def singleFile(filePath):
if os.path.isfile(filePath) and filePath.endswith('.json'):
data = json.load(open(filePath))
img = lUtils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = lUtils.labelme_shapes_to_label(
img.shape, data['shapes'])
# lbl[lbl>0] = 255
# print(lbl)
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = lUtils.draw_label(lbl, img, captions)
out_dir = osp.basename(filePath).replace('.', '_')
out_dir = osp.join(osp.dirname(filePath), out_dir)
if not osp.exists(out_dir):
os.mkdir(out_dir)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
print(np.max(lbl))
lbl = np.array(lbl, dtype=np.uint8)
lbl[lbl > 0] = 255
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label_255.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir)
def main():
'''
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
args = parser.parse_args()
'''
json_file = '/Users/nainggolan/Documents/dataset/te/1.json'
out_dir = osp.basename(json_file).replace('.', '_')
out_dir = osp.join(osp.dirname(json_file), out_dir)
os.mkdir(out_dir)
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
lbl_viz = utils.draw_label(lbl, img, lbl_names)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('wrote data to %s' % out_dir)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
parser.add_argument('-o', '--out', default=None)
args = parser.parse_args()
json_file = args.json_file
list = os.listdir(json_file)
for i in range(0, len(list)):
path = os.path.join(json_file, list[i])
if os.path.isfile(path):
data = json.load(open(path))
img = utils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name) for l, name in enumerate(lbl_names)
]
lbl_viz = utils.draw_label(lbl, img, captions)
out_dir = osp.basename(list[i]).replace('.', '_')
out_dir = osp.join(osp.dirname(list[i]), out_dir)
if not osp.exists(out_dir):
os.mkdir(out_dir)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
utils.lblsave(osp.join(out_dir, 'label.png'), lbl)
PIL.Image.fromarray(lbl_viz).save(
osp.join(out_dir, 'label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir)
def main():
'''
parser = argparse.ArgumentParser()
parser.add_argument()
args = parser.parse_args()
'''
json_file = '/Users/nainggolan/Desktop/te/1.json'
data = json.load(open(json_file)) # 加载json文件
img = utils.img_b64_to_array(data['imageData']) # 解析原图片数据
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes']
) # 解析'shapes'中的字段信息，解析出每个对象的mask与对应的label lbl存储 mask，lbl_names 存储对应的label
# lal 像素取值 0、1、2 其中0对应背景，1对应第一个对象，2对应第二个对象
# 使用该方法取出每个对象的mask mask=[] mask.append((lbl==1).astype(np.uint8)) # 解析出像素值为1的对象，对应第一个对象 mask 为0、1组成的（0为背景，1为对象）
# lbl_names ['background','cat_1','cat_2']
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
plt.subplot(121)
plt.imshow(img)
plt.subplot(122)
plt.imshow(lbl_viz)
plt.show()
def changeToDataset(json_dir, out_dir=None):
# parser = argparse.ArgumentParser()
# parser.add_argument('json_file')
# parser.add_argument('-o', '--out', default=None)
# args = parser.parse_args()
for fileName in os.listdir(json_dir):
if re.match(".*[.]json$", fileName):
json_file = osp.join(json_dir, fileName)
print json_file
if out_dir is None:
out_dir = osp.join(osp.dirname(json_file), "output")
# else:
# print 'Existed out_dir = ',out_dir
if not osp.exists(out_dir):
os.mkdir(out_dir)
out_dir_label = os.path.join(out_dir, 'label')
if not osp.exists(out_dir_label):
os.mkdir(out_dir_label)
out_dir_viz = os.path.join(out_dir, 'viz')
if not osp.exists(out_dir_viz):
os.mkdir(out_dir_viz)
print "out_dir_label = ", out_dir_label
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
#print 0: background 1: sto
# for l, name in enumerate(lbl_names):
# print '%d: %s' % (l, name)
captions = [
