├── .circleci
    └── config.yml
├── .gitignore
├── Dockerfile
├── LICENSE
├── README.md
├── configuration
    └── config.json
├── image_classification_service
    ├── __main__.py
    ├── configuration.py
    └── imagenet
    │   ├── model_data
    │       ├── classify_image_graph_def.pb
    │       ├── imagenet_2012_challenge_label_map_proto.pbtxt
    │       └── imagenet_synset_to_human_label_map.txt
    │   └── node_lookup.py
├── requirements.txt
├── scripts
    ├── build-docker
    ├── run-snet-service
    └── test-call
├── service.json
└── service_spec
    └── ExampleService.proto


/.circleci/config.yml:
--------------------------------------------------------------------------------
 1 | version: 2
 2 | jobs:
 3 |   build:
 4 |     docker:
 5 |     - image: circleci/python:3.6.6
 6 |     working_directory: ~/singnet/example-service
 7 |     environment:
 8 |       TRIGGER_BUILD_BRANCH: master
 9 |     steps:
10 |     - checkout
11 |     - run:
12 |         name: Build example-service
13 |         command: sudo pip3 install -r requirements.txt
14 |     - run:
15 |         name: Test example-service
16 |         command: |
17 |           cat > ./configuration/config.json << EOF
18 |           {
19 |             "SERVER_PORT": 5001,
20 |             "MINIMUM_SCORE": 0.20,
21 |             "LOG_LEVEL": 10
22 |           }
23 |           python image_classification_service &
24 |           ./scripts/test-call
25 |     - run:
26 |         name: Trigger platform-pipeline build
27 |         command: |
28 |           if [ "$CIRCLE_BRANCH" == "$TRIGGER_BUILD_BRANCH" ]
29 |           then
30 |             curl -u ${CIRCLECI_PLATFORM_PIPELINE_TOKEN}: \
31 |               -d build_parameters[CIRCLE_JOB]=build \
32 |               -d build_parameters[PARENT_PROJECT_REPONAME]="$CIRCLE_PROJECT_REPONAME" \
33 |               -d build_parameters[PARENT_BRANCH]="$CIRCLE_BRANCH" \
34 |               -d build_parameters[PARENT_BUILD_URL]="$CIRCLE_BUILD_URL" \
35 |               https://circleci.com/api/v1.1/project/github/singnet/platform-pipeline/tree/${TRIGGER_BUILD_BRANCH}
36 |           fi
37 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | venv/
2 | .idea/
3 | __pycache__/
4 | snetd.db
5 | snetd.config
6 | 
7 | 


--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------
1 | FROM python:3.6.5-stretch
2 | ADD . /
3 | RUN pip3 install -r /requirements.txt
4 | RUN touch /snetd.config.json
5 | RUN apt-get install -y wget
6 | RUN wget https://github.com/singnet/snet-daemon/releases/download/v0.1.1/snetd-0.1.1.tar.gz
7 | RUN tar -xvf snetd-0.1.1.tar.gz
8 | CMD ["./scripts/run-snet-service"]
9 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2018 SingularityNET
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # example-service
 2 | 
 3 | [![CircleCI](https://circleci.com/gh/singnet/example-service.svg?style=svg)](https://circleci.com/gh/singnet/example-service)
 4 | 
 5 | Simple image classification service compatible with the SingularityNET daemon
 6 | 
 7 | ## Getting Started
 8 | 
 9 | ### Prerequisites
10 | 
11 | * [Python 3.6.5](https://www.python.org/downloads/release/python-365/)
12 | 
13 | ### Installing
14 | 
15 | * Clone the git repository
16 | ```bash
17 | $ git clone git@github.com:singnet/example-service.git
18 | $ cd example-service
19 | ```
20 | 
21 | * Install the dependencies
22 | ```bash
23 | $ pip install -r requirements.txt
24 | ```
25 | 
26 | ### Configuration
27 | 
28 | * The following default configuration can be overridden by populating configuration/config.json in the source tree with
29 | the desired values
30 | ```json
31 | {
32 |   "SERVER_PORT": 5001,
33 |   "MINIMUM_SCORE": 0.20,
34 |   "LOG_LEVEL": 10
35 | }
36 | ```
37 | * SERVER_PORT: the port on which the example service will listen for incoming JSON-RPC calls over http
38 | * MINIMUM_SCORE: the minimum confidence score (between 0 and 1 inclusive) required to return a given prediction
39 | * LOG_LEVEL: the logging verbosity
40 | 
41 | ### Running
42 | 
43 | #### Standalone
44 | 
45 | * Invoke the example service directly
46 | ```bash
47 | $ python image_classification_service
48 | ```
49 | 
50 | #### With SingularityNET Daemon
51 | 
52 | ##### SingularityNET Daemon Configuration
53 | 
54 | Create `snetd.config.json` file containing the following:
55 | ```json
56 | {
57 |   "passthrough_enabled": true
58 | }
59 | ```
60 | in order to enable example service work with daemon. See [SingularityNet daemon configuration](https://github.com/singnet/snet-daemon/blob/master/README.md#configuration) for detailed configuration description.
