pyramid_network.py 文件源码

def _add_jittered_boxes(rois, scores, batch_inds, gt_boxes, jitter=0.1):
    ws = gt_boxes[:, 2] - gt_boxes[:, 0]
    hs = gt_boxes[:, 3] - gt_boxes[:, 1]
    shape = tf.shape(gt_boxes)[0]
    jitter = tf.random_uniform([shape, 1], minval = -jitter, maxval = jitter)
    jitter = tf.reshape(jitter, [-1])
    ws_offset = ws * jitter
    hs_offset = hs * jitter
    x1s = gt_boxes[:, 0] + ws_offset
    x2s = gt_boxes[:, 2] + ws_offset
    y1s = gt_boxes[:, 1] + hs_offset
    y2s = gt_boxes[:, 3] + hs_offset
    boxes = tf.concat(
            values=[
                x1s[:, tf.newaxis],
                y1s[:, tf.newaxis],
                x2s[:, tf.newaxis],
                y2s[:, tf.newaxis]],
            axis=1)
    new_scores = tf.ones([shape], tf.float32)
    new_batch_inds = tf.zeros([shape], tf.int32)

    return tf.concat(values=[rois, boxes], axis=0), \
           tf.concat(values=[scores, new_scores], axis=0), \
           tf.concat(values=[batch_inds, new_batch_inds], axis=0)