Spaces:
Running
Running
File size: 3,717 Bytes
d5d20be |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
"""
有一些png图像下部也会有一些透明的区域，使得图像无法对其底部边框
本程序实现移动图像，使其下部与png图像实际大小相对齐
"""
import os
import cv2
import numpy as np
from ..utils import get_box_pro
path_pre = os.path.join(os.getcwd(), 'pre')
path_final = os.path.join(os.getcwd(), 'final')
def merge(boxes):
"""
生成的边框可能不止只有一个，需要将边框合并
"""
x, y, h, w = boxes[0]
# x和y应该是整个boxes里面最小的值
if len(boxes) > 1:
for tmp in boxes:
x_tmp, y_tmp, h_tmp, w_tmp = tmp
if x > x_tmp:
x_max = x_tmp + w_tmp if x_tmp + w_tmp > x + w else x + w
x = x_tmp
w = x_max - x
if y > y_tmp:
y_max = y_tmp + h_tmp if y_tmp + h_tmp > y + h else y + h
y = y_tmp
h = y_max - y
return tuple((x, y, h, w))
def get_box(png_img):
"""
获取矩形边框最终返回一个元组(x,y,h,w)，分别对应矩形左上角的坐标和矩形的高和宽
"""
r, g, b , a = cv2.split(png_img)
gray_img = a
th, binary = cv2.threshold(gray_img, 127 , 255, cv2.THRESH_BINARY) # 二值化
# cv2.imshow("name", binary)
# cv2.waitKey(0)
contours, hierarchy = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # 得到轮廓列表contours
bounding_boxes = merge([cv2.boundingRect(cnt) for cnt in contours]) # 轮廓合并
# print(bounding_boxes)
return bounding_boxes
def get_box_2(png_img):
"""
不用opencv内置算法生成矩形了，改用自己的算法（for循环）
"""
_, _, _, a = cv2.split(png_img)
_, a = cv2.threshold(a, 127, 255, cv2.THRESH_BINARY)
# 将r，g，b通道丢弃，只留下透明度通道
# cv2.imshow("name", a)
# cv2.waitKey(0)
# 在透明度矩阵中，0代表完全透明
height,width=a.shape # 高和宽
f=0
tmp1 = 0
"""
获取上下
"""
for tmp1 in range(0,height):
tmp_a_high= a[tmp1:tmp1+1,:][0]
for tmp2 in range(width):
# a = tmp_a_low[tmp2]
if tmp_a_high[tmp2]!=0:
f=1
if f == 1:
break
delta_y_high = tmp1 + 1
f = 0
for tmp1 in range(height,-1, -1):
tmp_a_low= a[tmp1-1:tmp1+1,:][0]
for tmp2 in range(width):
# a = tmp_a_low[tmp2]
if tmp_a_low[tmp2]!=0:
f=1
if f == 1:
break
delta_y_bottom = height - tmp1 + 3
"""
获取左右
"""
f = 0
for tmp1 in range(width):
tmp_a_left = a[:, tmp1:tmp1+1]
for tmp2 in range(height):
if tmp_a_left[tmp2] != 0:
f = 1
if f==1:
break
delta_x_left = tmp1 + 1
f = 0
for tmp1 in range(width, -1, -1):
tmp_a_left = a[:, tmp1-1:tmp1]
for tmp2 in range(height):
if tmp_a_left[tmp2] != 0:
f = 1
if f==1:
break
delta_x_right = width - tmp1 + 1
return delta_y_high, delta_y_bottom, delta_x_left, delta_x_right
def move(input_image):
"""
裁剪主函数，输入一张png图像，该图像周围是透明的
"""
png_img = input_image # 获取图像
height, width, channels = png_img.shape # 高y、宽x
y_low,y_high, _, _ = get_box_pro(png_img, model=2) # for循环
base = np.zeros((y_high, width, channels),dtype=np.uint8) # for循环
png_img = png_img[0:height - y_high, :, :] # for循环
png_img = np.concatenate((base, png_img), axis=0)
return png_img
if __name__ == "__main__":
pass
|