61 | 
62 | ##### Running Service + Daemon on Host
63 | 
64 | * Invoke the run-snet-service script which launches both snetd and the example service
65 | ```bash
66 | $ ./scripts/run-snet-service
67 | ```
68 | 
69 | ##### Running Service + Daemon in Docker Container
70 | 
71 | * Ensure that PASSTHROUGH_ENDPOINT is configured to be "http://127.0.0.1:5001" in your daemon configuration
72 | * Run the docker image with your daemon configuration (where HOST_PORT is the port you want the daemon bound to on your
73 | host)
74 | ```bash
75 | $ docker run --detach -p HOST_PORT:DAEMON_LISTENING_PORT -v /path/to/config:/snetd.config singularitynet/example-service:latest
76 | ```
77 | 
78 | ### Testing
79 | 
80 | * Invoke the test-call script against a running instance of the example service
81 | ```bash
82 | $ ./scripts/test-call
83 | ```
84 | 
85 | ### Building Docker Image
86 | 
87 | * Invoke the docker build script
88 | ```bash
89 | $ ./scripts/build-docker
90 | ```
91 | 
92 | ## License
93 | 
94 | This project is licensed under the MIT License - see the
95 | [LICENSE](https://github.com/singnet/example-service/blob/master/LICENSE) file for details.
96 | 


--------------------------------------------------------------------------------
/configuration/config.json:
--------------------------------------------------------------------------------
1 | {}
2 | 


--------------------------------------------------------------------------------
/image_classification_service/__main__.py:
--------------------------------------------------------------------------------
 1 | import base64
 2 | import logging
 3 | from pathlib import Path
 4 | 
 5 | import tensorflow
 6 | from aiohttp import web
 7 | from jsonrpcserver.aio import methods
 8 | from jsonrpcserver.exceptions import InvalidParams
 9 | import sys
10 | sys.path.append(str(Path(__file__).absolute().parent.parent))
11 | 
12 | from image_classification_service import configuration as config
13 | from image_classification_service.imagenet.node_lookup import NodeLookup
14 | 
15 | logger = logging.getLogger(__name__)
16 | app = web.Application()
17 | 
18 | graph_path = Path(__file__).parent.joinpath("imagenet", "model_data", "classify_image_graph_def.pb")
19 | with tensorflow.gfile.FastGFile(str(graph_path), "rb") as f:
20 |     graph_def = tensorflow.GraphDef()
21 |     graph_def.ParseFromString(f.read())
22 |     tensorflow.import_graph_def(graph_def, name="")
23 | node_lookup = NodeLookup()
24 | session = tensorflow.Session()
25 | softmax_tensor = session.graph.get_tensor_by_name("softmax:0")
26 | 
27 | 
28 | @methods.add
29 | async def classify(**kwargs):
30 |     image = kwargs.get("image", None)
31 |     image_type = kwargs.get("image_type", None)
32 | 
33 |     if image is None:
34 |         raise InvalidParams("image is required")
35 | 
36 |     if image_type is None:
37 |         raise InvalidParams("image_type is required")
38 | 
39 |     binary_image = base64.b64decode(image)
40 |     if image_type == 'jpeg' or image_type == 'jpg':
41 |         decoder_key = 'DecodeJpeg/contents:0'
42 |     elif image_type == 'png':
43 |         decoder_key = 'DecodeJpeg/contents:0'
44 |     elif image_type == 'gif':
45 |         raise RuntimeError("TensorflowImageNet - cannot decode gif images")
46 |     elif image_type == 'bmp':
47 |         raise RuntimeError("TensorflowImageNet - cannot decode bmp images")
48 |     else:
49 |         decoder_key = 'DecodeJpeg/contents:0'
50 |         logger.warning("Missing image type {0}".format(image_type))
51 | 
52 |     logger.debug("classifying '{0}' image".format(image_type))
53 | 
54 |     raw_predictions = session.run(softmax_tensor, {decoder_key: binary_image})
55 | 
56 |     # Pull the predicted scorces out of the raw predictions.
57 |     predicted_scores = raw_predictions[0]
58 | 
59 |     # Sort and strip off the top 5 predictions.
60 |     top_predictions = predicted_scores.argsort()[-5:][::-1]
61 |     image_predictions = []
62 |     image_scores = []
63 |     for predicted_node_id in top_predictions:
64 |         # Get a text description for the top predicted node.
65 |         description = node_lookup.id_to_string(predicted_node_id)
66 | 
67 |         # Cast to a float so JSON can serialize it. Normal Tensorflow float32 are not serializable.
68 |         score = float(predicted_scores[predicted_node_id])
69 | 
70 |         logger.debug("        prediction = '{0}', score = {1}".format(description, score))
71 | 
72 |         # Add only those that exceed our minimum score to the predictions and scores lists.
