876897f
user_wwq 3 years ago
4 changed file(s) with 166 addition(s) and 328 deletion(s). Raw diff Collapse all Expand all
+162
-0
Untitled.ipynb less more
0 {
1 "cells": [
2 {
3 "cell_type": "code",
4 "execution_count": 3,
5 "id": "a2c41897",
6 "metadata": {},
7 "outputs": [
8 {
9 "name": "stderr",
10 "output_type": "stream",
11 "text": [
12 "2022-06-27 17:55:39.372674: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory\n",
13 "2022-06-27 17:55:39.372709: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n"
14 ]
15 },
16 {
17 "name": "stdout",
18 "output_type": "stream",
19 "text": [
20 "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/compat/v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
21 "Instructions for updating:\n",
22 "non-resource variables are not supported in the long term\n",
23 "Imported model (for Places365, 128x128 images)\n"
24 ]
25 }
26 ],
27 "source": [
28 "import tensorflow.compat.v1 as tf\n",
29 "tf.disable_v2_behavior()\n",
30 "tf.reset_default_graph()\n",
31 "import numpy as np\n",
32 "from PIL import Image\n",
33 "import src.model\n",
34 "import src.util\n",
35 "import os\n",
36 "import sys"
37 ]
38 },
39 {
40 "cell_type": "code",
41 "execution_count": 4,
42 "id": "594228ab",
43 "metadata": {},
44 "outputs": [],
45 "source": [
46 "model_PATH='/home/jovyan/work/src/output/models/model2000.ckpt'"
47 ]
48 },
49 {
50 "cell_type": "code",
51 "execution_count": 9,
52 "id": "0f45afcf",
53 "metadata": {},
54 "outputs": [],
55 "source": [
56 "import time\n",
57 "def run_time(func):\n",
58 " def inner(model, image, question):\n",
59 " back = func(model, image, question)\n",
60 " print(\"Runned time: {} s\".format(round((time.time() - t)/10, 3)))\n",
61 " return back\n",
62 " t = time.time()\n",
63 " return inner"
64 ]
65 },
66 {
67 "cell_type": "code",
68 "execution_count": 8,
69 "id": "db3b4a43",
70 "metadata": {},
71 "outputs": [],
72 "source": [
73 "def load_demo_image(in_PATH):\n",
74 " img = np.array(Image.open(in_PATH).convert('RGB'))[np.newaxis] / 255.0\n",
75 " img_p = util.preprocess_images_outpainting(img)\n",
76 " return img_p"
77 ]
78 },
79 {
80 "cell_type": "code",
81 "execution_count": 11,
82 "id": "1252a38c",
83 "metadata": {},
84 "outputs": [],
85 "source": [
86 "def image_to_path(img):\n",
87 " resize_img = img\n",
88 " path = uuid.uuid4().hex + '.png'\n",
89 " resize_img.save(path)\n",
90 " return path"
91 ]
92 },
93 {
94 "cell_type": "code",
95 "execution_count": 6,
96 "id": "5e7e4c55",
97 "metadata": {},
98 "outputs": [],
99 "source": [
100 "@run_time\n",
101 "def inference(model_PATH, img_p):\n",
102 " G_Z = tf.placeholder(tf.float32, shape=[None, IMAGE_SZ, IMAGE_SZ, 4], name='G_Z')\n",
103 " G_sample = model.generator(G_Z)\n",
104 " \n",
105 " saver = tf.train.Saver()\n",
106 " with tf.Session() as sess:\n",
107 " saver.restore(sess, model_PATH)\n",
108 " output, = sess.run([G_sample], feed_dict={G_Z: img_p})\n",
109 " img_norm = (output[0] * 255.0).astype(np.uint8)\n",
110 " img = Image.fromarray(img_norm, 'RGB')\n",
111 " #util.save_image(output[0], out_PATH)\n",
112 " return img"
113 ]
114 },
115 {
116 "cell_type": "code",
117 "execution_count": 12,
118 "id": "c4224744",
119 "metadata": {},
120 "outputs": [],
121 "source": [
122 "def handle(conf):\n",
123 " \"\"\"\n",
124 " 该方法是部署之后，其他人调用你的服务时候的处理方法。\n",