'%d: %s' % (l, name) for l, name in enumerate(lbl_names)
]
lbl_viz = utils.draw_label(lbl, img, captions)
#New Name
NewName = fileName.split('.')[0]
print osp.join(out_dir, NewName + '.png')
# PIL.Image.fromarray(img).save(osp.join(out_dir,NewName+ '_img.png'))
PIL.Image.fromarray(lbl).save(
osp.join(out_dir_label, NewName + '.png'))
PIL.Image.fromarray(lbl_viz).save(
osp.join(out_dir_viz, NewName + '_label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
# warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
def main():
json_file = 'C:/Users/QJ/Desktop/hh/total'
list = os.listdir(json_file)
for i in range(0, len(list)):
path = os.path.join(json_file, list[i])
if os.path.isfile(path):
data = json.load(open(path))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name) for l, name in enumerate(lbl_names)
]
lbl_viz = utils.draw_label(lbl, img, captions)
out_dir = osp.basename(list[i]).replace('.', '_')
out_dir = osp.join(osp.dirname(list[i]), out_dir)
out_dir = json_file + "/" + out_dir
if not osp.exists(out_dir):
os.mkdir(out_dir)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
# PIL.Image.fromarray(lbl).save()
labelpath = osp.join(out_dir, 'label.png')
# PIL.Image.fromarray(lbl).save(labelpath)
# opencvimg16 = cv2.imread(labelpath)
# opencvimg.convertTo(opencvimg6,)
lbl8u = np.zeros((lbl.shape[0], lbl.shape[1]), dtype=np.uint8)
for i in range(lbl.shape[0]):
for j in range(lbl.shape[1]):
lbl8u[i, j] = lbl[i, j]
PIL.Image.fromarray(lbl8u).save(labelpath)
# Alllabelpath="%s"
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.dump(info, f, default_flow_style=False)
fov = open(osp.join(out_dir, 'info.yaml'), 'w')
for key in info:
fov.writelines(key)
fov.write(':\n')
for k, v in lbl_names.items():
fov.write(' ')
fov.write(k)
fov.write(':\n')
fov.close()
print('Saved to: %s' % out_dir)
def changeToDataset(json_dir,out_dir=None):
# parser = argparse.ArgumentParser()
# parser.add_argument('json_file')
# parser.add_argument('-o', '--out', default=None)
# args = parser.parse_args()
for fileName in os.listdir(json_dir):
if re.match(".*[.]json$",fileName):
json_file = osp.join(json_dir,fileName)
print json_file
if out_dir is None:
out_dir = osp.join(osp.dirname(json_file), "output")
# else:
# print 'Existed out_dir = ',out_dir
if not osp.exists(out_dir):
os.mkdir(out_dir)
out_dir_label = os.path.join(out_dir, 'label')
if not osp.exists(out_dir_label):
os.mkdir(out_dir_label)
out_dir_viz = os.path.join(out_dir,'viz')
if not osp.exists(out_dir_viz):
os.mkdir(out_dir_viz)
print "out_dir_label = ",out_dir_label
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
#print 0: background 1: sto
# for l, name in enumerate(lbl_names):
# print '%d: %s' % (l, name)
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
#New Name
NewName = fileName.split('.')[0]
print osp.join(out_dir,NewName+ '.png')
# PIL.Image.fromarray(img).save(osp.join(out_dir,NewName+ '_img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir_label, NewName+ '.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir_viz, NewName+ '_label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
# warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
def json_to_dataset(json_file_path):
out_dir = osp.basename(json_file_path).replace('.', '_')
out_dir = osp.join(osp.dirname(json_file_path), out_dir)
if not osp.exists(out_dir): os.mkdir(out_dir)
data = json.load(open(json_file_path))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
lbl_viz = utils.draw_label(lbl, img, lbl_names)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('wrote data to %s' % out_dir)
def get_label(img, data_line, data_plane):
"""Gets parallel lines and vertical planes from label json."""
