Python dataset2tfrecord Examples

Example #1

File: ctest_voc_utils.py Project: Linby1103/tensorflow-retinaNet

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import os
import numpy as np
import matplotlib.pyplot as plt
import utils.tfrecord_voc_utils as voc_utils
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
output_path='D:/install/RetinaNet/RetinaNet-tensorflow/data/'
Annotations='E:/image/libin_dataset/RetinaNet/VOC/Annotations/'
JPEGImages='E:/image/libin_dataset/RetinaNet/VOC/JPEGImages/'
if os.path.exists(Annotations)==False:
    os.makedirs()

if os.path.exists(Annotations)==False:
    os.makedirs(JPEGImages)

tfrecord = voc_utils.dataset2tfrecord(Annotations, JPEGImages,
                                      output_path, 'test',2)
print(tfrecord)

Example #2

File: test_voc_utils.py Project: xiao-an-qi/centernet_tensorflow

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import os
import numpy as np
import matplotlib.pyplot as plt
import utils.tfrecord_voc_utils as voc_utils
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0'

# annotations path, image path, save path, tfrecord prefix, shard
xml_address = 'D:/Object-Detection-API-Tensorflow-master/VOC2007/AnnotationsSSD/'
image_address = 'D:/Object-Detection-API-Tensorflow-master/VOC2007/JPEGImages/'
save_address = 'D:/Object-Detection-API-Tensorflow-master/VOC2007/ImageSets/'

tfrecord = voc_utils.dataset2tfrecord(xml_address, image_address, save_address, 'train', 40)
print(tfrecord)

Example #3

File: test_voc_utils.py Project: zlf1993/PCT

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import os
import numpy as np
import matplotlib.pyplot as plt
import utils.tfrecord_voc_utils as voc_utils
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
os.environ['CUDA_VISIBLE_DEVICES'] = '0'

tfrecord = voc_utils.dataset2tfrecord('../VOC/Annotations',
                                      '../VOC/JPEGImages', '../data/', 'test',
                                      10)
print(tfrecord)

Example #4

File: test_voc_utils.py Project: PWenJay/Modified-YOLOv2

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import utils.tfrecord_voc_utils as voc_utils

# annotations path, image path, save path, tfrecord prefix, shard
annotations_path = os.path.join(os.getcwd(), '..', 'voc2007', 'Annotation')
JpegImages_path = os.path.join(os.getcwd(), '..', 'voc2007', 'JPEGImage')
tfrecord = voc_utils.dataset2tfrecord(annotations_path, JpegImages_path,
                                      '../data1/', 'train', 1)
print(tfrecord)

Example #5

File: test_voc_utils.py Project: sycophant-stone/tf_base

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import os
import numpy as np
import matplotlib.pyplot as plt
import utils.tfrecord_voc_utils as voc_utils
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
os.environ['CUDA_VISIBLE_DEVICES'] = '0'

tfrecord = voc_utils.dataset2tfrecord('VOC/VOCdevkit/VOC2007/Annotations',
                                      'VOC/VOCdevkit/VOC2007/JPEGImages',
                                      'data/', 'test', 10)
print(tfrecord)