125 " 请按规范填写参数结构，这样我们就能替你自动生成配置文件，方便其他人的调用。\n",
126 " 范例：\n",
127 " params['key'] = value # value_type: str # description: some description\n",
128 " value_type 可以选择：img, video, audio, str, int, float, [int], [str], [float]\n",
129 " 参数请放到params字典中，我们会自动解析该变量。\n",
130 " \"\"\"\n",
131 " base64_str = conf['Photo']\n",
132 " image = load_demo_image(base64_str)\n",
133 " res = inference(model_PATH, image)\n",
134 " image_str = image_to_path(res)\n",
135 " return {'Output': res}\n",
136 " "
137 ]
138 }
139 ],
140 "metadata": {
141 "kernelspec": {
142 "display_name": "Python 3 (ipykernel)",
143 "language": "python",
144 "name": "python3"
145 },
146 "language_info": {
147 "codemirror_mode": {
148 "name": "ipython",
149 "version": 3
150 },
151 "file_extension": ".py",
152 "mimetype": "text/x-python",
153 "name": "python",
154 "nbconvert_exporter": "python",
155 "pygments_lexer": "ipython3",
156 "version": "3.7.5"
157 }
158 },
159 "nbformat": 4,
160 "nbformat_minor": 5
161 }
+4
-4
handler.py less more
22 tf.reset_default_graph()
33 import numpy as np
44 from PIL import Image
5 import model
6 import util
5 import src.model
6 import src.util
77 import os
88 import sys
99
5353 参数请放到params字典中，我们会自动解析该变量。
5454 """
5555 base64_str = conf['Photo']
56 image = load_demo_image(base64_str, image_size, device)
56 image = load_demo_image(base64_str)
5757 res = inference(model_PATH, image)
5858 image_str = image_to_path(res)
59 return {'Output': res}
59 return {'Output': image_str}
6060 ⏎
+0
-162
src/.ipynb_checkpoints/Untitled-checkpoint.ipynb less more
0 {
1 "cells": [
2 {
3 "cell_type": "code",
4 "execution_count": 3,
5 "id": "a0f197c0",
6 "metadata": {},
7 "outputs": [
8 {
9 "name": "stderr",
10 "output_type": "stream",
11 "text": [
12 "2022-06-27 17:55:39.372674: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory\n",
13 "2022-06-27 17:55:39.372709: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n"
14 ]
15 },
16 {
17 "name": "stdout",
18 "output_type": "stream",
19 "text": [
20 "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/compat/v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
21 "Instructions for updating:\n",
22 "non-resource variables are not supported in the long term\n",
23 "Imported model (for Places365, 128x128 images)\n"
24 ]
25 }
26 ],
27 "source": [
28 "import tensorflow.compat.v1 as tf\n",
29 "tf.disable_v2_behavior()\n",
30 "tf.reset_default_graph()\n",
31 "import numpy as np\n",
32 "from PIL import Image\n",
33 "import model\n",
34 "import util\n",
35 "import os\n",
36 "import sys"
37 ]
38 },
39 {
40 "cell_type": "code",
41 "execution_count": 4,
42 "id": "35638e2a",
43 "metadata": {},
44 "outputs": [],
45 "source": [
46 "model_PATH='/home/jovyan/work/src/output/models/model2000.ckpt'"
47 ]
48 },
49 {
50 "cell_type": "code",
51 "execution_count": 9,
52 "id": "bfa0229a",
53 "metadata": {},
54 "outputs": [],
55 "source": [
56 "import time\n",
57 "def run_time(func):\n",
58 " def inner(model, image, question):\n",
59 " back = func(model, image, question)\n",
60 " print(\"Runned time: {} s\".format(round((time.time() - t)/10, 3)))\n",
61 " return back\n",
62 " t = time.time()\n",
63 " return inner"
64 ]
65 },
66 {
67 "cell_type": "code",
68 "execution_count": 8,
69 "id": "57494ceb",
70 "metadata": {},
71 "outputs": [],
