HivisionIDPhotos / hivision /creator /layout_calculator.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
r"""
@DATE: 2024/9/5 21:35
@File: layout_calculator.py
@IDE: pycharm
@Description:
布局计算器
"""
import cv2.detail
import numpy as np
def judge_layout(
input_width,
input_height,
PHOTO_INTERVAL_W,
PHOTO_INTERVAL_H,
LIMIT_BLOCK_W,
LIMIT_BLOCK_H,
):
centerBlockHeight_1, centerBlockWidth_1 = (
input_height,
input_width,
) # 由证件照们组成的一个中心区块(1 代表不转置排列)
centerBlockHeight_2, centerBlockWidth_2 = (
input_width,
input_height,
) # 由证件照们组成的一个中心区块(2 代表转置排列)
# 1.不转置排列的情况下:
layout_col_no_transpose = 0 # 行
layout_row_no_transpose = 0 # 列
for i in range(1, 4):
centerBlockHeight_temp = input_height * i + PHOTO_INTERVAL_H * (i - 1)
if centerBlockHeight_temp < LIMIT_BLOCK_H:
centerBlockHeight_1 = centerBlockHeight_temp
layout_row_no_transpose = i
else:
break
for j in range(1, 9):
centerBlockWidth_temp = input_width * j + PHOTO_INTERVAL_W * (j - 1)
if centerBlockWidth_temp < LIMIT_BLOCK_W:
centerBlockWidth_1 = centerBlockWidth_temp
layout_col_no_transpose = j
else:
break
layout_number_no_transpose = layout_row_no_transpose * layout_col_no_transpose
# 2.转置排列的情况下:
layout_col_transpose = 0 # 行
layout_row_transpose = 0 # 列
for i in range(1, 4):
centerBlockHeight_temp = input_width * i + PHOTO_INTERVAL_H * (i - 1)
if centerBlockHeight_temp < LIMIT_BLOCK_H:
centerBlockHeight_2 = centerBlockHeight_temp
layout_row_transpose = i
else:
break
for j in range(1, 9):
centerBlockWidth_temp = input_height * j + PHOTO_INTERVAL_W * (j - 1)
if centerBlockWidth_temp < LIMIT_BLOCK_W:
centerBlockWidth_2 = centerBlockWidth_temp
layout_col_transpose = j
else:
break
layout_number_transpose = layout_row_transpose * layout_col_transpose
if layout_number_transpose > layout_number_no_transpose:
layout_mode = (layout_col_transpose, layout_row_transpose, 2)
return layout_mode, centerBlockWidth_2, centerBlockHeight_2
else:
layout_mode = (layout_col_no_transpose, layout_row_no_transpose, 1)
return layout_mode, centerBlockWidth_1, centerBlockHeight_1
def generate_layout_photo(input_height, input_width):
# 1.基础参数表
LAYOUT_WIDTH = 1746
LAYOUT_HEIGHT = 1180
PHOTO_INTERVAL_H = 30 # 证件照与证件照之间的垂直距离
PHOTO_INTERVAL_W = 30 # 证件照与证件照之间的水平距离
SIDES_INTERVAL_H = 50 # 证件照与画布边缘的垂直距离
SIDES_INTERVAL_W = 70 # 证件照与画布边缘的水平距离
LIMIT_BLOCK_W = LAYOUT_WIDTH - 2 * SIDES_INTERVAL_W
LIMIT_BLOCK_H = LAYOUT_HEIGHT - 2 * SIDES_INTERVAL_H
# 2.创建一个 1180x1746 的空白画布
white_background = np.zeros([LAYOUT_HEIGHT, LAYOUT_WIDTH, 3], np.uint8)
white_background.fill(255)
# 3.计算照片的 layout(列、行、横竖朝向),证件照组成的中心区块的分辨率
layout_mode, centerBlockWidth, centerBlockHeight = judge_layout(
input_width,
input_height,
PHOTO_INTERVAL_W,
PHOTO_INTERVAL_H,
LIMIT_BLOCK_W,
LIMIT_BLOCK_H,
)
# 4.开始排列组合
x11 = (LAYOUT_WIDTH - centerBlockWidth) // 2
y11 = (LAYOUT_HEIGHT - centerBlockHeight) // 2
typography_arr = []
typography_rotate = False
if layout_mode[2] == 2:
input_height, input_width = input_width, input_height
typography_rotate = True
for j in range(layout_mode[1]):
for i in range(layout_mode[0]):
xi = x11 + i * input_width + i * PHOTO_INTERVAL_W
yi = y11 + j * input_height + j * PHOTO_INTERVAL_H
typography_arr.append([xi, yi])
return typography_arr, typography_rotate
def generate_layout_image(
input_image, typography_arr, typography_rotate, width=295, height=413
):
LAYOUT_WIDTH = 1746
LAYOUT_HEIGHT = 1180
white_background = np.zeros([LAYOUT_HEIGHT, LAYOUT_WIDTH, 3], np.uint8)
white_background.fill(255)
if input_image.shape[0] != height:
input_image = cv2.resize(input_image, (width, height))
if typography_rotate:
input_image = cv2.transpose(input_image)
height, width = width, height
for arr in typography_arr:
locate_x, locate_y = arr[0], arr[1]
white_background[locate_y : locate_y + height, locate_x : locate_x + width] = (
input_image
)
return white_background