73 |         if score > config.MINIMUM_SCORE:
74 |             image_predictions.append(description)
75 |             image_scores.append(score)
76 | 
77 |     return {"predictions": image_predictions, "confidences": image_scores}
78 | 
79 | 
80 | async def handle(request):
81 |     request = await request.text()
82 |     response = await methods.dispatch(request)
83 |     if response.is_notification:
84 |         return web.Response()
85 |     else:
86 |         return web.json_response(response, status=response.http_status)
87 | 
88 | 
89 | if __name__ == '__main__':
90 |     logging.basicConfig(level=config.LOG_LEVEL, format="%(asctime)s - [%(levelname)8s] - %(name)s - %(message)s")
91 |     app.router.add_post('/', handle)
92 |     web.run_app(app, host="127.0.0.1", port=config.SERVER_PORT)
93 | 


--------------------------------------------------------------------------------
/image_classification_service/configuration.py:
--------------------------------------------------------------------------------
 1 | import json
 2 | import logging
 3 | import os
 4 | import sys
 5 | from pathlib import Path
 6 | 
 7 | logger = logging.getLogger(__name__)
 8 | 
 9 | SERVER_PORT = 5001
10 | MINIMUM_SCORE = 0.20
11 | LOG_LEVEL = 10
12 | 
13 | # Override from file
14 | with open(Path(__file__).parent.parent.joinpath("configuration", "config.json")) as f:
15 |     overrides = json.load(f)
16 |     for k, v in overrides.items():
17 |         logger.debug("overriding config key %s with value %s from config file", k, v)
18 |         setattr(sys.modules[__name__], k, v)
19 | 
20 | # Override from environment variables
21 | for k in dir(sys.modules[__name__]):
22 |     if os.environ.get(k, None) is not None:
23 |         logger.debug("overriding config key %s with value %s from environment", k, os.environ[k])
24 |         setattr(sys.modules[__name__], k, os.environ[k])
25 | 


--------------------------------------------------------------------------------
/image_classification_service/imagenet/model_data/classify_image_graph_def.pb:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/singnet/sample-tensorflow-service/13cdfa81375fd0554d5071a47052268443944f68/image_classification_service/imagenet/model_data/classify_image_graph_def.pb


--------------------------------------------------------------------------------
/image_classification_service/imagenet/model_data/imagenet_2012_challenge_label_map_proto.pbtxt:
--------------------------------------------------------------------------------
   1 | # -*- protobuffer -*-
   2 | # LabelMap from ImageNet 2012 full data set UID to int32 target class.
   3 | entry {
   4 |   target_class: 449
   5 |   target_class_string: "n01440764"
   6 | }
   7 | entry {
   8 |   target_class: 450
   9 |   target_class_string: "n01443537"
  10 | }
  11 | entry {
  12 |   target_class: 442
  13 |   target_class_string: "n01484850"
  14 | }
  15 | entry {
  16 |   target_class: 443
  17 |   target_class_string: "n01491361"
  18 | }
  19 | entry {
  20 |   target_class: 444
  21 |   target_class_string: "n01494475"
  22 | }
  23 | entry {
  24 |   target_class: 445
  25 |   target_class_string: "n01496331"
  26 | }
  27 | entry {
  28 |   target_class: 446
  29 |   target_class_string: "n01498041"
  30 | }
  31 | entry {
  32 |   target_class: 383
  33 |   target_class_string: "n01514668"
  34 | }
  35 | entry {
  36 |   target_class: 384
  37 |   target_class_string: "n01514859"
  38 | }
  39 | entry {
  40 |   target_class: 385
  41 |   target_class_string: "n01518878"
  42 | }
  43 | entry {
  44 |   target_class: 386
  45 |   target_class_string: "n01530575"
  46 | }
  47 | entry {
  48 |   target_class: 387
  49 |   target_class_string: "n01531178"
  50 | }
  51 | entry {
  52 |   target_class: 388
  53 |   target_class_string: "n01532829"
  54 | }
  55 | entry {
  56 |   target_class: 389
  57 |   target_class_string: "n01534433"
  58 | }
  59 | entry {
  60 |   target_class: 390
  61 |   target_class_string: "n01537544"
  62 | }
  63 | entry {
  64 |   target_class: 391
  65 |   target_class_string: "n01558993"
  66 | }
  67 | entry {
  68 |   target_class: 392
  69 |   target_class_string: "n01560419"
  70 | }
  71 | entry {
  72 |   target_class: 393
  73 |   target_class_string: "n01580077"
  74 | }
  75 | entry {
  76 |   target_class: 394
  77 |   target_class_string: "n01582220"
  78 | }
  79 | entry {
  80 |   target_class: 395