72 "source": [
73 "def load_demo_image(in_PATH):\n",
74 " img = np.array(Image.open(in_PATH).convert('RGB'))[np.newaxis] / 255.0\n",
75 " img_p = util.preprocess_images_outpainting(img)\n",
76 " return img_p"
77 ]
78 },
79 {
80 "cell_type": "code",
81 "execution_count": 11,
82 "id": "d1ab22e6",
83 "metadata": {},
84 "outputs": [],
85 "source": [
86 "def image_to_path(img):\n",
87 " resize_img = img\n",
88 " path = uuid.uuid4().hex + '.png'\n",
89 " resize_img.save(path)\n",
90 " return path"
91 ]
92 },
93 {
94 "cell_type": "code",
95 "execution_count": 6,
96 "id": "4a7370fa",
97 "metadata": {},
98 "outputs": [],
99 "source": [
100 "@run_time\n",
101 "def inference(model_PATH, img_p):\n",
102 " G_Z = tf.placeholder(tf.float32, shape=[None, IMAGE_SZ, IMAGE_SZ, 4], name='G_Z')\n",
103 " G_sample = model.generator(G_Z)\n",
104 " \n",
105 " saver = tf.train.Saver()\n",
106 " with tf.Session() as sess:\n",
107 " saver.restore(sess, model_PATH)\n",
108 " output, = sess.run([G_sample], feed_dict={G_Z: img_p})\n",
109 " img_norm = (output[0] * 255.0).astype(np.uint8)\n",
110 " img = Image.fromarray(img_norm, 'RGB')\n",
111 " #util.save_image(output[0], out_PATH)\n",
112 " return img"
113 ]
114 },
115 {
116 "cell_type": "code",
117 "execution_count": 12,
118 "id": "b03bba02",
119 "metadata": {},
120 "outputs": [],
121 "source": [
122 "def handle(conf):\n",
123 " \"\"\"\n",
124 " 该方法是部署之后，其他人调用你的服务时候的处理方法。\n",
125 " 请按规范填写参数结构，这样我们就能替你自动生成配置文件，方便其他人的调用。\n",
126 " 范例：\n",
127 " params['key'] = value # value_type: str # description: some description\n",
128 " value_type 可以选择：img, video, audio, str, int, float, [int], [str], [float]\n",
129 " 参数请放到params字典中，我们会自动解析该变量。\n",
130 " \"\"\"\n",
131 " base64_str = conf['Photo']\n",
132 " image = load_demo_image(base64_str, image_size, device)\n",
133 " res = inference(model_PATH, image)\n",
134 " image_str = image_to_path(res)\n",
135 " return {'Output': res}\n",
136 " "
137 ]
138 }
139 ],
140 "metadata": {
141 "kernelspec": {
142 "display_name": "Python 3 (ipykernel)",
143 "language": "python",
144 "name": "python3"
145 },
146 "language_info": {
147 "codemirror_mode": {
148 "name": "ipython",
149 "version": 3
150 },
151 "file_extension": ".py",
152 "mimetype": "text/x-python",
153 "name": "python",
154 "nbconvert_exporter": "python",
155 "pygments_lexer": "ipython3",
156 "version": "3.7.5"
157 }
158 },
159 "nbformat": 4,
160 "nbformat_minor": 5
161 }
+0
-162
src/Untitled.ipynb less more
0 {
1 "cells": [
2 {
3 "cell_type": "code",
4 "execution_count": 3,
5 "id": "29291686",
6 "metadata": {},
7 "outputs": [
8 {
9 "name": "stderr",
10 "output_type": "stream",
11 "text": [
12 "2022-06-27 17:55:39.372674: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory\n",
13 "2022-06-27 17:55:39.372709: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n"
14 ]
15 },
16 {
17 "name": "stdout",
18 "output_type": "stream",
19 "text": [
20 "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/compat/v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
21 "Instructions for updating:\n",
22 "non-resource variables are not supported in the long term\n",
23 "Imported model (for Places365, 128x128 images)\n"
24 ]
25 }
26 ],
27 "source": [
28 "import tensorflow.compat.v1 as tf\n",
29 "tf.disable_v2_behavior()\n",
30 "tf.reset_default_graph()\n",
