def _save_images_to_local_disk(self, user, image, storage_dir):
user_id = str(user.id)
original_filename = "%s-%s.jpg" % (user_id, 'web')
original_file_path = '%s/%s' % (storage_dir, original_filename)
thumbnail_filename = '%s-%s.jpg' % (user_id, 'thumbnail')
thumbnail_file_path = '%s/%s' % (storage_dir, thumbnail_filename)
msg = "Saving user profile image to: %s" % original_file_path
current_app.logger.info(msg)
f = open(original_file_path, 'wb')
f.write(base64.b64decode(image))
f.close()
im = Image.open(original_file_path);
thumbnail_image = cropresize.crop_resize(im, (71, 96));
msg = "Saving user profile image thumbnail to: %s" % thumbnail_file_path
current_app.logger.info(msg)
thumbnail_image.save(thumbnail_file_path, 'JPEG', quality=100)
return {
"original_filename": original_filename,
"original_file_path": original_file_path,
"thumbnail_filename": thumbnail_filename,
"thumbnail_file_path": thumbnail_file_path,
}
def get_img2gist():
try:
img2gist = None
with open(name2gist_file, 'rb') as f:
print 'loading existed img2gist...'
sys.stdout.flush()
img2gist = pickle.load(f)
return img2gist
except Exception:
img2gist = {}
total_num = 0
with open(train_file_map, 'r') as f:
for line in f:
if line.strip():
total_num += 1
count = 0
with open(train_file_map, 'r') as f:
for line in f:
if line.strip():
count += 1
arr = line.strip().split()
name = arr[0].strip()
rpath = arr[1].strip()
im = Image.open(pjoin(train_images_dir, rpath))
im = crop_resize(im, normal_size, True)
desc = leargist.color_gist(im)
img2gist[name] = desc
sys.stdout.write(
'%d/%d\r size:(%d, %d) ' % (count, total_num, im.size[0], im.size[1]))
sys.stdout.flush()
with open(name2gist_file, 'wb') as f:
pickle.dump(img2gist, f)
return img2gist
def rsize(cls, oldPaste, weight, height):
assert oldPaste.is_image
img = cropresize.crop_resize(Image.open(oldPaste.path),
(int(weight), int(height)))
return cls.create_by_img(img, oldPaste.filename, oldPaste.mimetype)
def _save_images_to_local_disk(self, user, image, storage_dir):
user_id = str(user.id)
original_filename = "%s-%s.jpg" % (user_id, 'web')
original_file_path = '%s/%s' % (storage_dir, original_filename)
thumbnail_filename = '%s-%s.jpg' % (user_id, 'thumbnail')
thumbnail_file_path = '%s/%s' % (storage_dir, thumbnail_filename)
squareimg_filename = '%s-%s.jpg' % (user_id, 'square')
squareimg_file_path = '%s/%s' % (storage_dir, squareimg_filename)
msg = "Saving user profile image to: %s" % original_file_path
current_app.logger.info(msg)
f = open(original_file_path, 'wb')
# We may receive a FileStorage type:
if isinstance(image, FileStorage):
if hasattr(image.stream, 'getvalue'):
image = image.stream.getvalue()
else:
image = image.stream.read()
f.write(image)
else:
f.write(base64.b64decode(image))
f.close()
im = Image.open(original_file_path);
thumbnail_image = cropresize.crop_resize(im, (71, 96));
square_image = cropresize.crop_resize(im, (71, 71));
msg = "Saving user profile image thumbnail to: %s" % thumbnail_file_path
current_app.logger.info(msg)
thumbnail_image.save(thumbnail_file_path, 'JPEG', quality=100)
square_image.save(squareimg_file_path, 'JPEG', quality=100)
return {
"original_filename": original_filename,
"original_file_path": original_file_path,
"thumbnail_filename": thumbnail_filename,
"thumbnail_file_path": thumbnail_file_path,
"squareimg_filename": squareimg_filename,
"squareimg_file_path": squareimg_file_path,
}
def create_file_after_crop(cls, uploadedFile, width, height):
assert uploadedFile.is_image, TypeError("Unsupported Image Type.")
