def create_evaluation_desc_datastore(orb, kind):
storage_client = storage.Client('adina-image-analysis')
bucket = storage_client.get_bucket('sampled_social_media_images')
datastore_client = datastore.Client('adina-image-analysis')
for blob in bucket.list_blobs():
X = []
if not (utils.ext(blob.public_url) == '.jpeg'
or utils.ext(blob.public_url) == '.png'
or utils.ext(blob.public_url) == '.jpg'):
continue
try:
img = utils.url_to_img(blob.public_url)
except:
continue
k = datastore_client.key(kind, utils.del_ext(blob.name))
entity = datastore_client.get(k)
if not entity:
entity = datastore.Entity(key=k,
exclude_from_indexes=['ORB Descriptors'])
try:
des = utils.compute_ORB(img, orb, show_image=False)
if des.any() != None:
for i in range(des.shape[0]):
X.append(utils.convert_intList_to_bit(list(des[i])))
des_json = json.dumps(X)
entity.update({
'ORB Descriptors': des_json,
'Indexed(ORB)': "No"
})
datastore_client.put(entity)
else:
continue
except:
continue
return
def eval_compute_xq_cloud(orb, img_url):
"""compute the query vector of descriptors from the image url"""
img = utils.url_to_img(img_url)
xq = []
try:
des = utils.compute_ORB(img, orb, show_image=False)
if des.any() != None:
for i in range(des.shape[0]):
xq.append(utils.convert_intList_to_bit(list(des[i])))
else:
return None
except AttributeError:
None
return np.array(xq).astype('float32')
def sample_social_media_datastore(orb, quantity, kind):
storage_client = storage.Client('adina-image-analysis')
bucket = storage_client.get_bucket('adina-images')
datastore_client = datastore.Client('adina-image-analysis')
p = utils.count_storage('adina-images')
l = list(range(p))
choseen = random.sample(l, quantity)
i = 0
s = 31
for blob in bucket.list_blobs():
i += 1
X = []
if i in choseen:
if not (utils.ext(blob.public_url) == '.jpeg'
or utils.ext(blob.public_url) == '.png'
or utils.ext(blob.public_url) == '.jpg'):
continue
if not (blob.name.startswith('4C') or blob.name.startswith('RE')
or blob.name.startswith('R')):
continue
try:
img = utils.url_to_img(blob.public_url)
except:
continue
try:
des = utils.compute_ORB(img, orb, show_image=False)
if des.any() != None:
for i in range(des.shape[0]):
X.append(utils.convert_intList_to_bit(list(des[i])))
des_json = json.dumps(X)
name = '333_' + str(s)
s += 1
k = datastore_client.key(kind, name)
entity = datastore.Entity(key=k,
exclude_from_indexes=[
'ORB Descriptors',
'VGG16 Descriptors'
])
# print("1")
# print(entity)
entity.update({
'ORB Descriptors': des_json,
'Indexed(ORB)': "No"
})
# print("2")
# print(entity)
datastore_client.put(entity)
# print("3")
# print(entity)
if s % 1000 == 0:
print(s, 'images processed')
else:
continue
except:
continue
return