def genImage(self, filename):
"generate this image"
image = PIL.Image.open(filename)
if image.mode != self.getConfig('color'):
image = image.convert(self.getConfig('color'))
crop_left = self.getConfig('crop_left')
crop_upper = self.getConfig('crop_upper')
crop_right = self.getConfig('crop_right')
crop_lower = self.getConfig('crop_lower')
if crop_right and crop_lower:
image = image.crop((crop_left, crop_upper, crop_right, crop_lower))
(x, y) = image.size
if x > self.width:
y = y * self.width / x
x = self.width
if y > self.height:
x = x * self.height / y
y = self.height
if x == 0:
x = 1
if y == 0:
y = 1
image = image.resize((x, y))
tempFile = utility.saveImage(image, self.getConfig('format'))
if not self.image:
self.manage_addProduct['Image'].manage_addImage(
'image', tempFile, 'image')
else:
self.image.manage_upload(tempFile)
self.image.width = int(x)
self.image.height = int(y)
self.setFileSize()
def resizeImage(self, filename):
"generate this image"
image=PIL.Image.open(filename)
if image.mode != self.getConfig('color'):
image=image.convert(self.getConfig('color'))
maxWidth = self.getConfig('width')
maxHeight = self.getConfig('height')
crop_left = self.getConfig('crop_left')
crop_upper = self.getConfig('crop_upper')
crop_right = self.getConfig('crop_right')
crop_lower = self.getConfig('crop_lower')
if crop_right and crop_lower:
image = image.crop((crop_left, crop_upper, crop_right, crop_lower))
(x, y) = image.size
if x> maxWidth:
y = y * maxWidth / x
x = maxWidth
if y> maxHeight:
x = x * maxHeight / y
y = maxHeight
if x == 0:
x = 1
if y == 0:
y = 1
image = image.resize((x, y))
tempFile = utility.saveImage(image, self.getConfig('format'))
self.data.manage_upload(tempFile)
self.data.width = x
self.data.height = y
def makeThumbnail(self, filename):
"""
Makes a thumbnail image given an image Id when called on a Zope
folder.
The thumbnail is a Zope image object that is a small JPG
representation of the original image. The thumbnail has a
'original_id' property set to the id of the full size image
object.
"""
size=30
data = self.data or self.image
content_type = magicfile.magic(filename)
if content_type.startswith('image'):
image=Image.open(filename)
image=image.convert('RGB')
(x,y) = image.size
if x > size: x = size
if y > size: y = size
image = image.resize((x,y))
thumbnail_file = utility.saveImage(image, 'JPEG')
thumbnail_id = "thumbnail"
if not getattr(self, thumbnail_id):
self.manage_addProduct['Image'].manage_addImage(thumbnail_id, thumbnail_file, thumbnail_id)
else:
self._getOb(thumbnail_id).manage_upload(thumbnail_file)
def genImage(self, filename):
"generate this image"
image=PIL.Image.open(filename)
if image.mode != self.getConfig('color'):
image=image.convert(self.getConfig('color'))
crop_left = self.getConfig('crop_left')
crop_upper = self.getConfig('crop_upper')
crop_right = self.getConfig('crop_right')
crop_lower = self.getConfig('crop_lower')
if crop_right and crop_lower:
image = image.crop((crop_left, crop_upper, crop_right, crop_lower))
(x, y) = image.size
if x> self.width:
y = y * self.width / x
x = self.width
if y> self.height:
x = x * self.height / y
y = self.height
if x == 0:
x = 1
if y == 0:
y = 1
image = image.resize((x, y))
tempFile = utility.saveImage(image, self.getConfig('format'))
if not self.image:
self.manage_addProduct['Image'].manage_addImage('image', tempFile, 'image')
else:
self.image.manage_upload(tempFile)
self.image.width = int(x)
self.image.height = int(y)
self.setFileSize()
def resizeImage(self, filename):
"generate this image"
image = PIL.Image.open(filename)
if image.mode != self.getConfig('color'):
image = image.convert(self.getConfig('color'))
maxWidth = self.getConfig('width')
maxHeight = self.getConfig('height')
crop_left = self.getConfig('crop_left')
crop_upper = self.getConfig('crop_upper')
crop_right = self.getConfig('crop_right')
crop_lower = self.getConfig('crop_lower')
if crop_right and crop_lower:
image = image.crop((crop_left, crop_upper, crop_right, crop_lower))
(x, y) = image.size
if x > maxWidth:
y = y * maxWidth / x
x = maxWidth
if y > maxHeight:
x = x * maxHeight / y
y = maxHeight
if x == 0:
x = 1
if y == 0:
y = 1
image = image.resize((x, y))
tempFile = utility.saveImage(image, self.getConfig('format'))
self.data.manage_upload(tempFile)
self.data.width = x
self.data.height = y
node_shape = ((80, 52), (74, 46), (34, 20))
filter_shift_list = ((1, 1), (2, 2))
input_shape = [80, 52]
filter_shape = [7, 7]
data_list = load_image(data_path, file_num, isRGB)
makeFolder()
# 時間計測
time1 = time.clock()
cnn1 = CNN(data_list, filter_shape, filter_shift_list[0], input_shape, node_shape[1], pre_train_lr, pre_train_epoch)
output_list = cnn1.output()
saveImage(output_list, node_shape[1], 'cnn1_before_training')
cnn1.pre_train()
output_list = cnn1.output()
saveImage(output_list, node_shape[1], 'cnn1_after_training')
# for i in xrange(pre_train_epoch):
# cnn1.pre_train()
# output_list = cnn1.output()
# saveImage(output_list, (74,46))
cnn2 = CNN(cnn1.output(), filter_shape, filter_shift_list[1], node_shape[1], node_shape[2], pre_train_lr, pre_train_epoch)
output_list = cnn2.output()
saveImage(output_list, node_shape[2], 'cnn2_before_train')
cnn2.pre_train()
result_path = 'data/kouryu_room/cnn2_after_training'
result_data = load_result_image(result_path, file_num, isRGB)
# result_path = 'data/4position_rumba/image7000/rbm1_train3434'
# result_W = loadW(result_path)
makeFolder()
# def __init__(self, W, input, data_size,input_size, output_size, isDropout):
rbm1 = RBM(None, result_data, file_num, rbm_size_list[0], rbm_size_list[1])
for i in xrange(pre_train_epoch):
print 'rbm1 pre_train:' + str(i)
rbm1.contrast_divergence(i)
reinput = rbm1.reconstruct_from_input(rbm1.input)
saveImage(reinput, node_shape[2], 'rbm1_after_train')
saveW(rbm1.getW(), 'rbm1_after_train')
rbm2 = RBM(None, rbm1.output(), file_num, rbm_size_list[1], rbm_size_list[2])
for i in xrange(pre_train_epoch):
print 'rbm2 pre_train:' + str(i)
rbm2.contrast_divergence(i)
reinput = rbm2.reconstruct_from_input(rbm2.input)
reinput = rbm1.reconstruct_from_output(reinput)
saveImage(reinput, node_shape[2], 'rbm2_after_train')
saveW(rbm2.getW(), 'rbm2_after_train')
rbm3 = RBM(None, rbm2.output(), file_num, rbm_size_list[2], rbm_size_list[3])
for i in xrange(pre_train_epoch):
print 'rbm3 pre_train:' + str(i)
rbm3.contrast_divergence(i)
