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3_find_star.py
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from pickle import TRUE
from turtle import distance
import cv2
from cv2 import waitKey
import numpy as np
import os
from tqdm import tqdm
def txt2array(txt_path, delimiter):
#---
# 功能：读取只包含数字的txt文件，并转化为array形式
# txt_path：txt的路径；delimiter：数据之间的分隔符
#---
data_list = []
with open(txt_path) as f:
data = f.readlines()
for line in data:
line = line.strip("\n") # 去除末尾的换行符
data_split = line.split(delimiter)
temp = list(map(float, data_split))
data_list.append(temp)
data_array = np.array(data_list)
return data_array
def erose_img(img,img_mask,yz,):
original_img=img
# 图形太大，执行缩小操作
kernel=np.ones((5,5),np.uint8)
erosion=cv2.erode(img_mask,kernel)
sp=original_img.shape
# cv2.imshow("src",original_img)
gray1 = cv2.cvtColor(original_img, cv2.COLOR_BGR2GRAY)
gray2 = cv2.cvtColor(erosion, cv2.COLOR_BGR2GRAY)
# cv2.imshow("erosion",erosion)
chazhi=[]
for i in range(sp[0]):
for m in range(sp[1]):
# chazhi[i][m]=0
num1=int(gray1[i][m])
num2=int(gray2[i][m])
if((num1-num2)>yz):
# if(chazhi):
# x1=chazhi[-1][0]
# y1=chazhi[-1][1]
# r=pow(pow(x1-i,2)+pow(y1-m,2),0.5)
# if(r>200):
# chazhi.append([i,m,num1])
# else:
chazhi.append([i,m,num1])
new_list = sorted(chazhi, key = lambda x:x[2],reverse=True)
return new_list
def canny(img):
b, g, r = cv2.split(img)
img2 = cv2.merge([r, g, b])
grayImage = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gaussianBlur = cv2.GaussianBlur(grayImage, (3, 3), 0)
gaussian = cv2.GaussianBlur(grayImage, (5, 5), 0)
Canny = cv2.Canny(gaussian, 50, 150)
sp=grayImage.shape
chazhi=[]
for i in range(sp[0]):
for m in range(sp[1]):
if(Canny[i][m]==255):
# if(chazhi):
# x1=chazhi[-1][0]
# y1=chazhi[-1][1]
# r=pow(pow(x1-i,2)+pow(y1-m,2),0.5)
# if(r>200):
# chazhi.append([i,m,grayImage[i][m]])
# else:
chazhi.append([i,m,grayImage[i][m]])
new_list = sorted(chazhi, key = lambda x:x[2],reverse=True)
return new_list
def chazhi(gray1,gray2,yz):
sp=gray1.shape
chazhi=[]
for i in range(sp[0]):
for m in range(sp[1]):
# chazhi[i][m]=0
num1=int(gray1[i][m])
num2=int(gray2[i][m])
if((num1-num2)>yz):
# if(chazhi):
# x1=chazhi[-1][0]
# y1=chazhi[-1][1]
# r=pow(pow(x1-i,2)+pow(y1-m,2),0.5)
# if(r>200):
# chazhi.append([i,m,num1])
# else:
chazhi.append([i,m,num1])
new_list = sorted(chazhi, key = lambda x:x[2],reverse=True)
return new_list
def yishiying(gray1,keral_size,offset):
img_ret12 = cv2.adaptiveThreshold(gray1, 255, cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,keral_size,offset)
sp=gray1.shape
chazhi=[]
for i in range(sp[0]):
for m in range(sp[1]):
if(img_ret12[i][m]==255):
# if(chazhi):
# x1=chazhi[-1][0]
# y1=chazhi[-1][1]
# r=pow(pow(x1-i,2)+pow(y1-m,2),0.5)
# if(r>200):
# chazhi.append([i,m,gray1[i][m]])
# else:
chazhi.append([i,m,gray1[i][m]])
new_list = sorted(chazhi, key = lambda x:x[2],reverse=True)
return new_list
# file_FOLDER=星轨原图所在地
# pat=图案名称
# yz=canny的阈值，阈值越大，筛选的星星越少
# size_change=图案在照片上的大小，数值越大，大小越小
# method可选四种星星筛选方式，填入对应字符串'jubuyuzhi','chazhi','canny','erose',
# IsJianbian=图案是否以渐变方式出现，填入bool值
def MyStar(file_FOLDER,pat,yz,midu,size_change,method,IsJianbian):
