Python rpn.assign_anchor方法代码示例

本文整理汇总了Python中rpn.rpn.assign_anchor方法的典型用法代码示例。如果您正苦于以下问题：Python rpn.assign_anchor方法的具体用法？Python rpn.assign_anchor怎么用？Python rpn.assign_anchor使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类rpn.rpn的用法示例。

在下文中一共展示了rpn.assign_anchor方法的10个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]

        # assign anchor for label
        label = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                              self.feat_stride, self.anchor_scales,
                              self.anchor_ratios, self.allowed_border)
        return {'data': data, 'label': label}

开发者ID:i-pan，项目名称:kaggle-rsna18，代码行数:18，代码来源:loader.py

示例2: infer_shape

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def infer_shape(self, max_data_shape=None, max_label_shape=None):
        """ Return maximum data and label shape for single gpu """
        if max_data_shape is None:
            max_data_shape = []
        if max_label_shape is None:
            max_label_shape = []
        max_shapes = dict(max_data_shape + max_label_shape)
        input_batch_size = max_shapes['data'][0]
        im_info = [[max_shapes['data'][2], max_shapes['data'][3], 1.0]]
        _, feat_shape, _ = self.feat_sym.infer_shape(**max_shapes)
        label = assign_anchor(feat_shape[0], np.zeros((0, 5)), im_info, self.cfg,
                              self.feat_stride, self.anchor_scales, self.anchor_ratios, self.allowed_border,
                              self.normalize_target, self.bbox_mean, self.bbox_std)
        label = [label[k] for k in self.label_name]
        label_shape = [(k, tuple([input_batch_size] + list(v.shape[1:]))) for k, v in zip(self.label_name, label)]
        return max_data_shape, label_shape

开发者ID:wangshy31，项目名称:MANet_for_Video_Object_Detection，代码行数:18，代码来源:loader.py

示例3: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_triple_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]
        data['occluded'] = label['occluded']
        data['delta_bef_gt'] = label['delta_bef_gt']
        data['delta_aft_gt'] = label['delta_aft_gt']
        # assign anchor for label
        label = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                              self.feat_stride, self.anchor_scales,
                              self.anchor_ratios, self.allowed_border,
                              self.normalize_target, self.bbox_mean, self.bbox_std)
        #print '###################################begin parfetch##########################'
        #print 'data[gt_boxes]', data['gt_boxes']
        #print 'data[delta_bef]', data['delta_bef']
        #print 'data[delta_aft]', data['delta_aft']
        return {'data': data, 'label': label}

开发者ID:wangshy31，项目名称:MANet_for_Video_Object_Detection，代码行数:25，代码来源:loader.py

示例4: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_pair_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]

        # assign anchor for label
        label = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                              self.feat_stride, self.anchor_scales,
                              self.anchor_ratios, self.allowed_border,
                              self.normalize_target, self.bbox_mean, self.bbox_std)
        return {'data': data, 'label': label}

开发者ID:msracver，项目名称:Deep-Feature-Flow，代码行数:19，代码来源:loader.py

示例5: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_triple_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]

        # assign anchor for label
        label = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                              self.feat_stride, self.anchor_scales,
                              self.anchor_ratios, self.allowed_border,
                              self.normalize_target, self.bbox_mean, self.bbox_std)
        return {'data': data, 'label': label}

开发者ID:msracver，项目名称:Flow-Guided-Feature-Aggregation，代码行数:19，代码来源:loader.py

示例6: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]

        # assign anchor for label
        label = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                              self.feat_stride, self.anchor_scales,
                              self.anchor_ratios, self.allowed_border,
                              self.normalize_target, self.bbox_mean, self.bbox_std)
        return {'data': data, 'label': label}

开发者ID:SamvitJ，项目名称:Accel，代码行数:19，代码来源:loader.py

示例7: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]