## get parallel lines
# print(data_line['shapes'])
line2points = defaultdict(list) # store 2 points on each parallel line
line_names = [
"XZ_line",
"YZ_line",
"XY_line",
"XZ_line'",
"YZ_line'",
"XY_line'",
]
intersect = [] # common point of plane intersection line
for each_shape in data_line['shapes']:
for each_line in line_names:
if each_shape['label'] == each_line:
# print(each_shape['points'])
# print([list(reversed(each_shape['points'][0])), list(reversed(each_shape['points'][1]))])
line2points[each_line].append([
list(reversed(each_shape['points'][0])),
list(reversed(each_shape['points'][1]))
])
elif each_shape[
'label'] == "intersection": # common point of plane intersection line
intersect = list(reversed(each_shape['points'][0])) + [1]
# print(line2points)
## get vertical planes
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape,
data_plane['shapes'])
# lbl：binary array in: 1 out: 0
# lbl_names ：dict _background_：0 other labels: positive
# print(lbl_names)
mask = [] # for 3 verticle planes
for i in range(1, len(lbl_names)): # ignore background
mask.append((lbl == i).astype(np.uint8))
# captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
# lbl_viz = utils.draw_label(lbl, img, captions)
# plt.imshow(lbl_viz)
# plt.show()
return line2points, intersect, mask
def main():
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
args = parser.parse_args()
json_file = args.json_file
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
# lbl_names[0] 默认为背景，对应的像素值为0
# 解析图片中的对象 像素值不为0（0 对应背景）
mask = []
class_id = []
for i in range(1, len(lbl_names)): # 跳过第一个class（默认为背景）
mask.append((lbl == i).astype(
np.uint8)) # 解析出像素值为1的对应，对应第一个对象 mask 为0、1组成的（0为背景，1为对象）
class_id.append(i) # mask与clas 一一对应
mask = np.transpose(np.asarray(mask, np.uint8),
[1, 2, 0]) # 转成[h,w,instance count]
class_id = np.asarray(class_id, np.uint8) # [instance count,]
class_name = lbl_names[1:] # 不需要包含背景 lbl_names[0] 默认为背景
plt.subplot(221)
plt.imshow(img)
plt.axis('off')
plt.subplot(222)
plt.imshow(lbl_viz)
plt.axis('off')
plt.subplot(223)
plt.imshow(mask[:, :, 0], 'gray')
plt.title(class_name[0] + '\n id ' + str(class_id[0]))
plt.axis('off')
plt.subplot(224)
plt.imshow(mask[:, :, 1], 'gray')
plt.title(class_name[1] + '\n id ' + str(class_id[1]))
plt.axis('off')
plt.show()
def main():
# parser = argparse.ArgumentParser()
# parser.add_argument('json_file')
# args = parser.parse_args()
#
# json_file = args.json_file
# json_file=r"C:\Users\Administrator\Desktop\windows_v1.5.1\data\WIN_20180504_10_05_03_Pro.json"
json_file = r"C:\Users\Administrator\Desktop\windows_v1.5.1\data\img00000001.json"
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
lbl_viz = utils.draw_label(lbl, img, lbl_names)
plt.imshow(lbl_viz)
plt.show()
def process(json_file, out_dir):
"""
将label_me的数据转换为mask灰度图
:param json_file: label_me生成的json文件目录
:param out_dir:转换后png文件的目录
:return:暂无
"""
# 获取json文件列表(用glob直接会拿到绝对路径，不好取文件名字)
json_file_list = os.listdir(json_file)
for i in range(0, len(json_file_list)):
# 获取每个json文件的绝对路径
path = os.path.join(json_file, json_file_list[i])
# 提取出.json前的字符作为文件名，以便后续保存Label图片的时候使用
filename = json_file_list[i][:-5]
# 拿到后缀
extension = json_file_list[i][-4:]
# 只要json文件
if extension == 'json':
if os.path.isfile(path):
data = json.load(open(path))
# 根据'imageData'字段的字符可以得到原图像
img = image.img_b64_to_arr(data['imageData'])
# data['shapes']是json文件中记录着标注的位置及label等信息的字段
lbl, lbl_names = labelme_shapes_to_label(
img.shape, data['shapes'])
mask = []
class_id = []
# 跳过第一个class（因为0默认为背景,跳过不取！）
for cls in range(1, len(lbl_names)):
# mask与class_id 对应记录保存
# 举例：当解析出像素值为1，此时对应第一个mask 为0、1组成的（0为背景，1为对象）
mask.append((lbl == cls).astype(np.uint8))
class_id.append(cls)
mask = np.transpose(np.asarray(mask, np.uint8), [1, 2, 0])
if not osp.exists(out_dir):
os.mkdir(out_dir)
cv2.imwrite(osp.join(out_dir, '{}.png'.format(filename)),
mask[:, :, 0])
def main():
warnings.warn("This script is aimed to demonstrate how to convert the\n"
"JSON file to a single image dataset, and not to handle\n"
"multiple JSON files to generate a real-use dataset.")