31 "import numpy as np\n",
32 "from PIL import Image\n",
33 "import model\n",
34 "import util\n",
35 "import os\n",
36 "import sys"
37 ]
38 },
39 {
40 "cell_type": "code",
41 "execution_count": 4,
42 "id": "67b9aae4",
43 "metadata": {},
44 "outputs": [],
45 "source": [
46 "model_PATH='/home/jovyan/work/src/output/models/model2000.ckpt'"
47 ]
48 },
49 {
50 "cell_type": "code",
51 "execution_count": 9,
52 "id": "058a509a",
53 "metadata": {},
54 "outputs": [],
55 "source": [
56 "import time\n",
57 "def run_time(func):\n",
58 " def inner(model, image, question):\n",
59 " back = func(model, image, question)\n",
60 " print(\"Runned time: {} s\".format(round((time.time() - t)/10, 3)))\n",
61 " return back\n",
62 " t = time.time()\n",
63 " return inner"
64 ]
65 },
66 {
67 "cell_type": "code",
68 "execution_count": 8,
69 "id": "7dd82ead",
70 "metadata": {},
71 "outputs": [],
72 "source": [
73 "def load_demo_image(in_PATH):\n",
74 " img = np.array(Image.open(in_PATH).convert('RGB'))[np.newaxis] / 255.0\n",
75 " img_p = util.preprocess_images_outpainting(img)\n",
76 " return img_p"
77 ]
78 },
79 {
80 "cell_type": "code",
81 "execution_count": 11,
82 "id": "379d2efd",
83 "metadata": {},
84 "outputs": [],
85 "source": [
86 "def image_to_path(img):\n",
87 " resize_img = img\n",
88 " path = uuid.uuid4().hex + '.png'\n",
89 " resize_img.save(path)\n",
90 " return path"
91 ]
92 },
93 {
94 "cell_type": "code",
95 "execution_count": 6,
96 "id": "70d5031c",
97 "metadata": {},
98 "outputs": [],
99 "source": [
100 "@run_time\n",
101 "def inference(model_PATH, img_p):\n",
102 " G_Z = tf.placeholder(tf.float32, shape=[None, IMAGE_SZ, IMAGE_SZ, 4], name='G_Z')\n",
103 " G_sample = model.generator(G_Z)\n",
104 " \n",
105 " saver = tf.train.Saver()\n",
106 " with tf.Session() as sess:\n",
107 " saver.restore(sess, model_PATH)\n",
108 " output, = sess.run([G_sample], feed_dict={G_Z: img_p})\n",
109 " img_norm = (output[0] * 255.0).astype(np.uint8)\n",
110 " img = Image.fromarray(img_norm, 'RGB')\n",
111 " #util.save_image(output[0], out_PATH)\n",
112 " return img"
113 ]
114 },
115 {
116 "cell_type": "code",
117 "execution_count": 12,
118 "id": "d7439afa",
119 "metadata": {},
120 "outputs": [],
121 "source": [
122 "def handle(conf):\n",
123 " \"\"\"\n",
124 " 该方法是部署之后，其他人调用你的服务时候的处理方法。\n",
125 " 请按规范填写参数结构，这样我们就能替你自动生成配置文件，方便其他人的调用。\n",
126 " 范例：\n",
127 " params['key'] = value # value_type: str # description: some description\n",
128 " value_type 可以选择：img, video, audio, str, int, float, [int], [str], [float]\n",
129 " 参数请放到params字典中，我们会自动解析该变量。\n",
130 " \"\"\"\n",
131 " base64_str = conf['Photo']\n",
132 " image = load_demo_image(base64_str, image_size, device)\n",
133 " res = inference(model_PATH, image)\n",
134 " image_str = image_to_path(res)\n",
135 " return {'Output': res}\n",
136 " "
137 ]
138 }
139 ],
140 "metadata": {
141 "kernelspec": {
142 "display_name": "Python 3 (ipykernel)",
143 "language": "python",
144 "name": "python3"
145 },
146 "language_info": {
147 "codemirror_mode": {
148 "name": "ipython",
149 "version": 3
150 },
151 "file_extension": ".py",
152 "mimetype": "text/x-python",
153 "name": "python",
154 "nbconvert_exporter": "python",
155 "pygments_lexer": "ipython3",
156 "version": "3.7.5"
157 }
158 },
159 "nbformat": 4,
160 "nbformat_minor": 5
161 }