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Python common.ORIGINAL_IMAGE屬性代碼示例

本文整理匯總了Python中deeplab.common.ORIGINAL_IMAGE屬性的典型用法代碼示例。如果您正苦於以下問題:Python common.ORIGINAL_IMAGE屬性的具體用法?Python common.ORIGINAL_IMAGE怎麽用?Python common.ORIGINAL_IMAGE使用的例子?那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在deeplab.common的用法示例。


在下文中一共展示了common.ORIGINAL_IMAGE屬性的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: _preprocess_image

# 需要導入模塊: from deeplab import common [as 別名]
# 或者: from deeplab.common import ORIGINAL_IMAGE [as 別名]
def _preprocess_image(self, sample):
    """Preprocesses the image and label.

    Args:
      sample: A sample containing image and label.

    Returns:
      sample: Sample with preprocessed image and label.

    Raises:
      ValueError: Ground truth label not provided during training.
    """
    image = sample[common.IMAGE]
    label = sample[common.LABELS_CLASS]

    original_image, image, label = input_preprocess.preprocess_image_and_label(
        image=image,
        label=label,
        crop_height=self.crop_size[0],
        crop_width=self.crop_size[1],
        min_resize_value=self.min_resize_value,
        max_resize_value=self.max_resize_value,
        resize_factor=self.resize_factor,
        min_scale_factor=self.min_scale_factor,
        max_scale_factor=self.max_scale_factor,
        scale_factor_step_size=self.scale_factor_step_size,
        ignore_label=self.ignore_label,
        is_training=self.is_training,
        model_variant=self.model_variant)

    sample[common.IMAGE] = image

    if not self.is_training:
      # Original image is only used during visualization.
      sample[common.ORIGINAL_IMAGE] = original_image

    if label is not None:
      sample[common.LABEL] = label

    # Remove common.LABEL_CLASS key in the sample since it is only used to
    # derive label and not used in training and evaluation.
    sample.pop(common.LABELS_CLASS, None)

    return sample 
開發者ID:IBM,項目名稱:MAX-Image-Segmenter,代碼行數:46,代碼來源:data_generator.py

示例2: _preprocess_image

# 需要導入模塊: from deeplab import common [as 別名]
# 或者: from deeplab.common import ORIGINAL_IMAGE [as 別名]
def _preprocess_image(self, sample):
    """Preprocesses the image and label.

    Args:
      sample: A sample containing image and label.

    Returns:
      sample: Sample with preprocessed image and label.

    Raises:
      ValueError: Ground truth label not provided during training.
    """
    image = sample[common.IMAGE]
    label = sample[common.LABELS_CLASS]

    # print(self.crop_size)
    original_image, image, label = input_preprocess.preprocess_image_and_label(
        image=image,
        label=label,
        crop_height=self.crop_size[0],
        crop_width=self.crop_size[1],
        min_resize_value=self.min_resize_value,
        max_resize_value=self.max_resize_value,
        resize_factor=self.resize_factor,
        min_scale_factor=self.min_scale_factor,
        max_scale_factor=self.max_scale_factor,
        scale_factor_step_size=self.scale_factor_step_size,
        ignore_label=self.ignore_label,
        is_training=self.is_training,
        model_variant=self.model_variant)

    sample[common.IMAGE] = image

    if not self.is_training:
      # Original image is only used during visualization.
      sample[common.ORIGINAL_IMAGE] = original_image

    if label is not None:
      sample[common.LABEL] = label

    # Remove common.LABEL_CLASS key in the sample since it is only used to
    # derive label and not used in training and evaluation.
    sample.pop(common.LABELS_CLASS, None)

    return sample 
開發者ID:IBM,項目名稱:MAX-Image-Segmenter,代碼行數:47,代碼來源:data_generator.py


注:本文中的deeplab.common.ORIGINAL_IMAGE屬性示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台,相關代碼片段篩選自各路編程大神貢獻的開源項目,源碼版權歸原作者所有,傳播和使用請參考對應項目的License;未經允許,請勿轉載。