labelme标注后的图片切成小图和小json
splitMission.py和generateLabel.py两个脚本复制到4张图片和json所在的文件夹(最好是4的倍数因为默认以4个线程并行执行)中
python splitMission.py
源码
splitMission.py
点击查看代码
import cv2
import os
import base64
from PIL import Image
import PIL
import io
import json
import numpy as np
from multiprocessing import Pool
from generateLabel import *
import shutil
class imgToSplit():
def __init__(self,imgFile):
self.objName = imgFile.strip('.jpg')
self.img = cv2.imread(imgFile)
self.h,self.w = self.img.shape[:-1]
self.half_h,self.half_w = self.h//2,self.w//2
self.sub_json_list = []
self.disp = np.array([ (0,0) , (self.half_w,0) , (0,self.half_h) , (self.half_w,self.half_h)])
self.category = None #在3rd顺便获得category
print('executing',self.objName)
self.splitImage()
self.gen_4sub_json()
self.justDrawLabel()
self.saveSubJson()
def splitImage(self):
'''1st step ： split origin image into 4 pieces！'''
cv2.imwrite(r'.\target\%s_1.jpg' % self.objName, self.img[:self.half_h, :self.half_w])
cv2.imwrite(r'.\target\%s_2.jpg' % self.objName, self.img[:self.half_h, self.half_w:])
cv2.imwrite(r'.\target\%s_3.jpg' % self.objName, self.img[self.half_h:, :self.half_w])
cv2.imwrite(r'.\target\%s_4.jpg' % self.objName, self.img[self.half_h:, self.half_w:])
def gen_4sub_json(self):
'''2nd step : generate 4 json file to sub image!'''
def apply_exif_orientation(image):
try:
exif = image._getexif()
except AttributeError:
exif = None
if exif is None:
return image
exif = {
PIL.ExifTags.TAGS[k]: v
for k, v in exif.items()
if k in PIL.ExifTags.TAGS
}
orientation = exif.get('Orientation', None)
if orientation == 1:
# do nothing
return image
elif orientation == 2:
# left-to-right mirror
return PIL.ImageOps.mirror(image)
elif orientation == 3:
# rotate 180
return image.transpose(PIL.Image.ROTATE_180)
elif orientation == 4:
# top-to-bottom mirror
return PIL.ImageOps.flip(image)
elif orientation == 5:
# top-to-left mirror
return PIL.ImageOps.mirror(image.transpose(PIL.Image.ROTATE_270))
elif orientation == 6:
# rotate 270
return image.transpose(PIL.Image.ROTATE_270)
elif orientation == 7:
# top-to-right mirror
return PIL.ImageOps.mirror(image.transpose(PIL.Image.ROTATE_90))
elif orientation == 8:
# rotate 90
return image.transpose(PIL.Image.ROTATE_90)
else:
return image
def generateImgData(path):
try:
image_pil = PIL.Image.open(path)
except IOError:
pass
# apply orientation to image according to exif
image_pil = apply_exif_orientation(image_pil)
with io.BytesIO() as f:
image_pil.save(f, format='PNG')
f.seek(0)
raw = f.read()
return base64.b64encode(raw).decode('utf8')
for i in range(1, 5):
content = dict()
imgName = '%s_%i.jpg'%(self.objName,i)
img = cv2.imread(r'.\target\%s' % imgName)
content['version'] = '3.10.0'
content['flags'] = dict()
content['shapes'] = []
content['lineColor'] = [0, 255, 0, 128]
content['fillColor'] = [255, 0, 0, 128]
content['imagePath'] = imgName
content['imageData'] = generateImgData(r'.\target\%s' % imgName)
h, w = img.shape[:-1]
content['imageHeight'] = h
content['imageWidth'] = w
# content = json.dumps(content,indent=4)
# print(content)
# with open(r'.\target\%s' % imgName.replace('jpg', 'json'), 'w') as f:
# json.dump(content, f)
self.sub_json_list.append(content)
def justDrawLabel(self):
'''3rd 将label图片分门别类 画出label'''
with open('%s.json'%self.objName, 'r') as f:
data = json.load(f)
#获取类别
classes = [shape['label'] for shape in data['shapes']]
self.category = tuple(set(classes))
