def iterate(self):
THIS_DIR = os.getcwd()
os.chdir(os.path.join(ANNEX_DIR, self.base_path))
try:
iter_num = len(self.getAssetsByTagName(ASSET_TAGS['DLXDD_DD']))
bc = BatCountry(os.path.join(getConfig('caffe_root'), "models", "bvlc_googlenet"))
img = bc.dream(np.float32(self.get_image(file_name="dream_%d.jpg" % iter_num)))
bc.cleanup()
os.chdir(THIS_DIR)
iter_num += 1
dream = Image.fromarray(np.uint8(img))
asset_path = self.addAsset(None, "dream_%d.jpg" % iter_num, \
tags=[ASSET_TAGS['DLXDD_DD']], description="deep dream iteration")
if asset_path is not None:
dream.save(os.path.join(ANNEX_DIR, asset_path))
return True
except Exception as e:
print "ERROR ON ITERATION:"
print e, type(e)
return False
def POST(self):
data = web.input(auth_code='', image={})
if data.auth_code == '':
raise web.Forbidden()
if data.auth_code != config.auth_code:
raise web.Forbidden()
if 'image' not in data:
raise web.BadRequest()
input_image = Image.open(data['image'].file)
bc = BatCountry(os.environ['CAFFE_HOME'] + '/models/bvlc_googlenet')
result_data = bc.dream(np.float32(input_image),
end='inception_3b/5x5_reduce')
bc.cleanup()
result_image = Image.fromarray(np.uint8(result_data))
result = io.BytesIO()
result_image.save(result, 'PNG')
result.seek(0)
web.header('Content-type', 'image/png')
return result.read()
def iterate(self):
THIS_DIR = os.getcwd()
os.chdir(os.path.join(ANNEX_DIR, self.base_path))
try:
iter_num = len(self.getAssetsByTagName(ASSET_TAGS['DLXDD_DD']))
bc = BatCountry(
os.path.join(getConfig('caffe_root'), "models",
"bvlc_googlenet"))
img = bc.dream(
np.float32(self.get_image(file_name="dream_%d.jpg" %
iter_num)))
bc.cleanup()
os.chdir(THIS_DIR)
iter_num += 1
dream = Image.fromarray(np.uint8(img))
asset_path = self.addAsset(None, "dream_%d.jpg" % iter_num, \
tags=[ASSET_TAGS['DLXDD_DD']], description="deep dream iteration")
if asset_path is not None:
dream.save(os.path.join(ANNEX_DIR, asset_path))
return True
except Exception as e:
print "ERROR ON ITERATION:"
print e, type(e)
return False
def dream_that_image(before, after, layer, seed, filehash, iteration):
# dreaming...
mydebugmsg("Dreaming dream #" + str(iteration))
mydebugmsg("before = [" + before + "]")
mydebugmsg("after = [" + after + "]")
bc = BatCountry(DREAMMODEL)
features = bc.prepare_guide(Image.open(seed), end=layer)
image = bc.dream(np.float32(Image.open(before)),
end=layer,
iter_n=20,
objective_fn=BatCountry.guided_objective,
objective_features=features,
verbose=VERBOSITY)
bc.cleanup()
#
# write the output image to file
#
result = Image.fromarray(np.uint8(image))
result.save(after)
#
# Save both the input image and output image to S3 using the MD5 hash of the original file content as the key name
#
keyname = filehash + ".jpg"
key = beforebucket.new_key(keyname)
key.set_contents_from_filename(before)
key.set_acl('public-read')
mydebugmsg("new key name = [" + keyname + "]")
create_thumbnail(before, keyname, before_thumbnails_bucket)
#
# keyname should look like hashvalue.1.jpg
#
keyname = filehash + "." + str(iteration) + ".jpg"
key = afterbucket.new_key(keyname)
key.set_contents_from_filename(after)
key.set_acl('public-read')
mydebugmsg("new key name = [" + keyname + "]")
create_thumbnail(after, keyname, after_thumbnails_bucket)
photo_after_url = "https://{}.{}/{}".format(after_bucket_name,
s3.server_name(), keyname)
tweet_the_nightmare(photo_after_url)
mydebugmsg("url for tweepy = " + photo_after_url)
mydebugmsg("------------------------------------------")
return
# --image initial_images/fear_and_loathing/fal_01.jpg \
# --vis examples/output/visualizations
# import the necessary packages
from batcountry import BatCountry
from PIL import Image
import numpy as np
import argparse
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-b", "--base-model", required=True, help="base model path")
ap.add_argument("-l", "--layer", type=str, default="conv2/3x3",
help="layer of CNN to use")
ap.add_argument("-i", "--image", required=True, help="path to base image")
ap.add_argument("-v", "--vis", required=True,
help="path to output directory for visualizations")
args = ap.parse_args()
# we can't stop here...
bc = BatCountry(args.base_model)
(image, visualizations) = bc.dream(np.float32(Image.open(args.image)),
end=args.layer, visualize=True)
bc.cleanup()
# loop over the visualizations
for (k, vis) in visualizations:
# write the visualization to file
outputPath = "{}/{}.jpg".format(args.vis, k)
result = Image.fromarray(np.uint8(vis))
result.save(outputPath)
import os
from batcountry import BatCountry
import numpy as np
from PIL import Image
bc = BatCountry(os.path.expanduser("~/install/caffe/models/bvlc_googlenet"))
image = bc.dream(np.float32(Image.open("cat.1.jpg")))
bc.cleanup()
result = Image.fromarray(np.uint8(image))
result.save("output.jpg")
