标签：shapelabel img color float 270 180 points path 标注
在制作做遥感图像物体检测数据集的时候，遥感图像的物体都是平面的，有角度的问题，
可以对被检测物体实现不同角度的旋转，丰富数据集同时减少标注的工作量。
比如上图中的飞机，机头的朝向是斜向下的，现实中的飞机可能有各种的朝向，如果不做旋转，就会降低模型的检测能力。下图是旋转90度的效果。
需要安装的包：
labelme
scipy1.0.0版本
pyqt5
旋转最大的难点在于旋转后，需要对标注的点重新计算，保证标注的坐标不出现错乱。
旋转90度后，坐标转化：
points=shapelabel['points']#获取初始的坐标。
newPoints = [[float(points[0][1]), w-float(points[1][0])],
[float(points[1][1]), w-float(points[0][0])]]#旋转90度，重新对应坐标。w表示原始图像的宽度。
选旋转180度后，坐标转化：
points = shapelabel['points']
newPoints = [[w-float(points[1][0]), h - float(points[1][1])],
[w-float(points[0][0]), h - float(points[0][1])]] #旋转180度，重新对应坐标。h表示原始图像的高度。
旋转270度，坐标转化：
points = shapelabel['points']
newPoints = [[h - float(points[1][1]), float(points[0][0])],
[h - float(points[0][1]), float(points[1][0])]]
完整代码如下：
#scipy的版本为1.0.0 import scipy from scipy import misc import os import glob import PIL.Image from labelme.logger import logger from labelme import PY2 from labelme import QT4 import io import json import os.path as osp import PIL.Image from scipy import ndimage import base64 from labelme import utils
def load_image_file(filename):
try:
image_pil = PIL.Image.open(filename)
except IOError:
logger.error('Failed opening image file: {}'.format(filename))
return
# apply orientation to image according to exif
image_pil = utils.apply_exif_orientation(image_pil)
with io.BytesIO() as f:
ext = osp.splitext(filename)[1].lower()
if PY2 and QT4:
format = 'PNG'
elif ext in ['.jpg', '.jpeg']:
format = 'JPEG'
else:
format = 'PNG'
image_pil.save(f, format=format)
f.seek(0)
return f.read()
def dict_json(flags,imageData,shapes,imagePath,fillColor=None,lineColor=None,imageHeight=100,imageWidth=100):
'''
:param imageData: str
:param shapes: list
:param imagePath: str
:param fillColor: list
:param lineColor: list
:return: dict
'''
return {"version":"3.16.4","flags":flags,"shapes":shapes,'lineColor':lineColor,"fillColor":fillColor,'imagePath':imagePath.split('\\')[1],"imageData":imageData,'imageHeight':imageHeight,'imageWidth':imageWidth}
def get_image_paths(folder):
return glob.glob(os.path.join(folder, '*.jpg'))
def create_read_img(filename):
data = json.load(open(filename.split('.')[0]+'.json'))
shapes = data["shapes"]
version = data["version"]
flags = data["flags"]
lineColor = data["lineColor"]
fillColor = data['fillColor']
newshapes = []
im = misc.imread(filename)
h,w,d=im.shape
img_rote_90 = ndimage.rotate(im, 90)
img_path_90=filename[:-4]+'_90.jpg'
scipy.misc.imsave(img_path_90,img_rote_90)
imageData_90 = load_image_file(img_path_90)
imageData_90 = base64.b64encode(imageData_90).decode('utf-8')
imageHeight =w
imageWidth = h
for shapelabel in shapes:
newLabel=shapelabel['label']
newline_color=shapelabel['line_color']
newfill_color=shapelabel['fill_color']
points=shapelabel['points']
newPoints = [[float(points[0][1]), w-float(points[1][0])],
[float(points[1][1]), w-float(points[0][0])]]
newshape_type=shapelabel['shape_type']
newflags=shapelabel['flags']
newshapes.append({'label':newLabel,'line_color':newline_color,'fill_color':newfill_color,'points':newPoints,'shape_type':newshape_type,'flags':newflags})
data_90 = dict_json(flags, imageData_90, newshapes, img_path_90, fillColor, lineColor, imageHeight, imageWidth)
json_file = img_path_90[:-4] + '.json'
json.dump(data_90, open(json_file, 'w'))
img_rote_180 = ndimage.rotate(im, 180)
img_path_180=filename[:-4]+'_180.jpg'
scipy.misc.imsave(img_path_180,img_rote_180)
imageData_180 = load_image_file(img_path_180)
imageData_180 = base64.b64encode(imageData_180).decode('utf-8')
imageHeight = h
imageWidth = w
newshapes = []
for shapelabel in shapes:
newLabel = shapelabel['label']
newline_color = shapelabel['line_color']
newfill_color = shapelabel['fill_color']
points = shapelabel['points']
newPoints = [[w-float(points[1][0]), h - float(points[1][1])],
[w-float(points[0][0]), h - float(points[0][1])]]
newshape_type = shapelabel['shape_type']
newflags = shapelabel['flags']
newshapes.append(
{'label': newLabel, 'line_color': newline_color, 'fill_color': newfill_color, 'points': newPoints,
'shape_type': newshape_type, 'flags': newflags})
data_180 = dict_json(flags, imageData_180, newshapes, img_path_180, fillColor, lineColor, imageHeight, imageWidth)
json_file = img_path_180[:-4] + '.json'
json.dump(data_180, open(json_file, 'w'))
img_rote_270 = ndimage.rotate(im, 270)
img_path_270=filename[:-4]+'_270.jpg'
scipy.misc.imsave(img_path_270,img_rote_270)
imageData_270 = load_image_file(img_path_270)
imageData_270 = base64.b64encode(imageData_270).decode('utf-8')
imageHeight = w
imageWidth = h
newshapes = []
for shapelabel in shapes:
newLabel = shapelabel['label']
newline_color = shapelabel['line_color']
newfill_color = shapelabel['fill_color']
points = shapelabel['points']
newPoints = [[h - float(points[1][1]), float(points[0][0])],
[h - float(points[0][1]), float(points[1][0])]]
newshape_type = shapelabel['shape_type']
newflags = shapelabel['flags']
newshapes.append(
{'label': newLabel, 'line_color': newline_color, 'fill_color': newfill_color, 'points': newPoints,
'shape_type': newshape_type, 'flags': newflags})
data_270 = dict_json(flags, imageData_270, newshapes, img_path_270, fillColor, lineColor, imageHeight, imageWidth)
json_file = img_path_270[:-4] + '.json'
json.dump(data_270, open(json_file, 'w'))
print(filename)
img_path = 'USA' #这个路径是所有图片在的位置
imgs = get_image_paths(img_path)
print (imgs)
for i in imgs:
create_read_img(i)
标签：shapelabel,img,color,float,270,180,points,path,标注 来源： https://blog.51cto.com/u_15194128/2761823
本站声明： 1. iCode9 技术分享网（下文简称本站）提供的所有内容，仅供技术学习、探讨和分享； 2. 关于本站的所有留言、评论、转载及引用，纯属内容发起人的个人观点，与本站观点和立场无关； 3. 关于本站的所有言论和文字，纯属内容发起人的个人观点，与本站观点和立场无关； 4. 本站文章均是网友提供，不完全保证技术分享内容的完整性、准确性、时效性、风险性和版权归属；如您发现该文章侵犯了您的权益，可联系我们第一时间进行删除； 5. 本站为非盈利性的个人网站，所有内容不会用来进行牟利，也不会利用任何形式的广告来间接获益，纯粹是为了广大技术爱好者提供技术内容和技术思想的分享性交流网站。