img = cropresize.crop_resize(Image.open(uploadedFile), (int(width), int(height)))
rst = cls(uploadedFile.filename, uploadedFile.mimetype, 0)
img.save(rst.path)
filestat = os.stat(rst.path)
rst.size = filestat.st_size
return rst
def main_proc(query,
image_path,
random=False,
query_cache=False,
image_cache=False):
"""
Return distance of a (query, image) pair
"""
if random:
return np.random.rand()
global img2gist, query_miss, hash_miss, query_top10_cache, image_top10_cache
if img2gist is None:
img2gist = get_img2gist()
im = Image.open(image_path)
im = crop_resize(im, normal_size, True)
desc = leargist.color_gist(im)
if query_cache:
A = query_top10_cache
else:
t1 = -time.time()
A = query_top10_images(query)
query_top10_cache = A
print 'time for query_top10_images:', time.time() + t1
if image_cache:
B = image_top10_cache
else:
t2 = -time.time()
B = gist_top10_images(image_path)
image_top10_cache = B
print 'time for gist_top10_images:', time.time() + t2
if not A:
if not query_cache:
query_miss += 1
return np.random.rand()
if not B:
hash_miss += 1
sim_set = []
t3 = -time.time()
for i in A:
gist_i = img2gist[i]
for j in B:
v = np.sum((gist_i - img2gist[j])**2)
sim_set.append(v)
sim_set.append(np.sum((gist_i - desc)**2))
print 'time for compare:', time.time() + t3
return min(sim_set)
def create_file_after_crop(cls, uploadedFile, width, height):
assert uploadedFile.is_image, TypeError("Unsupported Image Type.")
img = cropresize.crop_resize(Image.open(uploadedFile),
(int(width), int(height)))
rst = cls(uploadedFile.filename, uploadedFile.mimetype, 0)
img.save(rst.path)
filestat = os.stat(rst.path)
rst.size = filestat.st_size
return rst
def main_proc(query, image_path, random=False, query_cache=False, image_cache=False):
"""
Return distance of a (query, image) pair
"""
if random:
return np.random.rand()
global img2gist, query_miss, hash_miss, query_top10_cache, image_top10_cache
if img2gist is None:
img2gist = get_img2gist()
im = Image.open(image_path)
im = crop_resize(im, normal_size, True)
desc = leargist.color_gist(im)
if query_cache:
A = query_top10_cache
else:
t1 = -time.time()
A = query_top10_images(query)
query_top10_cache = A
print 'time for query_top10_images:', time.time() + t1
if image_cache:
B = image_top10_cache
else:
t2 = -time.time()
B = gist_top10_images(image_path)
image_top10_cache = B
print 'time for gist_top10_images:', time.time() + t2
if not A:
if not query_cache:
query_miss += 1
return np.random.rand()
if not B:
hash_miss += 1
sim_set = []
t3 = -time.time()
for i in A:
gist_i = img2gist[i]
for j in B:
v = np.sum((gist_i - img2gist[j]) ** 2)
sim_set.append(v)
sim_set.append(np.sum((gist_i - desc) ** 2))
print 'time for compare:', time.time() + t3
return min(sim_set)
def create_sizes(self, ticket, attachment):
"""create the sizes for a ticket image"""
filename = attachment.filename
# add the specified sizes as attachments
sizes = self.sizes()
for name, size in sizes.items():
# crop the image
image = Image.open(attachment.path)
i = crop_resize(image, size)
buffer = StringIO()
i.save(buffer, image.format)
buffer.seek(0,2) # seek to end of file
filesize = buffer.tell()
buffer.seek(0)
a = Attachment(self.env, 'ticket', ticket.id)
a.author = ticket['reporter']
a.description = ticket['summary']
f = ('.%sx%s.' % (size[0] or '', size[1] or '')).join(filename.rsplit('.', 1)) # XXX assumes the file has an extension
a.insert(f, buffer, filesize)
def create_sizes(self, ticket, attachment):
"""create the sizes for a ticket image"""
filename = attachment.filename
# add the specified sizes as attachments
sizes = self.sizes()
for name, size in sizes.items():
# crop the image
image = Image.open(attachment.path)
i = crop_resize(image, size)
buffer = StringIO()
i.save(buffer, image.format)
buffer.seek(0, 2) # seek to end of file
filesize = buffer.tell()
