DOTAv1.5データセットは固定サイズ(1000*1000)にカットされ、ラベルデータは自動的に対応する映像に取り込まれる.
DOTAv1.5データセットは固定サイズ(1000*1000)にカットされ、ラベルデータは自動的に対応する映像に取り込まれる. 1.データセット映像は1000*1000 にカット 2.ラベルデータ自動キャプチャ 3.txt回転xml(VOC 07形式) 1.データセット映像を1000*1000にカット
1000未満の高さまたは幅は、ラベルデータの原点が左上角であるため、下または右方向に揃える(左上隅は動かない).pyコードは次のとおりです.
2.ラベルデータ自動取り込み
txttq.pyコードは次のとおりです.
3.txt回転xml(VOC 07形式)
1000未満の高さまたは幅は、ラベルデータの原点が左上角であるため、下または右方向に揃える(左上隅は動かない).pyコードは次のとおりです.
# -*- coding: utf-8 -*-
import cv2
import os
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
def tianchong_you(img):
size = img.shape
#if size[0]>=1000 and size[1]<1000:
constant = cv2.copyMakeBorder(img,0,0,0,1000-size[1],cv2.BORDER_CONSTANT,value=(107,113,115))#
#else:
# print(' ')
# return 0
return constant
def tianchong_xia(img):
size = img.shape
# if size[0]<1000 and size[1]>=1000:
constant = cv2.copyMakeBorder(img,0,1000-size[0],0,0,cv2.BORDER_CONSTANT,value=(107,113,115))
#else:
# print(' ')
# return 0
return constant
def tianchong_xy(img):
size = img.shape
#if size[0]<1000 and size[1]<1000:
constant = cv2.copyMakeBorder(img,0,1000-size[0],0,1000-size[1],cv2.BORDER_CONSTANT,value=(107,113,115))
#else:
# print(' ')
# return 0
return constant
def caijian(path,path_out,size_w=1000,size_h=1000,step=800):# 200
ims_list=os.listdir(path)
#print(ims_list)
count = 0
for im_list in ims_list:
number = 0
name = im_list[:-5]# “.tiff ”
print(name)
img = cv2.imread(ims_path+im_list)
size = img.shape
if size[0]>=1000 and size[1]>=1000:
count = count + 1
for h in range(0,size[0]-1,step):
star_h = h
for w in range(0,size[1]-1,step):
star_w = w
end_h = star_h + size_h
if end_h > size[0]:
star_h = size[0] - size_h
end_h = star_h + size_h
end_w = star_w + size_w
if end_w > size[1]:
star_w = size[1] - size_w
end_w = star_w + size_w
cropped = img[star_h:end_h, star_w:end_w]
name_img = name + '_'+ str(star_h) +'_' + str(star_w)# ，
cv2.imwrite('{}/{}.tiff'.format(path_out,name_img),cropped)
number = number + 1
if size[0]>=1000 and size[1]<1000:
print(' {} '.format(name))
count = count + 1
img0 = tianchong_you(img)
for h in range(0,size[0]-1,step):
star_h = h
star_w = 0
end_h = star_h + size_h
if end_h > size[0]:
star_h = size[0] - size_h
end_h = star_h + size_h
end_w = star_w + size_w
cropped = img0[star_h:end_h, star_w:end_w]
name_img = name + '_'+ str(star_h) +'_' + str(star_w)
cv2.imwrite('{}/{}.tiff'.format(path_out,name_img),cropped)
number = number + 1
if size[0]<1000 and size[1]>=1000:
count = count + 1
print(' {} '.format(name))
img0 = tianchong_xia(img)
for w in range(0,size[1]-1,step):
star_h = 0
star_w = w
end_w = star_w + size_w
if end_w > size[1]:
star_w = size[1] - size_w
end_w = star_w + size_w
end_h = star_h + size_h
cropped = img0[star_h:end_h, star_w:end_w]
name_img = name + '_'+ str(star_h) +'_' + str(star_w)
cv2.imwrite('{}/{}.tiff'.format(path_out,name_img),cropped)
number = number + 1
if size[0]<1000 and size[1]<1000:
count = count + 1
print(' {} '.format(name))
img0 = tianchong_xy(img)
cropped = img0[0:1000, 0:1000]
name_img = name + '_'+ '0' +'_' + '0'
cv2.imwrite('{}/{}.tiff'.format(path_out,name_img),cropped)
number = number + 1
print(' {} {} '.format(name,number))
print(' {} '.format(count))
if __name__ == '__main__':
ims_path='/home/***/data/VOCdevkit/mydataset/shiyan/yuantu/'#
# txt_path = '/home/***/data/VOCdevkit/mydataset/Annotations/txt/'
path = '/home/***/data/VOCdevkit/mydataset/shiyan/shuchu/' #
caijian(ims_path,path,size_w=1000,size_h=1000,step=800)
2.ラベルデータ自動取り込み
txttq.pyコードは次のとおりです.
