Mask-RCNN之PyramidROIAlign代码赏析

最新推荐文章于 2021-09-23 13:24:07 发布

P0ny

最新推荐文章于 2021-09-23 13:24:07 发布

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分类专栏：深度学习

本文链接：https://blog.youkuaiyun.com/qq_36735489/article/details/93218036


class PyramidROIAlign(KE.Layer):
    """Implements ROI Pooling on multiple levels of the feature pyramid.
    Params:
    - pool_shape: [pool_height, pool_width] of the output pooled regions. Usually [7, 7]

    Inputs:
    - boxes: [batch, num_boxes, (y1, x1, y2, x2)] in normalized coordinates. Possibly padded with zeros if not enough
             boxes to fill the array.
    - image_meta: [batch, (meta data)] Image details. See compose_image_meta()
    - feature_maps: List of feature maps from different levels of the pyramid. Each is [batch, height, width, channels]

    Output:
    Pooled regions in the shape: [batch, num_boxes, pool_height, pool_width, channels].
    The width and height are those specific in the pool_shape in the layer constructor.
    """

    def __init__(self, pool_shape, **kwargs):
        super(PyramidROIAlign, self).__init__(**kwargs)
        self.pool_shape = tuple(pool_shape)

    def call(self, inputs):
        # Crop boxes [batch, num_boxes, (y1, x1, y2, x2)] in normalized coords
        boxes = inputs[0]

        # Image meta
        # Holds details about the image. See compose_image_meta()
        image_meta = inputs[1]

        # Feature Maps. List of feature maps from different level of the
        # feature pyramid. Each is [batch, height, width, channels]
        feature_maps = inputs[2:]

        # Assign each ROI to a level in the pyramid based on the ROI area.
        y1, x1, y2, x2 = tf.split(boxes, 4, axis=2)