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paste.py
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import os
import cv2
import numpy as np
from until import until
import shutil
class Paste():
def __init__(self, datasetRoot, cropRoot, outputRoot, imgNum, pasteNum=1, pasteRadio=1.0, imgExe='.png',
imgSize=None, cropSizes=None, cropClasses=None, showRect=False, randomResizeRatioRange=None, opts=None):
if imgSize is None:
imgSize = [416, 416]
if randomResizeRatioRange is None:
randomResizeRatioRange = [1, 1]
if opts is None:
opts = ['train']
self.datasetRoot = datasetRoot
self.cropRoot = cropRoot
self.outputRoot = outputRoot
if (os.path.exists(self.outputRoot)):
shutil.rmtree(self.outputRoot)
os.makedirs(self.outputRoot + '/images')
os.makedirs(self.outputRoot + '/labels')
self.imgNum = imgNum
self.pasteNum = pasteNum # 如果这个值不为1，那么pasteRadio必须为1.0
self.pasteRadio = pasteRadio # 这个值只有pasteNum=1时才使用
self.imgExe = imgExe
self.imgSize = imgSize
self.cropSizes = cropSizes
self.cropClasses = cropClasses
self.showRect = showRect
self.randomResizeRatioRange = randomResizeRatioRange
self.opts = opts
self.curOpt = opts[0]
def pasteCropsOnImg(self, img, labels, cropImgs, CropImgsLabels):
imgW = img.shape[1]
imgH = img.shape[0]
hasPaste = False
for i in range(len(cropImgs)):
cropImg = cropImgs[i]
cropImgLabels = CropImgsLabels[i]
allowPatse = True
for cropImgLabel in cropImgLabels:
radio = min(self.imgSize[0] / imgW, self.imgSize[1] / imgH)
labelW = (int(cropImgLabel[6]) - int(cropImgLabel[4])) * radio
labelH = (int(cropImgLabel[7]) - int(cropImgLabel[5])) * radio
labelWH = int(labelW * labelH)
incropSizes = False
for cropSize in self.cropSizes: # 尺寸过滤得在实际知道目标要粘贴到哪张图中才能知道要不要过滤。因为同样的原始目标，在不同图缩小到416时尺寸不同
if (cropSize[0] * cropSize[0] <= labelWH and labelWH <= cropSize[1] * cropSize[1]):
incropSizes = True
break
if (incropSizes == False):
allowPatse = False
break
if(allowPatse == False): # 一张cropImg中有一个标签不符合尺寸过滤器，就不能粘贴
continue
hasPaste = True # 判断是否有cropImg最终能粘贴到原图中
cropImgW = cropImg.shape[1]
cropImgH = cropImg.shape[0]
trying = True
tryNum = 10
[pasteXmin, pasteYmin, pasteXmax, pasteYmax] = [0, 0 ,0 ,0]
while(trying and tryNum > 0):
tryNum -= 1
[ramdomXmin, ramdomXmax, ramdomYmin, ramdomYmax] = [cropImgW // 2 + 1, imgW - cropImgW // 2 -1, cropImgH // 2 + 1, imgH - cropImgH // 2 -1]
if(ramdomXmin >= ramdomXmax or ramdomYmin >= ramdomYmax):
break
[xc, yc] = [np.random.randint(ramdomXmin, ramdomXmax), np.random.randint(ramdomYmin, ramdomYmax)]
overlap = False
pasteXmin = xc - cropImgW // 2
pasteYmin = yc - cropImgH // 2
pasteXmax = xc + cropImgW // 2
pasteYmax = yc + cropImgH // 2
for label in labels:
if(until.mat_inter( label[4:8], [pasteXmin, pasteYmin, pasteXmax, pasteYmax] ) ):
overlap = True
break
if(overlap == False):
trying = False
if(trying == True):
return img, None
img[pasteYmin:pasteYmax, pasteXmin:pasteXmax] = cropImg
for cropImgLabel in cropImgLabels:
appendArr = [labels[0][0], labels[0][1], labels[0][2], cropImgLabel[3], pasteXmin + cropImgLabel[4], pasteYmin + cropImgLabel[5], pasteXmin + cropImgLabel[6], pasteYmin + cropImgLabel[7]]
# radio = min(self.imgSize[0] / imgW, self.imgSize[1] / imgH)
# print((appendArr[6] - appendArr[4]) * (appendArr[7] - appendArr[5]) * radio * radio)
labels.append(appendArr)
if(hasPaste == False):
return img, None
return img, labels
def createCropImgsAndImgsLabels(self, initCropIdx):
cropImgsLen = len(self.files)
pasteCropInfo = initCropIdx
newCropImgsLabels = []
newCropImgs = []
resIdx = 0
for pasteCount in range(self.pasteNum):
file = self.files[pasteCropInfo]
newCropImgsLabels.append([])
cropInfo = file.strip().split('.')[0]
cropImg = cv2.imread(
self.cropRoot + '/images/' + self.curOpt + '/' + cropInfo + self.imgExe) # 需要粘贴的裁剪图片
cropImgH = cropImg.shape[0]
cropImgW = cropImg.shape[1]
cropLabelsStr = open(self.cropRoot + '/labels/' + self.curOpt + '/' + cropInfo + '.txt',
'r').readlines()