# -*- coding: utf-8 -*-
import cv2
import os
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
category_set = ['backgroud','plane','small-vehicle','large-vehicle']
def tqtxt(path,path_txt,path_out,size_h=1000,size_w=1000):
ims_list=os.listdir(path)
for im_list in ims_list:
name_list = []
name = im_list[:-5]
name_list = name.split('_')
if len(name_list)<2:
continue
h = int(name_list[1])
w = int(name_list[2])
txtpath = path_txt + name_list[0] + '.txt'
txt_outpath = path_out + name + '.txt'
f = open(txt_outpath,'a')
with open(txtpath, 'r') as f_in: # txt
i = 0
lines = f_in.readlines()
#print(len(lines))
#splitlines = [x.strip().split(' ') for x in lines] #
for line in lines:
if i in [0,1]:
f.write(line)#txt
i = i+1
continue
splitline = line.split(' ')
label = splitline[8]
kunnan = splitline[9]
if label not in category_set:#
continue
x1 = int(float(splitline[0]))
y1 = int(float(splitline[1]))
x2 = int(float(splitline[2]))
y2 = int(float(splitline[3]))
x3 = int(float(splitline[4]))
y3 = int(float(splitline[5]))
x4 = int(float(splitline[6]))
y4 = int(float(splitline[7]))
if w<=x1<=w+size_w and w<=x2<=w+size_w and w<=x3<=w+size_w and w<=x4<=w+size_w and h<=y1<=h+size_h and h<=y2<=h+size_h and h<=y3<=h+size_h and h<=y4<=h+size_h:
f.write('{} {} {} {} {} {} {} {} {} {}'.format(float(x1-w),float(y1-h),float(x2-w),float(y2-h),float(x3-w),float(y3-h),float(x4-w),float(y4-h),label,kunnan))
f.close()
if __name__ == '__main__':
ims_path='/home/***/data/VOCdevkit/mydataset/JPEGImages/'#
txt_path = '/home/***/data/VOCdevkit/mydataset/Annotations/txt/'#
path = '/home/***/data/VOCdevkit/mydataset/Annotations/txt_out/'#
tqtxt(ims_path,txt_path,path,size_h=1000,size_w=1000)
3.txt回転xml(VOC 07形式)
# -*- coding:UTF-8 -*-
import os
import cv2
from xml.dom.minidom import Document
import sys
stdi, stdo, stde = sys.stdin, sys.stdout, sys.stderr
reload(sys)
sys.setdefaultencoding('utf-8')
sys.stdin, sys.stdout, sys.stderr = stdi, stdo, stde
category_set = ['backgroud','plane','small-vehicle','large-vehicle']
def custombasename(fullname):
return os.path.basename(os.path.splitext(fullname)[0])
def limit_value(a,b):
if a<1:
a = 1
if a>=b:
a = b-1
return a
def readlabeltxt(txtpath, height, width, hbb = True):
print(txtpath)
with open(txtpath, 'r') as f_in: # txt
lines = f_in.readlines()
splitlines = [x.strip().split(' ') for x in lines] #
boxes = []
for i, splitline in enumerate(splitlines):
if i in [0,1]: #DOTA
continue
label = splitline[8]
kunnan = splitline[9]
if label not in category_set:#
print(label)
continue
x1 = int(float(splitline[0]))
y1 = int(float(splitline[1]))
x2 = int(float(splitline[2]))
y2 = int(float(splitline[3]))
x3 = int(float(splitline[4]))
y3 = int(float(splitline[5]))
x4 = int(float(splitline[6]))
y4 = int(float(splitline[7]))
# hbb
if hbb:
xx1 = min(x1,x2,x3,x4)
xx2 = max(x1,x2,x3,x4)
yy1 = min(y1,y2,y3,y4)
