def __init__(self,
workspace_server_id=None,
host='localhost',
port=9008,
user_id='admin',
password='******',
debug=False):
self.printer = pprint.PrettyPrinter(indent=4)
config = skil_client.Configuration()
config.host = "{}:{}".format(host, port)
config.debug = debug
self.config = config
self.uploads = []
self.uploaded_model_names = []
self.auth_headers = None
self.api_client = skil_client.ApiClient(configuration=config)
self.api = skil_client.DefaultApi(api_client=self.api_client)
try:
self.printer.pprint('>>> Authenticating SKIL...')
credentials = Cred(user_id=user_id, password=password)
token = self.api.login(credentials)
self.token = token.token
config.api_key['authorization'] = self.token
config.api_key_prefix['authorization'] = "Bearer"
self.printer.pprint('>>> Done!')
except api_exception as e:
raise Exception(
"Exception when calling DefaultApi->login: {}\n".format(e))
if workspace_server_id:
self.server_id = workspace_server_id
else:
self.server_id = self.get_default_server_id()
result = {
'host': host,
'port': port,
'user_id': user_id,
'password': password,
'debug': debug,
'workspace_server_id': self.server_id
}
save_skil_config(result)
image_batch = tf.stack(crops)
return image_batch
def make_single_image_batch(image_path, coder):
image_data = tf.gfile.FastGFile(image_path, 'rb').read()
image = coder.decode_jpeg(image_data)
crop = tf.image.resize_images(image, (227,227))
image_batch = tf.stack([crop])
return image_batch
with tf.Session() as sess:
coder = ImageCoder()
image_batch = make_multi_crop_batch(image_file, coder)
image_batch = image_batch.eval()
configuration = skil_client.Configuration()
configuration.host = 'http://192.168.1.128:9008'
configuration.username = '******'
configuration.password = '******'
r = requests.post("http://192.168.1.128:9008/login", json={"userId": "admin", "password": "******"})
token = r.json()['token']
configuration.api_key['authorization'] = f'Bearer {token}'
api_instance = skil_client.DefaultApi(skil_client.ApiClient(configuration))
list_ind_array = [[convert_indarray(np.expand_dims(image_batch[i,:,:,:], axis=0))] for i in range(12)]
batch_results = []
index = 0