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
parser.add_argument('-o', '--out', default=None)
args = parser.parse_args()
json_file = args.json_file
if args.out is None:
out_dir = osp.basename(json_file).replace('.', '_')
out_dir = osp.join(osp.dirname(json_file), out_dir)
else:
out_dir = args.out
if not osp.exists(out_dir):
os.mkdir(out_dir)
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir)
def read_mask(file_name, save_fold):
json_file = file_name
data = json.load(open(json_file))
img = utils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes']) # lbl：array 0、1 （区域内的为1，之外为0）
# lbl_names ：dict _background_ ：0 label_wyk:1
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
#lbl_viz = utils.draw_label(lbl, img, captions)
mask = []
class_id = []
for i in range(1, len(lbl_names)): #若有多个class（物体） 跳过第一个class（默认为背景）
mask.append((lbl == i).astype(
np.uint8)) # 解析出像素值为1的对应，对应第一个对象 mask 为0、1组成的（0为背景，1为对象）
class_id.append(i) # mask与clas 一一对应
mask = np.transpose(np.asarray(mask, np.uint8),
[1, 2, 0]) # 转成[h,w,instance count]
class_id = np.asarray(class_id, np.uint8) # [instance count,]
# plt.subplot(221)
# plt.imshow(img)
# plt.title("original image")
# plt.axis('off')
# plt.subplot(222)
# plt.imshow(lbl_viz)
# plt.axis('off')
# plt.subplot(222)
# plt.imshow(mask[:,:,0],'gray')
mask2 = np.ones_like(img)
for i in range(mask2.shape[2]):
mask2[:, :, i] = mask.squeeze()
# plt.subplot(224)
plt.imshow(mask2 * img)
plt.axis('off')
plt.savefig(os.path.join(save_fold, file_name.replace('json', 'jpg')),
bbox_inches='tight',
pad_inches=0.0)
def main():
warnings.warn("This script is aimed to demonstrate how to convert the\n"
"JSON file to a single image dataset, and not to handle\n"
"multiple JSON files to generate a real-use dataset.")