yy2 = max(y1,y2,y3,y4)
xx1 = limit_value(xx1, width)
xx2 = limit_value(xx2, width)
yy1 = limit_value(yy1, height)
yy2 = limit_value(yy2, height)
box = [xx1,yy1,xx2,yy2,label,kunnan]
boxes.append(box)
else: # obb
x1 = limit_value(x1, width)
y1 = limit_value(y1, height)
x2 = limit_value(x2, width)
y2 = limit_value(y2, height)
x3 = limit_value(x3, width)
y3 = limit_value(y3, height)
x4 = limit_value(x4, width)
y4 = limit_value(y4, height)
box = [x1,y1,x2,y2,x3,y3,x4,y4,label]
boxes.append(box)
return boxes
def writeXml(tmp, imgname, w, h, d, bboxes, hbb = True):
doc = Document()
#owner
annotation = doc.createElement('annotation')
doc.appendChild(annotation)
#owner
folder = doc.createElement('folder')
annotation.appendChild(folder)
folder_txt = doc.createTextNode("VOC2007")
folder.appendChild(folder_txt)
filename = doc.createElement('filename')
annotation.appendChild(filename)
filename_txt = doc.createTextNode(imgname)
filename.appendChild(filename_txt)
#ones#
source = doc.createElement('source')
annotation.appendChild(source)
database = doc.createElement('database')
source.appendChild(database)
database_txt = doc.createTextNode("My Database")
database.appendChild(database_txt)
annotation_new = doc.createElement('annotation')
source.appendChild(annotation_new)
annotation_new_txt = doc.createTextNode("VOC2007")
annotation_new.appendChild(annotation_new_txt)
image = doc.createElement('image')
source.appendChild(image)
image_txt = doc.createTextNode("flickr")
image.appendChild(image_txt)
#owner
owner = doc.createElement('owner')
annotation.appendChild(owner)
flickrid = doc.createElement('flickrid')
owner.appendChild(flickrid)
flickrid_txt = doc.createTextNode("NULL")
flickrid.appendChild(flickrid_txt)
ow_name = doc.createElement('name')
owner.appendChild(ow_name)
ow_name_txt = doc.createTextNode("idannel")
ow_name.appendChild(ow_name_txt)
#onee#
#twos#
size = doc.createElement('size')
annotation.appendChild(size)
width = doc.createElement('width')
size.appendChild(width)
width_txt = doc.createTextNode(str(w))
width.appendChild(width_txt)
height = doc.createElement('height')
size.appendChild(height)
height_txt = doc.createTextNode(str(h))
height.appendChild(height_txt)
depth = doc.createElement('depth')
size.appendChild(depth)
depth_txt = doc.createTextNode(str(d))
depth.appendChild(depth_txt)
#twoe#
segmented = doc.createElement('segmented')
annotation.appendChild(segmented)
segmented_txt = doc.createTextNode("0")
segmented.appendChild(segmented_txt)
for bbox in bboxes:
#threes#
object_new = doc.createElement("object")
annotation.appendChild(object_new)
name = doc.createElement('name')
object_new.appendChild(name)
name_txt = doc.createTextNode(str(bbox[-2]))
name.appendChild(name_txt)
pose = doc.createElement('pose')
object_new.appendChild(pose)
pose_txt = doc.createTextNode("Unspecified")
