def load(cls, file_name):
config = deserialize_config(file_name)
skil_server = Skil.from_config()
experiment = get_experiment_by_id(skil_server, config['experiment_id'])
result = Model(model_id=config['model_id'],
experiment=experiment, create=False)
result.name = config['model_name']
return result
def enter():
enemy.dead = 0
enemy.life = 100
gfw.world.init(['bg', 'card', 'state', 'ui'])
gfw.world.remove(highscore)
center = get_canvas_width() // 2, get_canvas_height() // 1.4
center2 = get_canvas_width() // 2, 250
hp = 150, 700
gfw.world.add(gfw.layer.bg, gobj.ImageObject(theme + '/black.png',
center2))
gfw.world.add(gfw.layer.bg, gobj.ImageObject(theme + '/bg.png', center))
#gfw.world.add(gfw.layer.bg, gobj.ImageObject(theme + '/gaugefg.png', hp))
x, y = start_x, start_y
idxs = [n + 1 for n in range(9)]
#print('before:', idxs)
#random.shuffle(idxs)
#print('after: ', idxs)
for i in range(0, 9, +3):
print(idxs[i:i + 3])
for i in idxs:
c = Pattern(i, (x, y), theme)
gfw.world.add(gfw.layer.card, c)
x += Pattern.WIDTH + PADDING - 100
if x > get_canvas_width():
x = start_x
y -= Pattern.HEIGHT + PADDING - 100
icon = Skil(1, (150, 200), theme)
gfw.world.add(gfw.layer.card, icon)
pla = Player(1, (550, 450), theme)
gfw.world.add(gfw.layer.card, pla)
ene = Enemy(1, (150, 480), theme)
gfw.world.add(gfw.layer.card, ene)
global last_card
last_card = None
global TIME, font
TIME = 1000
font = gfw.font.load(gobj.res('ENCR10B.TTF'), 20)
highscore.load()
global bg_music, flip_wav
bg_music = load_music(gobj.res('bg1.mp3'))
bg_music.set_volume(60)
flip_wav = load_wav(gobj.res('pipe.wav'))
bg_music.repeat_play()
def load(cls, file_name):
config = deserialize_config(file_name)
skil_server = Skil.from_config()
experiment = get_experiment_by_id(skil_server, config['experiment_id'])
transform_type = config['transform_type']
result = Transform(transform_id=config['transform_id'],
transform_type=transform_type,
experiment=experiment,
create=False)
result.name = config['transform_name']
return result
from skil import Skil, WorkSpace, Experiment, Model, Deployment
from keras.datasets import mnist
skil_server = Skil()
work_space = WorkSpace(skil_server)
experiment = Experiment(work_space)
model = Model('model.pb', model_id='tf_model', experiment=experiment)
deployment = Deployment(skil_server)
service = model.deploy(deployment,
input_names=['input'],
output_names=['output'])
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_test = x_test.reshape(10000, 784)
x_test = x_test.astype('float32')
x_test /= 255
print(service.predict_single(x_test[0]))
print(service.predict(x_test[:10]))
from skil import Skil, Service, utils
from skil import get_workspace_by_id
from skil import get_experiment_by_id
from skil import get_model_by_id
from skil import get_deployment_by_id
from utils import annotate_image
from time import time
import cv2
skil_server = Skil(
host = 'localhost',
port = 9008,
user_id = 'admin',
password = '******'
)
experiment = skil_server.api.list_all_experiments(skil_server.server_id)[0]
workspace_id = experiment.model_history_id
experiment_id = 'yolo-experiment-01'
model_id = 'yolo-model-01'
deployment_id = '0'
work_space = get_workspace_by_id(skil_server, workspace_id)
experiment = get_experiment_by_id(work_space, experiment_id)
deployment = get_deployment_by_id(skil_server, deployment_id)
model = get_model_by_id(experiment, model_id)
service = Service(
skil=skil_server,
#import skil_client
#
#configuration = skil_client.Configuration()
#configuration.host = 'http://52.15.103.124:9008'
#configuration.api_key['authorization'] = 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJhdWQiOiJTa2lsVXNlciIsInN1YiI6IntcInVzZXJJZFwiOlwiYWRtaW5cIixcInVzZXJOYW1lXCI6XCJhZG1pblwiLFwicm9sZVwiOlwiYWRtaW5cIixcInNjb3BlXCI6XCJhZG1pblwifSIsImlzcyI6IlNraWxBdXRoTWFuYWdlciIsImV4cCI6MTU4NjgyODcxMCwiaWF0IjoxNTU1MjkyNzEwfQ.vXXpr0kk9H8nMbkcM8sPWPJwuws1GGvI8SWc76qKvUo'
#api_instance = skil_client.DefaultApi(skil_client.ApiClient(configuration))
#api_response = api_instance.predictimage("yolo", "default", "yolomodel", image='input.jpg')
#
from skil import Skil
skil_server = Skil(host='52.15.103.124', password='******')
from skil import WorkSpace, Experiment, Model
work_space = WorkSpace(skil_server, name="Object detection project")
experiment = Experiment(work_space, name="YOLO")
model = Model('yolo_v2.pb', name='yolo_model', experiment=experiment)
#
from skil import Deployment
deployment = Deployment(skil_server)
service = model.deploy(deployment,
scale=1,
input_names=['input'],
output_names=['output'])
#
#from skil.utils.yolo import annotate_image
#import cv2
#
#image = cv2.imread('input.jpg')
#detection = service.detect_objects(image)
'host': 'localhost', # Edit this if using docker-machine.
'port': '9008',
'username': '******',
'password': '******',
'workspace_id': '',
'experiment_id': '',
'deployment_id': ''
},
f)
with open('.skil', 'r') as f:
skil_conf = json.load(f)
# Connect to SKIL and create an experiment for storing our model experiments.
skil_server = Skil(host=skil_conf['host'],
port=skil_conf['port'],
user_id=skil_conf['username'],
password=skil_conf['password'])
work_space = None
if skil_conf['workspace_id'] == '':
work_space = WorkSpace(skil_server, name="Mnist Sample")
skil_conf['workspace_id'] = work_space.id
else:
work_space = skil.get_workspace_by_id(None, skil_server,
skil_conf['workspace_id'])
experiment = None
if skil_conf['experiment_id'] == '':
experiment = Experiment(work_space, name='Simple MLP')
skil_conf['experiment_id'] = experiment.id
else: