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Source code for mmcv.arraymisc.quantization

# Copyright (c) OpenMMLab. All rights reserved.
from typing import Union

import numpy as np


[docs]def quantize(arr: np.ndarray, min_val: Union[int, float], max_val: Union[int, float], levels: int, dtype=np.int64) -> tuple: """Quantize an array of (-inf, inf) to [0, levels-1]. Args: arr (ndarray): Input array. min_val (int or float): Minimum value to be clipped. max_val (int or float): Maximum value to be clipped. levels (int): Quantization levels. dtype (np.type): The type of the quantized array. Returns: tuple: Quantized array. """ if not (isinstance(levels, int) and levels > 1): raise ValueError( f'levels must be a positive integer, but got {levels}') if min_val >= max_val: raise ValueError( f'min_val ({min_val}) must be smaller than max_val ({max_val})') arr = np.clip(arr, min_val, max_val) - min_val quantized_arr = np.minimum( np.floor(levels * arr / (max_val - min_val)).astype(dtype), levels - 1) return quantized_arr
[docs]def dequantize(arr: np.ndarray, min_val: Union[int, float], max_val: Union[int, float], levels: int, dtype=np.float64) -> tuple: """Dequantize an array. Args: arr (ndarray): Input array. min_val (int or float): Minimum value to be clipped. max_val (int or float): Maximum value to be clipped. levels (int): Quantization levels. dtype (np.type): The type of the dequantized array. Returns: tuple: Dequantized array. """ if not (isinstance(levels, int) and levels > 1): raise ValueError( f'levels must be a positive integer, but got {levels}') if min_val >= max_val: raise ValueError( f'min_val ({min_val}) must be smaller than max_val ({max_val})') dequantized_arr = (arr + 0.5).astype(dtype) * (max_val - min_val) / levels + min_val return dequantized_arr