dirs = os.listdir( file_FOLDER )
path_file_FOLDER='path_txt/'+pat+'/'
lujing_dirs=os.listdir(path_file_FOLDER)
epoch=len(lujing_dirs)
size=len(dirs)
num_pic=0
mask_img=cv2.imread(file_FOLDER+'/'+dirs[0])
mask_img=cv2.resize(mask_img,(1920,1080))
for k in tqdm(range(0,size)):
filepath1=file_FOLDER+'/'+dirs[k]
filepath2=file_FOLDER+'/'+dirs[(k+int(size/2))%size]
img1 = cv2.imread(filepath1) #读取图片
img2 = cv2.imread(filepath2) #读取图片
# img1=cv2.resize(img1,(1920,1080))
# img2=cv2.resize(img2,(1920,1080))
gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY) #变为灰度图
gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY) #变为灰度图
sp=gray1.shape
if(method=='chazhi'):
star_pos_img=chazhi(gray1,gray2,yz)
if(method=='canny'):
star_pos_img=canny(img1)
if(method=='erose'):
star_pos_img=erose_img(img1,mask_img,100)
if(method=='jubuyuzhi'):
star_pos_img=yishiying(gray1,9,-25)
# if(num_pic==0):
# cv2.namedWindow(method, 0)
# cv2.resizeWindow(method, sp[0], sp[1]) # 自己设定窗口图片的大小
# cv2.imshow(method, star_pos_img)
# cv2.waitKey(0)
filename='output/'+file_FOLDER[-1]+'_'+pat+'_'+method+'/'
if not os.path.exists(filename):
#如果文件目录不存在则创建目录
os.makedirs(filename)
with open(filename+'pos_info.txt','ab') as f:
np.savetxt(f,star_pos_img[0:20], fmt='%d', delimiter=',',header=dirs[k])
filename=filename+dirs[k]
if(os.path.exists(filename)):
continue
w,h = img1.shape[:-1] #获取长宽
print(w,h)
gray = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY) #变为灰度图
cur_path_file=path_file_FOLDER+lujing_dirs[num_pic%epoch]
cur_path_file=path_file_FOLDER+lujing_dirs[num_pic%epoch]
array = txt2array(cur_path_file,',')
num=len(array)
for point in range(40):#这里的40也可更改，数值越大，图上的星星越多
if(not(IsJianbian)):
i=star_pos_img[point][0]
m=star_pos_img[point][1]
for x in range(0,num,midu):
offset_y=int(array[x][0]*size_change)
offset_x=int(array[x][1]*size_change)
if(i+offset_y<w and i+offset_y>=0 and m+offset_x<h and m+offset_x>=0):
img1[i+offset_y][m+offset_x]=img1[i][m]
else:
i=star_pos_img[point][0]
m=star_pos_img[point][1]
if(num_pic<24):
for x in range(0,int(num*num_pic/24),midu):
offset_y=int(array[x][0]*size_change)
offset_x=int(array[x][1]*size_change)
if(i+offset_y<w and i+offset_y>=0 and m+offset_x<h and m+offset_x>=0):
img1[i+offset_y][m+offset_x]=img1[i][m]
else:
for x in range(0,num,midu):
offset_y=int(array[x][0]*size_change)
offset_x=int(array[x][1]*size_change)
if(i+offset_y<w and i+offset_y>=0 and m+offset_x<h and m+offset_x>=0):
img1[i+offset_y][m+offset_x]=img1[i][m]
if(num_pic==0):
cv2.namedWindow('preview', 0)
cv2.resizeWindow('preview', w, h) # 自己设定窗口图片的大小
cv2.imshow("preview", img1)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.imwrite(filename,img1,[cv2.IMWRITE_JPEG_QUALITY, 100])
num_pic=num_pic+1
file_FOLDER = 'yuantu/4' #！！！文件夹的地址（手动修改）
pat='people'
yz=0
midu=2 # 密度为图案沿线的密度，数值越小，图案路径上的点越多
size_change=1
method='chazhi'
IsJianbian=True
MyStar(file_FOLDER,pat,yz,midu,size_change,method,IsJianbian)