class_docstr: The parameteres that define how anchors are generated.
  
  Args
      sizes   : List of sizes to use. Each size corresponds to one feature level.
      strides : List of strides to use. Each stride correspond to one feature level.
      ratios  : List of ratios to use per location in a feature map.
      scales  : List of scales to use per location in a feature map.
class_docstr_tok: ["The","parameteres","that","define","how","anchors","are","generated",".","Args","sizes",":","List","of","sizes","to","use",".","Each","size","corresponds","to","one","feature","level",".","strides",":","List","of","strides","to","use",".","Each","stride","correspond","to","one","feature","level",".","ratios",":","List","of","ratios","to","use","per","location","in","a","feature","map",".","scales",":","List","of","scales","to","use","per","location","in","a","feature","map","."]
code: def __init__(self, sizes, strides, ratios, scales):
      self.sizes = sizes
      self.strides = strides
      self.ratios = ratios
      self.scales = scales
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/utils/anchors.py
imports: import numpy
  from tensorflow import keras
label_desc: Use image node_id 1 to create a new AnchorParameters object  with example: obj = AnchorParameters(sizes, strides, ratios, scales)