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
parser.add_argument('-o', '--out', default=None)
args = parser.parse_args()
json_file = args.json_file
if args.out is None:
out_dir = osp.basename(json_file).replace('.', '_')
out_dir = osp.join(osp.dirname(json_file), out_dir)
else:
out_dir = args.out
if not osp.exists(out_dir):
os.mkdir(out_dir)
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
args = parser.parse_args()
json_file = args.json_file
data = json.load(open(json_file))
img = utils.img_b64_to_array(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape, data['shapes'])
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
plt.subplot(121)
plt.imshow(img)
plt.subplot(122)
plt.imshow(lbl_viz)
plt.show()
def get_all_class_mask(json_file_path):
'''
returns:
img: 原图
mask: 所有类别的mask,二值图，0和255
img_with_label: 带掩模的图
lbl_value_to_names: mask的index可以从lbl_value_to_names得到class名称
'''
if os.path.exists(json_file_path):
with open(json_file_path) as json_f:
data = json.load(json_f)
img = utils.img_b64_to_arr(data['imageData'])
#lbl是一个mask，每个obj的像素赋值为该obj对应的value
lbl, lbl_names_to_value = utils.labelme_shapes_to_label(
img.shape, data['shapes']) #包含背景0
captions = [
'%d: %s' % (l, name)
for l, name in enumerate(lbl_names_to_value)
]
img_with_label = utils.draw_label(lbl, img, captions)
tmp = [(l - 1, name) for l, name in enumerate(lbl_names_to_value)
if l != 0]
lbl_value_to_names = {}
for l, name in tmp:
lbl_value_to_names[l] = name #不包含背景
mask = []
# instance_id=[]
for i in range(1, len(lbl_names_to_value)): # 跳过第一个class（默认为背景）
mask.append(
(lbl == i).astype(np.uint8) * 255
) # mask[i]对应第i个对象的mask， 为0、255组成的（0为背景，255为对象）,所有对象的mask叠起来组成三维
# instance_id.append(i) # mask与clas 一一对应
# all_mask=np.transpose(np.asarray(mask,np.uint8),[1,2,0]) # 转成[h,w,instance count]
# instance_id=np.asarray(instance_id,np.uint8) # [instance count,]
else:
raise Exception("no such a json file!!")
return img, mask, img_with_label, lbl_value_to_names
def main():
warnings.warn("This script is aimed to demonstrate how to convert the\n"
"JSON file to a single image dataset, and not to handle\n"
"multiple JSON files to generate a real-use dataset.")
parser = argparse.ArgumentParser()
parser.add_argument('json_file')
parser.add_argument('-o', '--out', default=None)
args = parser.parse_args()
json_file = args.json_file
#freedom
list_path = os.listdir(json_file)
print('freedom =', json_file)
for i in range(0, len(list_path)):
path = os.path.join(json_file, list_path[i])
if os.path.isfile(path):
data = json.load(open(path))
img = utils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name) for l, name in enumerate(lbl_names)
]
lbl_viz = utils.draw_label(lbl, img, captions)
out_dir = osp.basename(path).replace('.', '_')
save_file_name = out_dir
out_dir = osp.join(osp.dirname(path), out_dir)
if not osp.exists(json_file + '\\' + 'labelme_json'):
os.mkdir(json_file + '\\' + 'labelme_json')
labelme_json = json_file + '\\' + 'labelme_json'
out_dir1 = labelme_json + '\\' + save_file_name
if not osp.exists(out_dir1):
os.mkdir(out_dir1)
PIL.Image.fromarray(img).save(out_dir1 + '\\' + save_file_name +
'_img.png')
PIL.Image.fromarray(lbl).save(out_dir1 + '\\' + save_file_name +
'_label.png')
PIL.Image.fromarray(lbl_viz).save(out_dir1 + '\\' +
save_file_name +
'_label_viz.png')
if not osp.exists(json_file + '\\' + 'mask_png'):
os.mkdir(json_file + '\\' + 'mask_png')
mask_save2png_path = json_file + '\\' + 'mask_png'
################################
#mask_pic = cv2.imread(out_dir1+'\\'+save_file_name+'_label.png',)
#print('pic1_deep:',mask_pic.dtype)
mask_dst = img_as_ubyte(lbl) #mask_pic
print('pic2_deep:', mask_dst.dtype)
cv2.imwrite(
mask_save2png_path + '\\' + save_file_name + '_label.png',
mask_dst)
##################################
with open(osp.join(out_dir1, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir1, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir1)
