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
python类IS_MULTISCALE的实例源码
train.py 文件源码
项目：Automatic_Group_Photography_Enhancement
作者: Yuliang-Zou
项目源码
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test.py 文件源码
项目：Automatic_Group_Photography_Enhancement
作者: Yuliang-Zou
项目源码
文件源码
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def _get_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
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_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
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_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
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_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
def _get_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
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_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
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'
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_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.TEST.HAS_RPN:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
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.IS_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_blobs(im, rois):
"""Convert an image and RoIs within that image into network inputs."""
if cfg.IS_RPN:
blobs = {'data' : None, 'boxes_grid' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
blobs['boxes_grid'] = rois
else:
blobs = {'data' : None, 'rois' : None}
blobs['data'], im_scale_factors = _get_image_blob(im)
if cfg.IS_MULTISCALE:
if cfg.IS_EXTRAPOLATING:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
else:
blobs['rois'] = _get_rois_blob(rois, cfg.TEST.SCALES_BASE)
return blobs, im_scale_factors
train.py 文件源码
项目：Automatic_Group_Photography_Enhancement
作者: Yuliang-Zou
项目源码
文件源码
阅读 29
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def get_data_layer(roidb, num_classes):
"""return a data layer."""
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
layer = GtDataLayer(roidb)
else:
layer = RoIDataLayer(roidb, num_classes)
else:
layer = RoIDataLayer(roidb, num_classes)
return layer
def get_data_layer(roidb, num_classes):
"""return a data layer."""
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
layer = GtDataLayer(roidb)
else:
layer = RoIDataLayer(roidb, num_classes)
else:
layer = RoIDataLayer(roidb, num_classes)
return layer
def get_data_layer(roidb, num_classes):
"""return a data layer."""
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
layer = GtDataLayer(roidb)
else:
layer = RoIDataLayer(roidb, num_classes)
else:
layer = RoIDataLayer(roidb, num_classes)
return layer
def get_data_layer(roidb, num_classes):
"""return a data layer."""
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
layer = GtDataLayer(roidb)
else:
layer = RoIDataLayer(roidb, num_classes)
else:
layer = RoIDataLayer(roidb, num_classes)
return layer
def get_data_layer(roidb, num_classes):
"""return a data layer."""
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
layer = GtDataLayer(roidb)
else:
layer = RoIDataLayer(roidb, num_classes)
else:
layer = RoIDataLayer(roidb, num_classes)
return layer
def get_data_layer(roidb, num_classes):
"""return a data layer."""
if cfg.TRAIN.HAS_RPN:
if cfg.IS_MULTISCALE:
layer = GtDataLayer(roidb)
else:
layer = RoIDataLayer(roidb, num_classes)
else:
layer = RoIDataLayer(roidb, num_classes)
return layer