randomResizeRatio = np.random.uniform(self.randomResizeRatioRange[0],
self.randomResizeRatioRange[1])
newCropImgH = int(cropImgH * randomResizeRatio) // 2 * 2
newCropImgW = int(cropImgW * randomResizeRatio) // 2 * 2
newCropImgWH = newCropImgW * newCropImgH
# allowPatse = False
# for cropSize in self.cropSizes:
# if(cropSize[0]*cropSize[0] <= newCropImgWH and newCropImgWH <= cropSize[1]*cropSize[1]):
# allowPatse = True
# break
# if(allowPatse == False):
# continue
newCropImg = cv2.resize(cropImg, (newCropImgW, newCropImgH))
newCropImgs.append(newCropImg)
hasObjNotInObjsizes = False
for i in range(len(cropLabelsStr)):
label = cropLabelsStr[i]
items = label.strip().split(' ')
objClass = items[3]
if(int(objClass) not in self.cropClasses):
hasObjNotInObjsizes = True
xmin = int(float(items[4]) * randomResizeRatio)
ymin = int(float(items[5]) * randomResizeRatio)
xmax = int(float(items[6]) * randomResizeRatio)
ymax = int(float(items[7]) * randomResizeRatio)
newCropImgsLabels[resIdx].append(
[cropInfo, newCropImgW, newCropImgH, objClass, xmin, ymin, xmax, ymax])
if(hasObjNotInObjsizes):
break
if(hasObjNotInObjsizes == True):
newCropImgs.pop()
newCropImgsLabels.pop()
else:
resIdx += 1
pasteCropInfo = np.random.randint(0, cropImgsLen) # 随机找另一种裁剪图
return newCropImgs, newCropImgsLabels
def randomPaste(self):
for opt in self.opts:
self.curOpt = opt
os.makedirs(self.outputRoot + '/images/' + self.curOpt + '/')
os.makedirs(self.outputRoot + '/labels/' + self.curOpt + '/')
self.files = os.listdir(self.cropRoot + '/labels/' + self.curOpt + '/')
cropImgsLen = len(self.files) # 裁剪出来的图片的数目
randomArr = np.random.randint(self.imgNum, size=cropImgsLen)
for idx in range(int(cropImgsLen * self.pasteRadio)):
# if(idx != 328):
# continue
print(idx)
cropInfo = self.files[idx].strip().split('.')[0]
# 处理粘贴图片信息
newCropImgs, newCropImgsLabels = self.createCropImgsAndImgsLabels(idx)
if(len(newCropImgs) == 0):
continue
tryPaste = True
info = ''
img = None
labels = None
imgW = imgH = 0
tryNum = 0
while (tryPaste and tryNum < 10):
tryNum += 1
info = str(randomArr[idx]).zfill(5)
# print(info)
# 处理被粘贴图片信息
img = cv2.imread(self.datasetRoot + '/images/' + self.curOpt + '/' + info + self.imgExe) # 被处理的原始图片
imgH = img.shape[0]
imgW = img.shape[1]
if not os.path.exists(self.datasetRoot + '/labels/' + self.curOpt + '/' + info + '.txt'):
break
labelsStr = open(self.datasetRoot + '/labels/' + self.curOpt + '/' + info + '.txt', 'r').readlines()
labels = []
for i in range(len(labelsStr)):
label = labelsStr[i]
items = label.strip().split(' ')
objClass = items[3]
xmin = int(items[4])
ymin = int(items[5])
xmax = int(items[6])
ymax = int(items[7])
labels.append([info, imgW, imgH, objClass, xmin, ymin, xmax, ymax])
img, labels = self.pasteCropsOnImg(img, labels, newCropImgs, newCropImgsLabels)
if (labels != None):
tryPaste = False
else:
randomArr[idx] = np.random.randint(0, self.imgNum)
if (tryPaste):
continue
fOut = open(self.outputRoot + '/labels/' + self.curOpt + '/' + cropInfo + '_' + info + '.txt', 'w')
for label in labels:
if(self.showRect):
cv2.rectangle(img, (label[4], label[5]), (label[6], label[7]), (255, 0, 0))
fOut.write(
cropInfo + '_' + info + ' ' + str(imgW) + ' ' + str(imgH) + ' ' + str(label[3]) + ' ' + str(
label[4]) + ' ' + str(label[5]) + ' ' + str(label[6]) + ' ' + str(label[7]) + '\n')
# cv2.imshow('aa', img)
cv2.imwrite(self.outputRoot + '/images/' + self.curOpt + '/' + cropInfo + '_' + info + self.imgExe, img)
if __name__ == '__main__':
datasetRoot = '../CTSDB_jing/'
cropRoot = './CTSDB_jing/objCrop/padding/0.5'
outputRoot = './CTSDB_jing/imgPaste/cropSizes/16_64'
imgNum = 700
randomResizeRatioRange = [0.5, 1]
cropSizes = [[16, 64]]
cropClasses = [0, 1, 2]
imgExe = '.png'
paste = Paste(datasetRoot, cropRoot, outputRoot, imgNum, imgExe=imgExe,pasteNum=1, pasteRadio=1, cropSizes=cropSizes, cropClasses=cropClasses, showRect=False, randomResizeRatioRange=randomResizeRatioRange)
paste.randomPaste()