def main():
json_file = 'E:\项目\学习1\Mask_RCNN\image\oc\\11'
list = os.listdir(json_file)
if not os.path.exists(json_file + '/' + 'pic'):
os.makedirs(json_file + '/' + 'pic')
if not os.path.exists(json_file + '/' + 'cv_mask'):
os.makedirs(json_file + '/' + 'cv_mask')
if not os.path.exists(json_file + '/' + 'labelme_json'):
os.makedirs(json_file + '/' + 'labelme_json')
if not os.path.exists(json_file + '/' + 'json'):
os.makedirs(json_file + '/' + 'json')
for i in range(0, len(list)):
# python open()函数用于打开一个文件，有的时候list[i]不是文件
path = os.path.join(json_file, list[i])
if os.path.isfile(path):
# 拷贝文件函数，属于shutil库
copyfile(path, json_file + '/json/' + list[i])
data = json.load(open(path))
img = utils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name) for l, name in enumerate(lbl_names)
]
lbl_viz = utils.draw_label(lbl, img, captions)
out_dir = osp.basename(list[i]).replace('.', '_')
out_dir = osp.join(osp.dirname(list[i]), out_dir)
# 只取filename的前几个字符就行
filename = out_dir[:-5]
# 文件路径
out_dir = json_file + "/" + 'labelme_json' + "/" + out_dir
out_dir1 = json_file + "/" + 'pic'
out_dir2 = json_file + "/" + 'cv_mask'
if not osp.exists(out_dir):
os.mkdir(out_dir)
# 写入原图
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img' + '.png'))
PIL.Image.fromarray(img).save(
osp.join(out_dir1,
str(filename) + '.png'))
# 写入mask图
utils.lblsave(osp.join(out_dir, 'label.png'), lbl)
utils.lblsave(osp.join(out_dir2, str(filename) + '.png'), lbl)
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
with open(osp.join(out_dir, 'label_names' + '.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
yaml.dump(info, f, default_flow_style=False)
fov = open(osp.join(out_dir, 'info' + '.yaml'), 'w')
for key in info:
fov.writelines(key)
fov.write(':\n')
for k, v in lbl_names.items():
# 这里需要注意，按照标准的labelme生成的yaml文件的格式，建议转化前看看标准的什么样
fov.write('-')
fov.write(' ')
fov.write(k)
fov.write('\n')
fov.close()
print('Saved to: %s' % out_dir)
def main():
warnings.warn("This script is aimed to demonstrate how to convert the\n"
"JSON file to a single image dataset, and not to handle\n"
"multiple JSON files to generate a real-use dataset.")
parser = argparse.ArgumentParser()
parser.add_argument('--json_file',
default='jsonFile/',
help='path to load json_file. . ')
parser.add_argument('-o',
'--out',
default='labeltrain_test',
help='path to output mask. . ')
# parser.add_argument('json_file')
# parser.add_argument('-o', '--out', default=None)
args = parser.parse_args()
json_file = args.json_file
if args.out is None:
out_dir = osp.basename(json_file).replace('.', '_')
out_dir = osp.join(osp.dirname(json_file), out_dir)
else:
out_dir = args.out
if not osp.exists(out_dir):
os.mkdir(out_dir)
# print("jsonfile:",json_file)
# print(out_dir)
count = os.listdir(json_file)
# print(count[0:10])
#
for i in range(0, len(count)):
path = os.path.join(json_file, count[i])
if os.path.isfile(path):
data = json.load(open(path))
if data['imageData']:
imageData = data['imageData']
else:
imagePath = os.path.join(os.path.dirname(path),
data['imagePath'])
with open(imagePath, 'rb') as f:
imageData = f.read()
imageData = base64.b64encode(imageData).decode('utf-8')
img = utils.img_b64_to_arr(imageData)
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name) for l, name in enumerate(lbl_names)
]
lbl_viz = utils.draw_label(lbl, img, captions)
####====================================================================
####=======creat dir save label ========================================
json_out_dir = osp.basename(path).replace('.', '_')
save_file_name = osp.join(osp.dirname(__file__), out_dir,
json_out_dir)
# print(save_file_name)
# print(abc)
#creat dir save label
if not osp.exists(save_file_name):
os.mkdir(save_file_name)
# PIL.Image.fromarray(img).save(out_dir1 + '\\' + save_file_name + '_img.png')
PIL.Image.fromarray(lbl).save(save_file_name + '/' + 'label.png')
PIL.Image.fromarray(lbl_viz).save(save_file_name + '/' +