  81 |   target_class_string: "n01592084"
  82 | }
  83 | entry {
  84 |   target_class: 396
  85 |   target_class_string: "n01601694"
  86 | }
  87 | entry {
  88 |   target_class: 397
  89 |   target_class_string: "n01608432"
  90 | }
  91 | entry {
  92 |   target_class: 398
  93 |   target_class_string: "n01614925"
  94 | }
  95 | entry {
  96 |   target_class: 399
  97 |   target_class_string: "n01616318"
  98 | }
  99 | entry {
 100 |   target_class: 400
 101 |   target_class_string: "n01622779"
 102 | }
 103 | entry {
 104 |   target_class: 494
 105 |   target_class_string: "n01629819"
 106 | }
 107 | entry {
 108 |   target_class: 495
 109 |   target_class_string: "n01630670"
 110 | }
 111 | entry {
 112 |   target_class: 496
 113 |   target_class_string: "n01631663"
 114 | }
 115 | entry {
 116 |   target_class: 497
 117 |   target_class_string: "n01632458"
 118 | }
 119 | entry {
 120 |   target_class: 498
 121 |   target_class_string: "n01632777"
 122 | }
 123 | entry {
 124 |   target_class: 499
 125 |   target_class_string: "n01641577"
 126 | }
 127 | entry {
 128 |   target_class: 500
 129 |   target_class_string: "n01644373"
 130 | }
 131 | entry {
 132 |   target_class: 501
 133 |   target_class_string: "n01644900"
 134 | }
 135 | entry {
 136 |   target_class: 458
 137 |   target_class_string: "n01664065"
 138 | }
 139 | entry {
 140 |   target_class: 459
 141 |   target_class_string: "n01665541"
 142 | }
 143 | entry {
 144 |   target_class: 460
 145 |   target_class_string: "n01667114"
 146 | }
 147 | entry {
 148 |   target_class: 461
 149 |   target_class_string: "n01667778"
 150 | }
 151 | entry {
 152 |   target_class: 462
 153 |   target_class_string: "n01669191"
 154 | }
 155 | entry {
 156 |   target_class: 463
 157 |   target_class_string: "n01675722"
 158 | }
 159 | entry {
 160 |   target_class: 464
 161 |   target_class_string: "n01677366"
 162 | }
 163 | entry {
 164 |   target_class: 465
 165 |   target_class_string: "n01682714"
 166 | }
 167 | entry {
 168 |   target_class: 466
 169 |   target_class_string: "n01685808"
 170 | }
 171 | entry {
 172 |   target_class: 467
 173 |   target_class_string: "n01687978"
 174 | }
 175 | entry {
 176 |   target_class: 468
 177 |   target_class_string: "n01688243"
 178 | }
 179 | entry {
 180 |   target_class: 469
 181 |   target_class_string: "n01689811"
 182 | }
 183 | entry {
 184 |   target_class: 470
 185 |   target_class_string: "n01692333"
 186 | }
 187 | entry {
 188 |   target_class: 471
 189 |   target_class_string: "n01693334"
 190 | }
 191 | entry {
 192 |   target_class: 472
 193 |   target_class_string: "n01694178"
 194 | }
 195 | entry {
 196 |   target_class: 473
 197 |   target_class_string: "n01695060"
 198 | }
 199 | entry {
 200 |   target_class: 475
 201 |   target_class_string: "n01697457"
 202 | }
 203 | entry {
 204 |   target_class: 476
 205 |   target_class_string: "n01698640"
 206 | }
 207 | entry {
 208 |   target_class: 474
 209 |   target_class_string: "n01704323"
 210 | }
 211 | entry {
 212 |   target_class: 477
 213 |   target_class_string: "n01728572"
 214 | }
 215 | entry {
 216 |   target_class: 478
 217 |   target_class_string: "n01728920"
 218 | }
 219 | entry {
 220 |   target_class: 479
 221 |   target_class_string: "n01729322"
 222 | }
 223 | entry {
 224 |   target_class: 480
 225 |   target_class_string: "n01729977"
 226 | }
 227 | entry {
 228 |   target_class: 481
 229 |   target_class_string: "n01734418"
 230 | }
 231 | entry {
 232 |   target_class: 482
 233 |   target_class_string: "n01735189"
 234 | }
 235 | entry {
 236 |   target_class: 483
 237 |   target_class_string: "n01737021"
 238 | }
 239 | entry {
 240 |   target_class: 484
 241 |   target_class_string: "n01739381"
 242 | }
 243 | entry {
 244 |   target_class: 485
 245 |   target_class_string: "n01740131"
 246 | }
 247 | entry {
 248 |   target_class: 486
 249 |   target_class_string: "n01742172"
 250 | }
 251 | entry {
 252 |   target_class: 487
 253 |   target_class_string: "n01744401"
 254 | }
 255 | entry {
 256 |   target_class: 488
 257 |   target_class_string: "n01748264"
 258 | }
 259 | entry {
 260 |   target_class: 489
 261 |   target_class_string: "n01749939"
 262 | }
 263 | entry {
 264 |   target_class: 490
 265 |   target_class_string: "n01751748"
 266 | }
 267 | entry {
 268 |   target_class: 491
 269 |   target_class_string: "n01753488"
 270 | }
 271 | entry {
 272 |   target_class: 492
