Commit cc38b7821a5408390fae68feffa179cecd812cd5 - 62b5d1b7621f1a08902903b0 - (('Mo Repos',), {'htdigest_file': None, 'use_smarthttp': 0, 'require_browser_auth': 0, 'disable_push': 0, 'unauthenticated_push': 0, 'ctags

+1

-1

app_spec.yml less more

+11

-1

handler.py less more

9	9
10	10	model_PATH='/home/jovyan/work/src/output/models/model2000.ckpt'
11	11
	12	import time
	13	def run_time(func):
	14	def inner(model, image, question):
	15	back = func(model, image, question)
	16	print("Runned time: {} s".format(round((time.time() - t)/10, 3)))
	17	return back
	18	t = time.time()
	19	return inner
	20
12	21	def load_demo_image(in_PATH):
13	22	img = np.array(Image.open(in_PATH).convert('RGB'))[np.newaxis] / 255.0
14	23	img_p = util.preprocess_images_outpainting(img)
15	24	return img_p
16	25
	26	@run_time
17	27	def inference(model_PATH, img_p):
18	28	G_Z = tf.placeholder(tf.float32, shape=[None, IMAGE_SZ, IMAGE_SZ, 4], name='G_Z')
19	29	G_sample = model.generator(G_Z)

38	48	"""
39	49	base64_str = conf['Photo']
40	50	image = load_demo_image(base64_str, image_size, device)
41		res = inference(model, image)
	51	res = inference(model_PATH, image)
42	52	# add your code
43	53	return {'Output': res}
44	54	⏎

+8

-8

src/.ipynb_checkpoints/Untitled-checkpoint.ipynb less more

2	2	{
3	3	"cell_type": "code",
4	4	"execution_count": 3,
5		"id": "769c9afd",
	5	"id": "04c7f16a",
6	6	"metadata": {},
7	7	"outputs": [
8	8	{

39	39	{
40	40	"cell_type": "code",
41	41	"execution_count": 4,
42		"id": "227c58c5",
	42	"id": "0dd13c75",
43	43	"metadata": {},
44	44	"outputs": [],
45	45	"source": [

49	49	{
50	50	"cell_type": "code",
51	51	"execution_count": 9,
52		"id": "dc65195f",
	52	"id": "649a883e",
53	53	"metadata": {},
54	54	"outputs": [],
55	55	"source": [

66	66	{
67	67	"cell_type": "code",
68	68	"execution_count": 8,
69		"id": "bcbe551f",
	69	"id": "fba4c6ff",
70	70	"metadata": {},
71	71	"outputs": [],
72	72	"source": [

79	79	{
80	80	"cell_type": "code",
81	81	"execution_count": 6,
82		"id": "36fcb0d9",
	82	"id": "ff900f2b",
83	83	"metadata": {},
84	84	"outputs": [],
85	85	"source": [

100	100	},
101	101	{
102	102	"cell_type": "code",
103		"execution_count": null,
104		"id": "b79deb86",
	103	"execution_count": 10,
	104	"id": "9d164058",
105	105	"metadata": {},
106	106	"outputs": [],
107	107	"source": [

116	116	" \"\"\"\n",
117	117	" base64_str = conf['Photo']\n",
118	118	" image = load_demo_image(base64_str, image_size, device)\n",
119		" res = inference(model, image)\n",
	119	" res = inference(model_PATH, image)\n",
120	120	" # add your code\n",
121	121	" return {'Output': res}\n",
122	122	" "

+8

-8

src/Untitled.ipynb less more

2	2	{
3	3	"cell_type": "code",
4	4	"execution_count": 3,
5		"id": "3c86ef8a",
	5	"id": "755152e5",
6	6	"metadata": {},
7	7	"outputs": [
8	8	{

39	39	{
40	40	"cell_type": "code",
41	41	"execution_count": 4,
42		"id": "87b58a5a",
	42	"id": "c45b2ba8",
43	43	"metadata": {},
44	44	"outputs": [],
45	45	"source": [

49	49	{
50	50	"cell_type": "code",
51	51	"execution_count": 9,
52		"id": "4e963aed",
	52	"id": "7eb0351a",
53	53	"metadata": {},
54	54	"outputs": [],
55	55	"source": [

66	66	{
67	67	"cell_type": "code",
68	68	"execution_count": 8,
69		"id": "aba8e440",
	69	"id": "196069cc",
70	70	"metadata": {},
71	71	"outputs": [],
72	72	"source": [

79	79	{
80	80	"cell_type": "code",
81	81	"execution_count": 6,
82		"id": "bc8c0bf4",
	82	"id": "e0a075d4",
83	83	"metadata": {},
84	84	"outputs": [],
85	85	"source": [

100	100	},
101	101	{
102	102	"cell_type": "code",
103		"execution_count": null,
104		"id": "5c1557b3",
	103	"execution_count": 10,
	104	"id": "c7dfafbb",
105	105	"metadata": {},
106	106	"outputs": [],
107	107	"source": [

116	116	" \"\"\"\n",
117	117	" base64_str = conf['Photo']\n",
118	118	" image = load_demo_image(base64_str, image_size, device)\n",
119		" res = inference(model, image)\n",
	119	" res = inference(model_PATH, image)\n",
120	120	" # add your code\n",
121	121	" return {'Output': res}\n",
122	122	" "