'label_viz.png')
####=====================================================================
#========================================================================
#==============transform label.png to uint8 for train====================
mask_path = out_dir
mask_name = osp.basename(path).split(".")[0]
mask_dst = img_as_ubyte(lbl) # mask_pic
print('pic2_deep:', mask_dst.dtype)
cv2.imwrite(mask_path + '/' + mask_name + '.png', mask_dst)
####======================================================================
with open(osp.join(save_file_name, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(save_file_name, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % save_file_name)
def processor(json_file, encoding="utf-8", flag=False):
"""
input a json folder,or single file path
"""
if not os.path.exists(json_file):
raise FileExistsError('Not Found')
else:
if os.path.isfile(json_file):
if not json_file.endswith('.json'):
raise TypeError('Must be a *.json file')
else:
parent_path = os.path.dirname(json_file) + os.sep
try:
data = json.load(open(json_file, encoding=encoding))
img = lUtils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = lUtils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name)
for l, name in enumerate(lbl_names)
]
lbl_viz = lUtils.draw_label(lbl, img, captions)
##
if np.max(lbl) == 255 or np.max(lbl) == 1:
lbl[lbl > 0] = 255
##
lbl = np.array(lbl, dtype=np.uint8)
if not flag:
out_dir = osp.basename(json_file).split('.json')[0]
save_file_name = out_dir
if not osp.exists(parent_path + 'mask'):
os.mkdir(parent_path + 'mask')
maskdir = parent_path + 'mask'
if not osp.exists(parent_path + 'mask_viz'):
os.mkdir(parent_path + 'mask_viz')
maskvizdir = parent_path + 'mask_viz'
out_dir1 = maskdir
PIL.Image.fromarray(lbl).save(out_dir1 + '/' +
save_file_name + '.png')
PIL.Image.fromarray(lbl_viz).save(maskvizdir + '/' +
save_file_name +
'_label_viz.png')
with open(osp.join(out_dir1, 'label_names.txt'),
'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir1, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir1)
else:
return lbl
except Exception as e:
# print(e)
logger.error(e)
else:
list_path = os.listdir(json_file)
# print('freedom =', json_file)
for i in tqdm(range(0, len(list_path))):
path = os.path.join(json_file, list_path[i])
if os.path.isfile(path) and path.endswith('.json'):
try:
data = json.load(open(path, encoding=encoding))
img = lUtils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = lUtils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name)
for l, name in enumerate(lbl_names)
]
lbl_viz = lUtils.draw_label(lbl, img, captions)
# lbl[lbl>0] = 255
if np.max(lbl) == 255 or np.max(lbl) == 1:
lbl[lbl > 0] = 255
lbl = np.array(lbl, dtype=np.uint8)
# out_dir = osp.basename(path).replace('.', '_')
out_dir = osp.basename(path).split('.json')[0]
save_file_name = out_dir
# out_dir = osp.join(osp.dirname(path), out_dir)
if not osp.exists(json_file + 'mask'):
os.mkdir(json_file + 'mask')
maskdir = json_file + 'mask'
if not osp.exists(json_file + 'mask_viz'):
os.mkdir(json_file + 'mask_viz')
maskvizdir = json_file + 'mask_viz'
out_dir1 = maskdir
# if not osp.exists(out_dir1):
# os.mkdir(out_dir1)
# PIL.Image.fromarray(img).save(out_dir1 + '\\' + save_file_name + '_img.png')
PIL.Image.fromarray(lbl).save(out_dir1 + '/' +
save_file_name + '.png')
PIL.Image.fromarray(lbl_viz).save(maskvizdir + '/' +
save_file_name +
'_label_viz.png')
with open(osp.join(out_dir1, 'label_names.txt'),
'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
# warnings.warn('info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir1, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir1)
except Exception as e:
# print(e)
logger.error(e)
def main():
warnings.warn("This script is aimed to demonstrate how to convert the\n"
"JSON file to a single image dataset, and not to handle\n"
"multiple JSON files to generate a real-use dataset.")
json_file = "results/annotations/"
images_path = "results/images/"
save_dir = "results"
# freedom
#list_path = os.listdir(json_file)
print('freedom =', json_file)
#for i in range(0, len(list_path)):
for root_dir, _, files in os.walk(json_file):
#path = os.path.join(json_file, list_path[i])
for file in files:
path = os.path.join(root_dir, file)
sub_dir = path.split('/')[-2]
if os.path.isfile(path):
print('---', path)
try:
data = json.load(open(path), encoding='utf-8')
if data['imageData']:
imageData = data['imageData']
else:
#imagePath = os.path.join(os.path.dirname(json_file), data['imagePath'])
imagePath = os.path.join(images_path, sub_dir,
data['imagePath'])
with open(imagePath, 'rb') as f:
imageData = f.read()
imageData = base64.b64encode(imageData).decode(
'utf-8')
img = utils.img_b64_to_arr(imageData)
lbl, lbl_names = utils.labelme_shapes_to_label(
img.shape, data['shapes'])
captions = [
'%d: %s' % (l, name)
for l, name in enumerate(lbl_names)
]
# lbl_viz = utils.draw_label(lbl, img, captions)
lbl_viz = labelmeutils.draw_label(lbl, img, captions)
out_dir = osp.basename(path).split('.json')[0]
save_file_name = out_dir
if not osp.exists(osp.join(save_dir, 'mask')):
os.mkdir(osp.join(save_dir, 'mask'))
maskdir = osp.join(save_dir, 'mask')
if not osp.exists(osp.join(save_dir, 'mask_viz')):
os.mkdir(osp.join(save_dir, 'mask_viz'))
maskvizdir = osp.join(save_dir, 'mask_viz')
out_dir1 = maskdir
PIL.Image.fromarray(lbl).save(
osp.join(out_dir1, save_file_name + '.png'))
PIL.Image.fromarray(lbl_viz).save(
osp.join(maskvizdir,
save_file_name + '_label_viz.png'))
with open(osp.join(out_dir1, 'label_names.txt'), 'w') as f:
for lbl_name in lbl_names:
f.write(lbl_name + '\n')
warnings.warn(
'info.yaml is being replaced by label_names.txt')
info = dict(label_names=lbl_names)
with open(osp.join(out_dir1, 'info.yaml'), 'w') as f:
yaml.safe_dump(info, f, default_flow_style=False)
print('Saved to: %s' % out_dir1)
except Exception as exc:
print('generated an exception: %s' % (exc))
continue
import PIL.Image
import yaml
from labelme import utils
json_file = 'F:/Graduate/'
list = os.listdir(json_file) #返回指定文件夹包含文件列表
for i in range(0, len(list)):
path = os.path.join(json_file, list[i])
filename = list[i][:-5] #(生成.json)
if os.path.isfile(path):
data = json.load(open(path))
img = utils.img_b64_to_arr(data['imageData'])
lbl, lbl_names = utils.labelme_shapes_to_label(img.shape,
data['shapes'])
captions = ['%d: %s' % (l, name) for l, name in enumerate(lbl_names)]
lbl_viz = utils.draw_label(lbl, img, captions)
# 返回最后文件名bo_json
out_dir = osp.basename(list[i]).replace('.', '_')
#out_dir = osp.join(osp.dirname(list[i]), out_dir)#文件夹路径和文件名合并
out_dir = osp.join('F:/Graduate', out_dir)
#out_dir='G:/bo/'
if not osp.exists(out_dir):
os.mkdir(out_dir) #自动创建目录
'''
PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
PIL.Image.fromarray(lbl).save(osp.join(out_dir, 'label.png'))
PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