 273 |   target_class_string: "n01755581"
 274 | }
 275 | entry {
 276 |   target_class: 493
 277 |   target_class_string: "n01756291"
 278 | }
 279 | entry {
 280 |   target_class: 601
 281 |   target_class_string: "n01768244"
 282 | }
 283 | entry {
 284 |   target_class: 602
 285 |   target_class_string: "n01770081"
 286 | }
 287 | entry {
 288 |   target_class: 603
 289 |   target_class_string: "n01770393"
 290 | }
 291 | entry {
 292 |   target_class: 604
 293 |   target_class_string: "n01773157"
 294 | }
 295 | entry {
 296 |   target_class: 605
 297 |   target_class_string: "n01773549"
 298 | }
 299 | entry {
 300 |   target_class: 606
 301 |   target_class_string: "n01773797"
 302 | }
 303 | entry {
 304 |   target_class: 607
 305 |   target_class_string: "n01774384"
 306 | }
 307 | entry {
 308 |   target_class: 608
 309 |   target_class_string: "n01774750"
 310 | }
 311 | entry {
 312 |   target_class: 609
 313 |   target_class_string: "n01775062"
 314 | }
 315 | entry {
 316 |   target_class: 610
 317 |   target_class_string: "n01776313"
 318 | }
 319 | entry {
 320 |   target_class: 611
 321 |   target_class_string: "n01784675"
 322 | }
 323 | entry {
 324 |   target_class: 401
 325 |   target_class_string: "n01795545"
 326 | }
 327 | entry {
 328 |   target_class: 402
 329 |   target_class_string: "n01796340"
 330 | }
 331 | entry {
 332 |   target_class: 403
 333 |   target_class_string: "n01797886"
 334 | }
 335 | entry {
 336 |   target_class: 404
 337 |   target_class_string: "n01798484"
 338 | }
 339 | entry {
 340 |   target_class: 405
 341 |   target_class_string: "n01806143"
 342 | }
 343 | entry {
 344 |   target_class: 406
 345 |   target_class_string: "n01806567"
 346 | }
 347 | entry {
 348 |   target_class: 407
 349 |   target_class_string: "n01807496"
 350 | }
 351 | entry {
 352 |   target_class: 408
 353 |   target_class_string: "n01817953"
 354 | }
 355 | entry {
 356 |   target_class: 409
 357 |   target_class_string: "n01818515"
 358 | }
 359 | entry {
 360 |   target_class: 410
 361 |   target_class_string: "n01819313"
 362 | }
 363 | entry {
 364 |   target_class: 411
 365 |   target_class_string: "n01820546"
 366 | }
 367 | entry {
 368 |   target_class: 412
 369 |   target_class_string: "n01824575"
 370 | }
 371 | entry {
 372 |   target_class: 413
 373 |   target_class_string: "n01828970"
 374 | }
 375 | entry {
 376 |   target_class: 414
 377 |   target_class_string: "n01829413"
 378 | }
 379 | entry {
 380 |   target_class: 415
 381 |   target_class_string: "n01833805"
 382 | }
 383 | entry {
 384 |   target_class: 416
 385 |   target_class_string: "n01843065"
 386 | }
 387 | entry {
 388 |   target_class: 417
 389 |   target_class_string: "n01843383"
 390 | }
 391 | entry {
 392 |   target_class: 418
 393 |   target_class_string: "n01847000"
 394 | }
 395 | entry {
 396 |   target_class: 419
 397 |   target_class_string: "n01855032"
 398 | }
 399 | entry {
 400 |   target_class: 420
 401 |   target_class_string: "n01855672"
 402 | }
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3504 |   target_class: 349
3505 |   target_class_string: "n04487394"
3506 | }
3507 | entry {
3508 |   target_class: 765
3509 |   target_class_string: "n04493381"
3510 | }
3511 | entry {
3512 |   target_class: 727
3513 |   target_class_string: "n04501370"
3514 | }
3515 | entry {
3516 |   target_class: 544
3517 |   target_class_string: "n04505470"
3518 | }
3519 | entry {
3520 |   target_class: 220
3521 |   target_class_string: "n04507155"
3522 | }
3523 | entry {
3524 |   target_class: 292
3525 |   target_class_string: "n04509417"
3526 | }
3527 | entry {
3528 |   target_class: 334
3529 |   target_class_string: "n04515003"
3530 | }
3531 | entry {
3532 |   target_class: 666
3533 |   target_class_string: "n04517823"
3534 | }
3535 | entry {
3536 |   target_class: 874
3537 |   target_class_string: "n04522168"
3538 | }
3539 | entry {
3540 |   target_class: 990
3541 |   target_class_string: "n04523525"
3542 | }
3543 | entry {
3544 |   target_class: 969
3545 |   target_class_string: "n04525038"
3546 | }
3547 | entry {
3548 |   target_class: 558
3549 |   target_class_string: "n04525305"
3550 | }
3551 | entry {
3552 |   target_class: 790
3553 |   target_class_string: "n04532106"
3554 | }
3555 | entry {
3556 |   target_class: 682
3557 |   target_class_string: "n04532670"
3558 | }
3559 | entry {
3560 |   target_class: 343
3561 |   target_class_string: "n04536866"
3562 | }