imgData = data['imageData']
img = img_b64_to_arr(imgData)
categories = pointsDivByLabel(data['shapes'])
for cateName, shapes in categories.items():
label_name_to_value = {'_background_': 0}
for shape in sorted(shapes, key=lambda x: x['label']):
label_name = shape['label']
if label_name in label_name_to_value:
label_value = label_name_to_value[label_name]
else:
label_value = len(label_name_to_value)
label_name_to_value[label_name] = label_value
lbl = shapes_to_label(img.shape, shapes, label_name_to_value)
self._mapPiecesToJson(cateName,lbl)
# lblsave(r'.\labelme_temp\%s_label_%s.png' % (self.objName,cateName), lbl)
def _mapPiecesToJson(self,cate,img):
""" 4th 读取label_png图片 分割 并将每块 映射到对应的sub json"""
def generateNewShape(labelName,pointSet):
"""生成新的字典 方便json添加到shapes列表"""
res = dict()
res['label'] = labelName
res['line_color'] = None
res['fill_color'] = None
res['points'] = pointSet
res['shape_type'] = 'polygon'
return res
# img = cv2.imread(r'.\labelme_temp\%s_label_%s.png' % (self.objName,cate),0)
img = np.uint8(img)
#横竖两道杠
img[:, self.half_w - 2: self.half_w + 3] = 0
img[self.half_h - 2:self.half_h + 3, :] = 0
#找到轮廓并拟合
contours, _ = cv2.findContours(img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
aprox = [cv2.approxPolyDP(c, 1, True) for c in contours]
aprox = [a.reshape(-1,2) for a in aprox if len(a)>=3] #过滤掉长度不符合规范的点 并reshape gzj
aprox = [a.reshape(-1, 2) for a in aprox ] #
#aprox = [a for a in aprox if (np.std(a,axis=0) > 2).all() ] #过滤掉 噪声点 （纠结在一团的小块）gzj
for pointSet in aprox:
#任意取出一点 作为判断 在哪个象限标注
judgeX = pointSet[0,0]
judgeY = pointSet[0,1]
if judgeX < self.half_w and judgeY < self.half_h:
order = 0
elif judgeX > self.half_w and judgeY < self.half_h:
order = 1
elif judgeX < self.half_w and judgeY > self.half_h:
order = 2
elif judgeX > self.half_w and judgeY > self.half_h:
order = 3
#减去偏移量
pointSet -= self.disp[order]
#写入json
self.sub_json_list[order]\
['shapes'].append(generateNewShape(cate,pointSet.tolist()))
# os.remove(r'.\labelme_temp\%s_label_%s.png'% (self.objName,cate))
def saveSubJson(self):
'''最后将所有json保存'''
for i in range(1,5):
with open(r'.\target\%s_%i.json' %(self.objName,i), 'w') as f:
json.dump(self.sub_json_list[i-1], f)
def mission(file):
file = file.replace('JPG', 'jpg')
imgToSplit(file)
if __name__ == '__main__':
# mission = imgToSplit('DJI_0301.jpg')
# mission.splitImage()
# mission.gen_4sub_json()
# mission.confirmNewPoints()
# mission.saveSubJson()
#存放目标图片
if not os.path.exists(r'.\target'):
os.mkdir(r'.\target')
imgFiles = [ f for f in os.listdir('.') if 'jpg' in f or 'JPG' in f]
# for file in imgFiles:
# file = file.replace('JPG','jpg')
# imgToSplit(file)
pool = Pool(processes=4)
pool.map(mission,imgFiles)
print('done!')
点击查看代码
import json
import io
import base64
import numpy as np
from PIL import Image
from PIL import ImageDraw
import PIL
import math
import os.path as osp
def label_colormap(N=256):
def bitget(byteval, idx):
return ((byteval & (1 << idx)) != 0)
cmap = np.zeros((N, 3))
for i in range(0, N):
id = i
r, g, b = 0, 0, 0
for j in range(0, 8):
r = np.bitwise_or(r, (bitget(id, 0) << 7 - j))
g = np.bitwise_or(g, (bitget(id, 1) << 7 - j))
b = np.bitwise_or(b, (bitget(id, 2) << 7 - j))
id = (id >> 3)
cmap[i, 0] = r
cmap[i, 1] = g
cmap[i, 2] = b
cmap = cmap.astype(np.float32) / 255
return cmap
def lblsave(filename, lbl):
if osp.splitext(filename)[1] != '.png':
filename += '.png'
