms_threshold = config.TEST.NMS
self._bbox_pred = nonlinear_pred
base_path = os.path.dirname(__file__)
sym, arg_params, aux_params = mx.model.load_checkpoint(base_path + '/model/e2e', 0)
self.nms = gpu_nms_wrapper(self.nms_threshold, self.ctx_id)
self.pixel_means = np.array([103.939, 116.779, 123.68]) # BGR
if not test_mode:
image_size = (640, 640)
self.model = mx.mod.Module(symbol=sym, context=self.ctx, label_names=None)
self.model.bind(data_shapes=[('data', (1, 3, image_size[0], image_size[1]))], for_training=False)
self.model.set_params(arg_params, aux_params)
else:
from rcnn.core.module import MutableModule
image_size = (640, 640)
data_shape = [('data', (1, 3, image_size[0], image_size[1]))]
self.model = MutableModule(symbol=sym, data_names=['data'], label_names=None,
context=self.ctx, max_data_shapes=data_shape)
self.model.bind(data_shape, None, for_training=False)
self.model.set_params(arg_params, aux_params)
print('init ssh success') 示例2: __init__
# 需要導入模塊: from rcnn.processing import nms [as 別名]
# 或者: from rcnn.processing.nms import gpu_nms_wrapper [as 別名]
def __init__(self, prefix, epoch, ctx_id=0, test_mode=False):
self.ctx_id = ctx_id
self.ctx = mx.gpu(self.ctx_id)
self.fpn_keys = []
fpn_stride = []
fpn_base_size = []
self._feat_stride_fpn = [32, 16, 8]
for s in self._feat_stride_fpn:
self.fpn_keys.append('stride%s'%s)
fpn_stride.append(int(s))
fpn_base_size.append(16)
self._scales = np.array([32,16,8,4,2,1])
self._ratios = np.array([1.0]*len(self._feat_stride_fpn))
#self._anchors_fpn = dict(zip(self.fpn_keys, generate_anchors_fpn(base_size=fpn_base_size, scales=self._scales, ratios=self._ratios)))
self._anchors_fpn = dict(zip(self.fpn_keys, generate_anchors_fpn()))
self._num_anchors = dict(zip(self.fpn_keys, [anchors.shape[0] for anchors in self._anchors_fpn.values()]))
self._rpn_pre_nms_top_n = 1000
#self._rpn_post_nms_top_n = rpn_post_nms_top_n
#self.score_threshold = 0.05
self.nms_threshold = 0.3
self._bbox_pred = nonlinear_pred
sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
self.nms = gpu_nms_wrapper(self.nms_threshold, self.ctx_id)
self.pixel_means = np.array([103.939, 116.779, 123.68]) #BGR
self.pixel_means = config.PIXEL_MEANS
print('means', self.pixel_means)
if not test_mode:
image_size = (640, 640)
self.model = mx.mod.Module(symbol=sym, context=self.ctx, label_names = None)
self.model.bind(data_shapes=[('data', (1, 3, image_size[0], image_size[1]))], for_training=False)
self.model.set_params(arg_params, aux_params)
else:
from rcnn.core.module import MutableModule
image_size = (2400, 2400)
data_shape = [('data', (1,3,image_size[0], image_size[1]))]
self.model = MutableModule(symbol=sym, data_names=['data'], label_names=None,
context=self.ctx, max_data_shapes=data_shape)
self.model.bind(data_shape, None, for_training=False)
self.model.set_params(arg_params, aux_params)