3563 | entry {
3564 |   target_class: 936
3565 |   target_class_string: "n04540053"
3566 | }
3567 | entry {
3568 |   target_class: 665
3569 |   target_class_string: "n04542943"
3570 | }
3571 | entry {
3572 |   target_class: 524
3573 |   target_class_string: "n04548280"
3574 | }
3575 | entry {
3576 |   target_class: 928
3577 |   target_class_string: "n04548362"
3578 | }
3579 | entry {
3580 |   target_class: 317
3581 |   target_class_string: "n04550184"
3582 | }
3583 | entry {
3584 |   target_class: 231
3585 |   target_class_string: "n04552348"
3586 | }
3587 | entry {
3588 |   target_class: 906
3589 |   target_class_string: "n04553703"
3590 | }
3591 | entry {
3592 |   target_class: 669
3593 |   target_class_string: "n04554684"
3594 | }
3595 | entry {
3596 |   target_class: 958
3597 |   target_class_string: "n04557648"
3598 | }
3599 | entry {
3600 |   target_class: 819
3601 |   target_class_string: "n04560804"
3602 | }
3603 | entry {
3604 |   target_class: 795
3605 |   target_class_string: "n04562935"
3606 | }
3607 | entry {
3608 |   target_class: 772
3609 |   target_class_string: "n04579145"
3610 | }
3611 | entry {
3612 |   target_class: 502
3613 |   target_class_string: "n04579432"
3614 | }
3615 | entry {
3616 |   target_class: 899
3617 |   target_class_string: "n04584207"
3618 | }
3619 | entry {
3620 |   target_class: 912
3621 |   target_class_string: "n04589890"
3622 | }
3623 | entry {
3624 |   target_class: 904
3625 |   target_class_string: "n04590129"
3626 | }
3627 | entry {
3628 |   target_class: 935
3629 |   target_class_string: "n04591157"
3630 | }
3631 | entry {
3632 |   target_class: 831
3633 |   target_class_string: "n04591713"
3634 | }
3635 | entry {
3636 |   target_class: 503
3637 |   target_class_string: "n04592741"
3638 | }
3639 | entry {
3640 |   target_class: 672
3641 |   target_class_string: "n04596742"
3642 | }
3643 | entry {
3644 |   target_class: 951
3645 |   target_class_string: "n04597913"
3646 | }
3647 | entry {
3648 |   target_class: 815
3649 |   target_class_string: "n04599235"
3650 | }
3651 | entry {
3652 |   target_class: 723
3653 |   target_class_string: "n04604644"
3654 | }
3655 | entry {
3656 |   target_class: 248
3657 |   target_class_string: "n04606251"
3658 | }
3659 | entry {
3660 |   target_class: 240
3661 |   target_class_string: "n04612504"
3662 | }
3663 | entry {
3664 |   target_class: 714
3665 |   target_class_string: "n04613696"
3666 | }
3667 | entry {
3668 |   target_class: 553
3669 |   target_class_string: "n06359193"
3670 | }
3671 | entry {
3672 |   target_class: 930
3673 |   target_class_string: "n06596364"
3674 | }
3675 | entry {
3676 |   target_class: 791
3677 |   target_class_string: "n06785654"
3678 | }
3679 | entry {
3680 |   target_class: 932
3681 |   target_class_string: "n06794110"
3682 | }
3683 | entry {
3684 |   target_class: 861
3685 |   target_class_string: "n06874185"
3686 | }
3687 | entry {
3688 |   target_class: 774
3689 |   target_class_string: "n07248320"
3690 | }
3691 | entry {
3692 |   target_class: 803
3693 |   target_class_string: "n07565083"
3694 | }
3695 | entry {
3696 |   target_class: 754
3697 |   target_class_string: "n07579787"
3698 | }
3699 | entry {
3700 |   target_class: 813
3701 |   target_class_string: "n07583066"
3702 | }
3703 | entry {
3704 |   target_class: 844
3705 |   target_class_string: "n07584110"
3706 | }
3707 | entry {
3708 |   target_class: 771
3709 |   target_class_string: "n07590611"
3710 | }
3711 | entry {
3712 |   target_class: 793
3713 |   target_class_string: "n07613480"
3714 | }
3715 | entry {
3716 |   target_class: 974
3717 |   target_class_string: "n07614500"
3718 | }
3719 | entry {
3720 |   target_class: 968
3721 |   target_class_string: "n07615774"
3722 | }
3723 | entry {
3724 |   target_class: 873
3725 |   target_class_string: "n07684084"
3726 | }
3727 | entry {
3728 |   target_class: 768
3729 |   target_class_string: "n07693725"
3730 | }
3731 | entry {
3732 |   target_class: 975
3733 |   target_class_string: "n07695742"
3734 | }
3735 | entry {
3736 |   target_class: 993
3737 |   target_class_string: "n07697313"
3738 | }
3739 | entry {
3740 |   target_class: 885
3741 |   target_class_string: "n07697537"
3742 | }
3743 | entry {
3744 |   target_class: 734
3745 |   target_class_string: "n07711569"
3746 | }
3747 | entry {
3748 |   target_class: 736
3749 |   target_class_string: "n07714571"
3750 | }
3751 | entry {
3752 |   target_class: 737
3753 |   target_class_string: "n07714990"