# Assume label ranses [-1, 254] for int32,
# and [0, 255] for uint8 as VOC.
if lbl.min() >= -1 and lbl.max() < 255:
lbl_pil = PIL.Image.fromarray(lbl.astype(np.uint8), mode='P')
colormap = label_colormap(255)
lbl_pil.putpalette((colormap * 255).astype(np.uint8).flatten())
lbl_pil.save(filename)
else:
print(
'[%s] Cannot save the pixel-wise class label as PNG, '
'so please use the npy file.' % filename
)
def img_b64_to_arr(img_b64):
f = io.BytesIO()
f.write(base64.b64decode(img_b64))
img_arr = np.array(Image.open(f))
return img_arr
def shape_to_mask(img_shape, points, shape_type=None,
line_width=10, point_size=5):
mask = np.zeros(img_shape[:2], dtype=np.uint8)
mask = Image.fromarray(mask)
draw = ImageDraw.Draw(mask)
xy = [tuple(point) for point in points]
if shape_type == 'circle':
assert len(xy) == 2, 'Shape of shape_type=circle must have 2 points'
(cx, cy), (px, py) = xy
d = math.sqrt((cx - px) ** 2 + (cy - py) ** 2)
draw.ellipse([cx - d, cy - d, cx + d, cy + d], outline=1, fill=1)
elif shape_type == 'rectangle':
assert len(xy) == 2, 'Shape of shape_type=rectangle must have 2 points'
draw.rectangle(xy, outline=1, fill=1)
elif shape_type == 'line':
assert len(xy) == 2, 'Shape of shape_type=line must have 2 points'
draw.line(xy=xy, fill=1, width=line_width)
elif shape_type == 'linestrip':
draw.line(xy=xy, fill=1, width=line_width)
elif shape_type == 'point':
assert len(xy) == 1, 'Shape of shape_type=point must have 1 points'
cx, cy = xy[0]
r = point_size
draw.ellipse([cx - r, cy - r, cx + r, cy + r], outline=1, fill=1)
else:
assert len(xy) > 2, 'Polygon must have points more than 2'
draw.polygon(xy=xy, outline=1, fill=1)
mask = np.array(mask, dtype=bool)
return mask
def shapes_to_label(img_shape, shapes, label_name_to_value, type='class'):
assert type in ['class', 'instance']
cls = np.zeros(img_shape[:2], dtype=np.int32)
if type == 'instance':
ins = np.zeros(img_shape[:2], dtype=np.int32)
instance_names = ['_background_']
for shape in shapes:
points = shape['points']
label = shape['label']
shape_type = shape.get('shape_type', None)
if type == 'class':
cls_name = label
elif type == 'instance':
cls_name = label.split('-')[0]
if label not in instance_names:
instance_names.append(label)
ins_id = len(instance_names) - 1
cls_id = label_name_to_value[cls_name]
mask = shape_to_mask(img_shape[:2], points, shape_type)
cls[mask] = cls_id
if type == 'instance':
ins[mask] = ins_id
if type == 'instance':
return cls, ins
return cls
def pointsDivByLabel(listOfDict):
"""传入data['shapes'] 用label 将各个类分开"""
res = dict()
for shape in listOfDict:
if shape['label'] in res.keys():
res[shape['label']].append(shape)
else:
res[shape['label']] = [shape]
return res
# def justDrawLabel(file):
# obj = file.strip('.json')
#
# with open(file,'r') as f:
# data = json.load(f)
#
# imgData = data['imageData']
#
# img = img_b64_to_arr(imgData)
#
# categories = pointsDivByLabel(data['shapes'])
# for cateName,shapes in categories.items():
# label_name_to_value = {'_background_': 0}
#
# for shape in sorted(shapes, key=lambda x: x['label']):
# label_name = shape['label']
# if label_name in label_name_to_value:
# label_value = label_name_to_value[label_name]
# else:
# label_value = len(label_name_to_value)
# label_name_to_value[label_name] = label_value
#
# lbl = shapes_to_label(img.shape, shapes, label_name_to_value)
# lblsave('label_%s.png'%cateName, lbl)
if __name__ == '__main__':
# justDrawLabel('test4.json')
pass