        # assign anchor for label
        label = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                              self.feat_stride, self.anchor_scales,
                              self.anchor_ratios, self.allowed_border)
        return {'data': data, 'label': label}

# TODO test this dataloader for quadrangle

开发者ID:jessemelpolio，项目名称:Faster_RCNN_for_DOTA，代码行数:20，代码来源:loader.py

示例8: infer_shape

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def infer_shape(self, max_data_shape=None, max_label_shape=None):
        """ Return maximum data and label shape for single gpu """
        if max_data_shape is None:
            max_data_shape = []
        if max_label_shape is None:
            max_label_shape = []
        max_shapes = dict(max_data_shape + max_label_shape)
        input_batch_size = max_shapes['data'][0]
        im_info = [[max_shapes['data'][2], max_shapes['data'][3], 1.0]]
        feat_shape = max_shapes['data']
        H = int(np.ceil(feat_shape[2] * 1.0 / self.feat_stride))
        W = int(np.ceil(feat_shape[3] * 1.0 / self.feat_stride))
        _, feat_shape, _ = self.feat_sym.infer_shape(**max_shapes)

        label = assign_anchor(feat_shape[0], np.zeros((0, 5)), im_info, self.cfg,
                              self.feat_stride, self.anchor_scales, self.anchor_ratios, self.allowed_border,
                              self.normalize_target, self.bbox_mean, self.bbox_std)

        label = [label[k] for k in self.label_name]
        label_shape = [(k, tuple([input_batch_size] + list(v.shape[1:]))) for k, v in zip(self.label_name, label)]
        return max_data_shape, label_shape

开发者ID:happywu，项目名称:Sequence-Level-Semantics-Aggregation，代码行数:23，代码来源:loader.py

示例9: parfetch

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def parfetch(self, iroidb):
        # get testing data for multigpu
        data, label = get_rpn_triple_batch(iroidb, self.cfg)
        data_shape = {k: v.shape for k, v in data.items()}
        del data_shape['im_info']
        _, feat_shape, _ = self.feat_sym.infer_shape(**data_shape)
        feat_shape = [int(i) for i in feat_shape[0]]

        # add gt_boxes to data for e2e
        data['gt_boxes'] = label['gt_boxes'][np.newaxis, :, :]

        # assign anchor for label
        label_f = assign_anchor(feat_shape, label['gt_boxes'], data['im_info'], self.cfg,
                                self.feat_stride, self.anchor_scales,
                                self.anchor_ratios, self.allowed_border,
                                self.normalize_target, self.bbox_mean, self.bbox_std)

        return {'data': data, 'label': label_f}

开发者ID:happywu，项目名称:Sequence-Level-Semantics-Aggregation，代码行数:20，代码来源:loader.py

示例10: infer_shape

# 需要导入模块: from rpn import rpn [as 别名]
# 或者: from rpn.rpn import assign_anchor [as 别名]
def infer_shape(self, max_data_shape=None, max_label_shape=None):
        """ Return maximum data and label shape for single gpu """
        if max_data_shape is None:
            max_data_shape = []
        if max_label_shape is None:
            max_label_shape = []
        max_shapes = dict(max_data_shape + max_label_shape)
        input_batch_size = max_shapes['data'][0]
        im_info = [[max_shapes['data'][2], max_shapes['data'][3], 1.0]]
        _, feat_shape, _ = self.feat_sym.infer_shape(**max_shapes)
        label = assign_anchor(feat_shape[0], np.zeros((0, 5)), im_info, self.cfg,
                              self.feat_stride, self.anchor_scales, self.anchor_ratios, self.allowed_border)
        label = [label[k] for k in self.label_name]
        label_shape = [(k, tuple([input_batch_size] + list(v.shape[1:]))) for k, v in zip(self.label_name, label)]
        return max_data_shape, label_shape

开发者ID:i-pan，项目名称:kaggle-rsna18，代码行数:17，代码来源:loader.py

注：本文中的rpn.rpn.assign_anchor方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。