3754 | }
3755 | entry {
3756 |   target_class: 738
3757 |   target_class_string: "n07715103"
3758 | }
3759 | entry {
3760 |   target_class: 739
3761 |   target_class_string: "n07716358"
3762 | }
3763 | entry {
3764 |   target_class: 740
3765 |   target_class_string: "n07716906"
3766 | }
3767 | entry {
3768 |   target_class: 741
3769 |   target_class_string: "n07717410"
3770 | }
3771 | entry {
3772 |   target_class: 742
3773 |   target_class_string: "n07717556"
3774 | }
3775 | entry {
3776 |   target_class: 743
3777 |   target_class_string: "n07718472"
3778 | }
3779 | entry {
3780 |   target_class: 744
3781 |   target_class_string: "n07718747"
3782 | }
3783 | entry {
3784 |   target_class: 735
3785 |   target_class_string: "n07720875"
3786 | }
3787 | entry {
3788 |   target_class: 745
3789 |   target_class_string: "n07730033"
3790 | }
3791 | entry {
3792 |   target_class: 746
3793 |   target_class_string: "n07734744"
3794 | }
3795 | entry {
3796 |   target_class: 318
3797 |   target_class_string: "n07742313"
3798 | }
3799 | entry {
3800 |   target_class: 229
3801 |   target_class_string: "n07745940"
3802 | }
3803 | entry {
3804 |   target_class: 319
3805 |   target_class_string: "n07747607"
3806 | }
3807 | entry {
3808 |   target_class: 320
3809 |   target_class_string: "n07749582"
3810 | }
3811 | entry {
3812 |   target_class: 321
3813 |   target_class_string: "n07753113"
3814 | }
3815 | entry {
3816 |   target_class: 322
3817 |   target_class_string: "n07753275"
3818 | }
3819 | entry {
3820 |   target_class: 323
3821 |   target_class_string: "n07753592"
3822 | }
3823 | entry {
3824 |   target_class: 324
3825 |   target_class_string: "n07754684"
3826 | }
3827 | entry {
3828 |   target_class: 325
3829 |   target_class_string: "n07760859"
3830 | }
3831 | entry {
3832 |   target_class: 326
3833 |   target_class_string: "n07768694"
3834 | }
3835 | entry {
3836 |   target_class: 816
3837 |   target_class_string: "n07802026"
3838 | }
3839 | entry {
3840 |   target_class: 999
3841 |   target_class_string: "n07831146"
3842 | }
3843 | entry {
3844 |   target_class: 953
3845 |   target_class_string: "n07836838"
3846 | }
3847 | entry {
3848 |   target_class: 864
3849 |   target_class_string: "n07860988"
3850 | }
3851 | entry {
3852 |   target_class: 806
3853 |   target_class_string: "n07871810"
3854 | }
3855 | entry {
3856 |   target_class: 948
3857 |   target_class_string: "n07873807"
3858 | }
3859 | entry {
3860 |   target_class: 830
3861 |   target_class_string: "n07875152"
3862 | }
3863 | entry {
3864 |   target_class: 900
3865 |   target_class_string: "n07880968"
3866 | }
3867 | entry {
3868 |   target_class: 798
3869 |   target_class_string: "n07892512"
3870 | }
3871 | entry {
3872 |   target_class: 947
3873 |   target_class_string: "n07920052"
3874 | }
3875 | entry {
3876 |   target_class: 859
3877 |   target_class_string: "n07930864"
3878 | }
3879 | entry {
3880 |   target_class: 823
3881 |   target_class_string: "n07932039"
3882 | }
3883 | entry {
3884 |   target_class: 361
3885 |   target_class_string: "n09193705"
3886 | }
3887 | entry {
3888 |   target_class: 992
3889 |   target_class_string: "n09229709"
3890 | }
3891 | entry {
3892 |   target_class: 359
3893 |   target_class_string: "n09246464"
3894 | }
3895 | entry {
3896 |   target_class: 365
3897 |   target_class_string: "n09256479"
3898 | }
3899 | entry {
3900 |   target_class: 368
3901 |   target_class_string: "n09288635"
3902 | }
3903 | entry {
3904 |   target_class: 366
3905 |   target_class_string: "n09332890"
3906 | }
3907 | entry {
3908 |   target_class: 363
3909 |   target_class_string: "n09399592"
3910 | }
3911 | entry {
3912 |   target_class: 364
3913 |   target_class_string: "n09421951"
3914 | }
3915 | entry {
3916 |   target_class: 367
3917 |   target_class_string: "n09428293"
3918 | }
3919 | entry {
3920 |   target_class: 360
3921 |   target_class_string: "n09468604"
3922 | }
3923 | entry {
3924 |   target_class: 362
3925 |   target_class_string: "n09472597"
3926 | }
3927 | entry {
3928 |   target_class: 954
3929 |   target_class_string: "n09835506"
3930 | }
3931 | entry {
3932 |   target_class: 848
3933 |   target_class_string: "n10148035"
3934 | }
3935 | entry {
3936 |   target_class: 982
3937 |   target_class_string: "n10565667"
3938 | }
3939 | entry {
3940 |   target_class: 330
3941 |   target_class_string: "n11879895"
3942 | }
3943 | entry {
3944 |   target_class: 357
3945 |   target_class_string: "n11939491"
