hashing.py

# from compiler.ast import flatten
import sys
from PIL import Image
import numpy as np
import scipy.fftpack

import cv2

import collections
def flatten(x):
    result = []
    for el in x:
        if isinstance(x, collections.Iterable) and not isinstance(el, str):
            result.extend(flatten(el))
        else:
            result.append(el)
    return result




def dhash(image, hashSize=8):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    resized = cv2.resize(gray, (hashSize + 1, hashSize))
    diff = resized[:, 1:] > resized[:, :-1]
    return sum([2 ** i for (i, v) in enumerate(diff.flatten()) if v])

def convert_hash(h):
    #将哈希值转换为 numpy 的 64-bit 浮点数；
    #然后再转换为 int 格式.
    return int(np.array(h, dtype="float64"))

def hamming(a, b):
    #计算 Hamming 距离
    return bin(int(a) ^ int(b)).count("1")

def binary_array_to_hex(arr):
    bit_string = ''.join(str(b) for b in 1 * arr.flatten())
    width = int(np.ceil(len(bit_string)/4))
    return '{:0>{width}x}'.format(int(bit_string, 2), width=width)



def pHash(img):
    # 感知哈希算法
    # 缩放32*32
    img = cv2.resize(img, (32, 32))  # , interpolation=cv2.INTER_CUBIC

    # 转换为灰度图
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # 将灰度图转为浮点型，再进行dct变换
    dct = cv2.dct(np.float32(gray))
    # opencv实现的掩码操作
    dct_roi = dct[0:8, 0:8]

    hash = []
    avreage = np.mean(dct_roi)
    for i in range(dct_roi.shape[0]):
        for j in range(dct_roi.shape[1]):
            if dct_roi[i, j] > avreage:
                hash.append(1)
            else:
                hash.append(0)
    return sum([2 ** i for (i, v) in enumerate(hash) if v])


def aHash(img):
    # 均值哈希算法
    # 缩放为8*8
    img = cv2.resize(img, (8, 8))
    # 转换为灰度图
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # s为像素和初值为0，hash_str为hash值初值为''
    s = 0
    hash = []
    # 遍历累加求像素和
    for i in range(8):
        for j in range(8):
            s = s+gray[i, j]
    # 求平均灰度
    avg = s/64
    # 灰度大于平均值为1相反为0生成图片的hash值
    for i in range(8):
        for j in range(8):
            if gray[i, j] > avg:
                hash.append(1)
            else:
                hash.append(0)
    return sum([2 ** i for (i, v) in enumerate(hash) if v])