def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
if cfg.TRAIN.USE_FLIPPED:
print('Appending horizontally-flipped training examples...')
imdb.append_flipped_images()
print('done')
print('Preparing training data...')
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print('done')
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
"""if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
imdb.append_flipped_images()
print 'done'""" # think about including this flipping operation again....
print 'Preparing training data...'
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print 'done'
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
imdb.append_flipped_images()
print 'done'
print 'Preparing training data...'
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print 'done'
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
#parse xml annotation
#box = imdb.roidb[i]实现了解析，因为imdb.roidb = imdb._roidb_handler = pascal_voc.gt_roidb
imdb.append_flipped_images()
print 'done'
print 'Preparing training data...'
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print 'done'
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
# 在训练期间使用水平翻转图像
# 不光把数据加载进来，还要把翻转之后的数据加载进来，可以数量量加倍
imdb.append_flipped_images()
print 'done'
print 'Preparing training data...'
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
# 准备数据 对roidb做处理 （把之前结果命名更规范一些）
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print 'done'
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
imdb.append_flipped_images()
print 'done'
print 'Preparing training data...'
# 训练时是否使用RPN
if cfg.TRAIN.HAS_RPN:
# 是否多尺度
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print 'done'
# 返回imdb中最关键的属性roidb，此时roidb的每个元素包含更多的信息，视gdl或rdl而定
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
# cfg.TRAIN.USE_FLIPPED已经定义为TRUE，表示使用水平反转图像（数据增强），防止过拟合
if cfg.TRAIN.USE_FLIPPED:
print('Appending horizontally-flipped training examples...'
) # clw modify: for py3
imdb.append_flipped_images()
print('done') # clw modify: for py3
print('Preparing training data...') # clw modify: for py3
if cfg.TRAIN.HAS_RPN: #False
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
# 就是对roidb进行进一步的操作，添加了image.weight.height.max_classes.max_overlaps
rdl_roidb.prepare_roidb(imdb)
print('done') # clw modify: for py3
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
if cfg.TRAIN.USE_FLIPPED:
print('Appending horizontally-flipped training examples...')
imdb.append_flipped_images()
print('done')
print('Preparing training data...')
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
# TODO: fix multiscale training (single scale is already a good trade-off)
print('#### warning: multi-scale has not been tested.')
print(
'#### warning: using single scale by setting IS_MULTISCALE: False.'
)
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
print('done')
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
"""if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
imdb.append_flipped_images()
print 'done'""" # think about including this flipping operation again....
print 'Preparing training data...'
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
"""print('&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&')
print(imdb.image_index)
print(len(imdb.image_index)) # is twice as long as it should be!! <- due to flipping!
print('&&&&&&&&&&&&&&&&&&&&&&&')"""
else:
rdl_roidb.prepare_roidb(imdb)
print 'done'
return imdb.roidb
def get_training_roidb(imdb):
"""Returns a roidb (Region of Interest database) for use in training."""
#cfg.TRAIN.USE_FLIPPED已经定义为TRUE，表示使用水平反转图像（数据增强），防止过拟合
if cfg.TRAIN.USE_FLIPPED:
print 'Appending horizontally-flipped training examples...'
# append_flipped_images：将图片水平对称变换，增加样本数量
# roidb是imdb的一个成员变量，roidb是一个list（每个元素对应一张图片），list中的元素是一个字典，字典中存放了5个key，分别是boxes信息，每个box的class信息，是否是flipped的标志位，重叠信息gt_overlaps，以及seg_areas；分析该函数可知，将box的值按照水平对称，原先roidb中只有5011个元素，经过水平对称后通过append增加到5011*2=10022个
imdb.append_flipped_images()
print('done')
print('Preparing training data...')
#cfg.TRAIN.HAS_RPN为false
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
gdl_roidb.prepare_roidb(imdb)
else:
rdl_roidb.prepare_roidb(imdb)
else:
#就是对roidb进行进一步的操作，添加了image.weight.height.max_classes.max_overlaps
rdl_roidb.prepare_roidb(imdb)
print 'done'
return imdb.roidb