#合成圖片
import numpy as np
import cv2
channel_1 = cv2.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-1.TIF',cv2.IMREAD_GRAYSCALE)
channel_2 = cv2.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-2.TIF',cv2.IMREAD_GRAYSCALE)
channel_3 = cv2.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-3.TIF',cv2.IMREAD_GRAYSCALE)
channel_4 = cv2.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-4.TIF',cv2.IMREAD_GRAYSCALE)
print('channel1_shape,channel2_shape,channel3_shape,channel4_shape',(channel_1.shape,channel_2.shape,channel_3.shape,channel_4.shape))
channel_1 = channel_1.reshape([channel_1.shape[0],channel_1.shape[1],1])
channel_2 = channel_2.reshape([channel_2.shape[0],channel_2.shape[1],1])
channel_3 = channel_3.reshape([channel_3.shape[0],channel_3.shape[1],1])
channel_4 = channel_4.reshape([channel_4.shape[0],channel_4.shape[1],1])
print('channel1_shape,channel2_shape,channel3_shape,channel4_shape',(channel_1.shape,channel_2.shape,channel_3.shape,channel_4.shape))
total_channel = np.concatenate((channel_3,channel_2,channel_1),axis=2)
image = total_channel[:,:,:]
cv2.imwrite('./pic.png',image)
#使用鼠標採集圖片數據生成.npy文件
import numpy as np
from math import *
import sys
import os
import glob
import argparse
import cv2 as cv
import keras
import random
from matplotlib import pyplot as plt
import pickle
channel_1 = cv.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-1.TIF',cv.IMREAD_GRAYSCALE)
channel_2 = cv.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-2.TIF',cv.IMREAD_GRAYSCALE)
channel_3 = cv.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-3.TIF',cv.IMREAD_GRAYSCALE)
channel_4 = cv.imread('/home/xm/桌面/make_dataset/3201844/HJ1A-CCD1-27-68-20170820-L20003201844-4.TIF',cv.IMREAD_GRAYSCALE)
channel_1 = channel_1.reshape([channel_1.shape[0],channel_1.shape[1],1])
channel_2 = channel_2.reshape([channel_2.shape[0],channel_2.shape[1],1])
channel_3 = channel_3.reshape([channel_3.shape[0],channel_3.shape[1],1])
channel_4 = channel_4.reshape([channel_4.shape[0],channel_4.shape[1],1])
all_channel = np.concatenate((channel_1,channel_2,channel_3,channel_4),axis=2)
image = all_channel[:,:,:]
data = np.zeros([1,28,28,4])
print('image.shap....................................................',image.shape)
def onmouse(event, x, y, flags, param):#鼠標事件響應函數
global drag_start, sel, lab, cloudsets, count,data,filenames,sam
if event == cv.EVENT_LBUTTONDOWN:#左鍵按下時記錄當前初始座標，並初始化矩形sel
drag_start = x, y
sel = 0,0,0,0
sam=0,0,0,0
elif event == cv.EVENT_LBUTTONUP:#鼠標左鍵嘆彈起時響應
if sel[2] > sel[0] and sel[3] > sel[1]:#判斷右下角座標是否大於左上角
mid=int((sel[1]+sel[3])/2),int((sel[0]+sel[2])/2)
sam_0 = mid[0]-28,mid[1]-28,mid[0]+28,mid[1]+28
sam_1=mid[0]-28,mid[1],mid[0],mid[1]+28
sam_2=mid[0]-28,mid[1]-28,mid[0],mid[1]
sam_3=mid[0],mid[1],mid[0]+28,mid[1]+28
sam_4=mid[0],mid[1]-28,mid[0]+28,mid[1]
count+=1
filenames = './others/'+str(count)+'.png'
cv2.imwrite(filenames,image[sam_1[0]:sam_1[2],sam_1[1]:sam_1[3],:])
count+=1
filenames = './others/'+str(count)+'.png'
cv2.imwrite(filenames,image[sam_2[0]:sam_2[2],sam_2[1]:sam_2[3],:])
count+=1
filenames = './others/'+str(count)+'.png'
cv2.imwrite(filenames,image[sam_3[0]:sam_3[2],sam_3[1]:sam_3[3],:])
count+=1
filenames = './others/'+str(count)+'.png'
cv2.imwrite(filenames,image[sam_4[0]:sam_4[2],sam_4[1]:sam_4[3],:])
## patch = gray[sam[0]:sam[2],sam[1]:sam[3]]#取矩形區域內像素作爲patch圖像
patch = []
patch.append(image[sam_1[0]:sam_1[2],sam_1[1]:sam_1[3],:])#取矩形區域內像素作爲patch圖像
patch.append(image[sam_2[0]:sam_2[2],sam_2[1]:sam_2[3],:])#取矩形區域內像素作爲patch圖像
patch.append(image[sam_3[0]:sam_3[2],sam_3[1]:sam_3[3],:])#取矩形區域內像素作爲patch圖像
patch.append(image[sam_4[0]:sam_4[2],sam_4[1]:sam_4[3],:])#取矩形區域內像素作爲patch圖像
#print('patch.shap....................................................',patch.shape)
## target = cv.cvtColor(patch, cv.COLOR_GRAY2BGR)#取矩形區域內原始像素截取圖像
#cloudsets.append([target,int(input('lab:'))])
## features = target.reshape([-1,28,28,4])
patch = np.array(patch)
features = patch.reshape([-1,28,28,4])
## cloudsets.append([features,lab])
## cloudsets.append(features)
data = np.concatenate([data,features],axis=0)
print('data.shape...................................................',data.shape)
print(features.shape,sam,count,lab,sam[0],sam[1],sam[2],sam[3])
## np.save('cloudsets',cloudsets)
np.save('./others.npy',data[1:])
#f = open('/home/xm/桌面/dataset.txt','wb')
#pickle.dump(data[1:],f)
#plt.imsave('sample.jpg',target)
drag_start = None
elif drag_start:
#print flags
if flags & cv.EVENT_FLAG_LBUTTON:#取當前座標與初始座標較小的爲矩形座標左上，較大的爲右下
minpos = min(drag_start[0], x), min(drag_start[1], y)
maxpos = max(drag_start[0], x), max(drag_start[1], y)
sel = minpos[0], minpos[1], maxpos[0], maxpos[1]
img = cv.cvtColor(gray, cv.COLOR_GRAY2BGR)
cv.rectangle(img, (sel[0], sel[1]), (sel[2], sel[3]), (0,255,255), 1)
#print(sel[0],sel[1],sel[2],sel[3])
cv.imshow("gray", img)
else:
print ("selection is complete" )
drag_start = None
drag_start = None#全局變量取方塊鼠標拖拽時使用
sel = (0,0,0,0)#全局變量 長方形左上頜右下定點座標存儲
lab=0
##if os.path.exists('cloudsets.npy'):
## cloudsets=np.load('cloudsets.npy')
## cloudsets=cloudsets.tolist()
##else:
## cloudsets=[]
count=0
#filename = 'HC421.jpg'
filename = './pic.png'
cv.namedWindow("gray",2) # 第二個參數 １窗口固定；２窗口可調整
cv.setMouseCallback("gray", onmouse)
ext = os.path.splitext(filename)[1][1:] #get the filename extenstion
if ext == "png" or ext == "jpg" or ext == "bmp" or ext == "tiff" or ext == "pbm":
print (filename )
img=cv.imread(filename,1)
sel = (0,0,0,0)
drag_start = None
gray=cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow("gray",gray)
cv.waitKey(0)
cv.destroyAllWindows()