buffer.seek(0)
a = Attachment(self.env, 'ticket', ticket.id)
a.author = ticket['reporter']
a.description = ticket['summary']
f = ('.%sx%s.' % (size[0] or '', size[1] or '')).join(
filename.rsplit('.',
1)) # XXX assumes the file has an extension
a.insert(f, buffer, filesize)
def gist_top10_images(img):
"""
32 bit hash:
bucket ratio: 225410/4294967296
max conflicts: 8691
16 bit hash:
bucket ratio: 8135/65536
max conficts: 93329
"""
global lsh
# name2path = get_name2path(train_file_map)
# info of known dataset
# print lsh.hash_tables[0].keys()[0]
# print 'bucket ratio: %d/%d' % (len(lsh.hash_tables[0].keys()), 2 ** hash_len)
# counts = []
# t = lsh.hash_tables[0]
# for k in t.keys():
# counts.append(len(t.get_list(k)))
# print 'max conflicts:', max(counts)
# print 'min conflicts:', min(counts)
im = Image.open(img)
im = crop_resize(im, normal_size, True)
desc = leargist.color_gist(im)
# for i in xrange(len(desc)):
# desc[i] += 0.01
res = lsh.query(desc, num_results=10, distance_func="euclidean")
# print 'num of results:', len(res)
# for i in res:
# name = json.loads(i[0])[1]
# print name, name2path[name], i[1]
return [json.loads(i[0])[1] for i in res]
def __call__(self, request, data):
# add width + height data
data['width'] = self.width
data['height'] = self.height
# filter out non-images
_files = []
for f in data['files']:
mimetype = mimetypes.guess_type(f['name'])[0]
if mimetype and mimetype.split('/')[0] == 'image':
_files.append(f)
f['link'] = f['path']
data['files'] = _files
# columns for grid display
if self.columns is None:
data['columns'] = len(data['files'])
else:
data['columns'] = int(self.columns)
# thumbnails
if 'thumbnails' not in self.args:
return
thumb_dir = self.thumb_dir
if not os.path.isabs(thumb_dir):
thumb_dir = os.path.join(data['directory'], self.thumb_dir)
else:
raise NotImplementedError
if not os.path.exists(thumb_dir):
os.mkdir(thumb_dir)
for f in data['files']:
filepath = os.path.join(data['directory'], f['name'])
thumbnail = '%s%s' % (self.thumb_prefix, f['name'])
thumbnail_file = os.path.join(data['directory'], thumb_dir,
thumbnail)
create_thumbnail = False
if os.path.exists(thumbnail_file):
try:
# ensure the size is smaller than the specified size
thumb = Image.open(thumbnail_file)
if self.width and thumb.size[0] > self.width:
create_thumbnail = True
if self.height and thumb.size[1] > self.height:
create_thumbnail = True
except:
pass
# ensure the original file has not been modified
if os.path.getmtime(thumbnail_file) < os.path.getmtime(
filepath):
create_thumbnail = True
else:
# create a new thumbnail
create_thumbnail = True
if create_thumbnail: # do thumbnail creation
flag = False
try:
image = Image.open(filepath)
thumbnail_image = crop_resize(image,
(self.width, self.height))
fd = file(thumbnail_file, 'w')
flag = True
thumbnail_image.save(fd)
fd.close()
except Exception, e: # failure to create thumbnail
# cleanup file
if flag:
fd.close()
os.remove(thumbnail_file)
# fix the path to point to the thumbnail
if os.path.exists(thumbnail_file):
f['path'] = '%s/%s/%s' % (f['path'].rsplit(
'/', 1)[0], self.thumb_dir, thumbnail)
#/usr/bin/env python
import Image
import cropresize
import os
files = os.listdir('images/')
files = [f for f in files if not str(f) == '.DS_Store']
for f in files:
img = Image.open('images/' + str(f))
img = cropresize.crop_resize(img, (230, 172))
img.save('thumbs/' + str(f))
print """<a class="fancybox" href="images/may2013/images/{0}" rel="may2013"><img src="images/may2013/thumbs/{0}"></a>
""".format(str(f))
def rsize(cls, oldPaste, weight, height):
assert oldPaste.is_image
img = cropresize.crop_resize(Image.open(oldPaste.path), (int(weight), int(height)))
return cls.create_by_img(img, oldPaste.filename, oldPaste.mimetype)
def _resize(self, im, size, upscale):
return crop_resize(im, size, exact_size=upscale)