pose.appendChild(pose_txt)
truncated = doc.createElement('truncated')
object_new.appendChild(truncated)
truncated_txt = doc.createTextNode("0")
truncated.appendChild(truncated_txt)
difficult = doc.createElement('difficult')
object_new.appendChild(difficult)
difficult_txt = doc.createTextNode(bbox[-1])
difficult.appendChild(difficult_txt)
#threes-1#
bndbox = doc.createElement('bndbox')
object_new.appendChild(bndbox)
if hbb:
xmin = doc.createElement('xmin')
bndbox.appendChild(xmin)
xmin_txt = doc.createTextNode(str(bbox[0]))
xmin.appendChild(xmin_txt)
ymin = doc.createElement('ymin')
bndbox.appendChild(ymin)
ymin_txt = doc.createTextNode(str(bbox[1]))
ymin.appendChild(ymin_txt)
xmax = doc.createElement('xmax')
bndbox.appendChild(xmax)
xmax_txt = doc.createTextNode(str(bbox[2]))
xmax.appendChild(xmax_txt)
ymax = doc.createElement('ymax')
bndbox.appendChild(ymax)
ymax_txt = doc.createTextNode(str(bbox[3]))
ymax.appendChild(ymax_txt)
else:
x0 = doc.createElement('x0')
bndbox.appendChild(x0)
x0_txt = doc.createTextNode(str(bbox[0]))
x0.appendChild(x0_txt)
y0 = doc.createElement('y0')
bndbox.appendChild(y0)
y0_txt = doc.createTextNode(str(bbox[1]))
y0.appendChild(y0_txt)
x1 = doc.createElement('x1')
bndbox.appendChild(x1)
x1_txt = doc.createTextNode(str(bbox[2]))
x1.appendChild(x1_txt)
y1 = doc.createElement('y1')
bndbox.appendChild(y1)
y1_txt = doc.createTextNode(str(bbox[3]))
y1.appendChild(y1_txt)
x2 = doc.createElement('x2')
bndbox.appendChild(x2)
x2_txt = doc.createTextNode(str(bbox[4]))
x2.appendChild(x2_txt)
y2 = doc.createElement('y2')
bndbox.appendChild(y2)
y2_txt = doc.createTextNode(str(bbox[5]))
y2.appendChild(y2_txt)
x3 = doc.createElement('x3')
bndbox.appendChild(x3)
x3_txt = doc.createTextNode(str(bbox[6]))
x3.appendChild(x3_txt)
y3 = doc.createElement('y3')
bndbox.appendChild(y3)
y3_txt = doc.createTextNode(str(bbox[7]))
y3.appendChild(y3_txt)
xmlname = os.path.splitext(imgname)[0]
tempfile = os.path.join(tmp ,xmlname+'.xml')
with open(tempfile, 'wb') as f:
f.write(doc.toprettyxml(indent='\t', encoding='utf-8'))
return
if __name__ == '__main__':
data_path = '/home/***/data/VOCdevkit/mydataset/JPEGImages'
images_path = os.path.join(data_path) #
labeltxt_path = os.path.join('/home/***/data/VOCdevkit/mydataset/Annotations/txt_out') #DOTA
anno_new_path = os.path.join('/home/***/data/VOCdevkit/mydataset/Annotations/xml_out') # voc （hbb ）
ext = '.tiff' #
filenames=os.listdir(labeltxt_path) # txt
for filename in filenames:
filepath=labeltxt_path + '/'+filename # DOTA
picname = os.path.splitext(filename)[0] + ext
pic_path = os.path.join(images_path, picname)
im= cv2.imread(pic_path) #
(H,W,D) = im.shape #
boxes = readlabeltxt(filepath, H, W, hbb = True) # （hbb） gt
if len(boxes)==0:
print(' ',filepath)
# ， H,W,D xml
# xml
writeXml(anno_new_path, picname, W, H, D, boxes, hbb = True)
print(' %s'%filename)