3946 | }
3947 | entry {
3948 |   target_class: 358
3949 |   target_class_string: "n12057211"
3950 | }
3951 | entry {
3952 |   target_class: 331
3953 |   target_class_string: "n12144580"
3954 | }
3955 | entry {
3956 |   target_class: 327
3957 |   target_class_string: "n12267677"
3958 | }
3959 | entry {
3960 |   target_class: 328
3961 |   target_class_string: "n12620546"
3962 | }
3963 | entry {
3964 |   target_class: 332
3965 |   target_class_string: "n12768682"
3966 | }
3967 | entry {
3968 |   target_class: 886
3969 |   target_class_string: "n12985857"
3970 | }
3971 | entry {
3972 |   target_class: 913
3973 |   target_class_string: "n12998815"
3974 | }
3975 | entry {
3976 |   target_class: 956
3977 |   target_class_string: "n13037406"
3978 | }
3979 | entry {
3980 |   target_class: 893
3981 |   target_class_string: "n13040303"
3982 | }
3983 | entry {
3984 |   target_class: 878
3985 |   target_class_string: "n13044778"
3986 | }
3987 | entry {
3988 |   target_class: 812
3989 |   target_class_string: "n13052670"
3990 | }
3991 | entry {
3992 |   target_class: 981
3993 |   target_class_string: "n13054560"
3994 | }
3995 | entry {
3996 |   target_class: 329
3997 |   target_class_string: "n13133613"
3998 | }
3999 | entry {
4000 |   target_class: 889
4001 |   target_class_string: "n15075141"
4002 | }
4003 | 


--------------------------------------------------------------------------------
/image_classification_service/imagenet/node_lookup.py:
--------------------------------------------------------------------------------
 1 | # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
 2 | #
 3 | # Licensed under the Apache License, Version 2.0 (the "License");
 4 | # you may not use this file except in compliance with the License.
 5 | # You may obtain a copy of the License at
 6 | #
 7 | #     http://www.apache.org/licenses/LICENSE-2.0
 8 | #
 9 | # Unless required by applicable law or agreed to in writing, software
10 | # distributed under the License is distributed on an "AS IS" BASIS,
11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 | # See the License for the specific language governing permissions and
13 | # limitations under the License.
14 | # ==============================================================================
15 | 
16 | # NOTE: This file was altered from the original classify_image.py Tensorflow Imagenet Tutorial
17 | 
18 | import logging
19 | import re
20 | from pathlib import Path
21 | 
22 | import tensorflow as tf
23 | 
24 | logger = logging.getLogger(__name__)
25 | 
26 | AGENT_DIRECTORY = Path(__file__).parent
27 | 
28 | 
29 | class NodeLookup(object):
30 |     """Converts integer node ID's to human readable labels."""
31 | 
32 |     def __init__(self, label_lookup_path=None, uid_lookup_path=None):
33 | 
34 |         model_directory = AGENT_DIRECTORY.joinpath('model_data')
35 | 
36 |         label_lookup_path = str(model_directory.joinpath('imagenet_2012_challenge_label_map_proto.pbtxt'))
37 |         if not tf.gfile.Exists(label_lookup_path):
38 |             tf.logging.fatal('Missing Label file %s', label_lookup_path)
39 | 
40 |         uid_lookup_path = str(model_directory.joinpath('imagenet_synset_to_human_label_map.txt'))
41 |         if not tf.gfile.Exists(uid_lookup_path):
42 |             tf.logging.fatal('Missing UID Lookup file %s', uid_lookup_path)
43 | 
44 |         # Loads mapping from string UID to human-readable string
45 |         proto_as_ascii_lines = tf.gfile.GFile(uid_lookup_path).readlines()
46 |         uid_to_human = {}
47 |         p = re.compile(r'[n\d]*[ \S,]*')
48 |         for line in proto_as_ascii_lines:
49 |             parsed_items = p.findall(line)
50 |             uid = parsed_items[0]
51 |             human_string = parsed_items[2]
52 |             uid_to_human[uid] = human_string
53 | 
54 |         # Loads mapping from string UID to integer node ID.
55 |         node_id_to_uid = {}
56 |         proto_as_ascii = tf.gfile.GFile(label_lookup_path).readlines()
57 |         target_class = ''
58 |         for line in proto_as_ascii:
59 |             if line.startswith('  target_class:'):
60 |                 target_class = int(line.split(': ')[1])
61 |             if line.startswith('  target_class_string:'):
62 |                 target_class_string = line.split(': ')[1]
63 |                 node_id_to_uid[target_class] = target_class_string[1:-2]
64 | 
65 |         # Loads the final mapping of integer node ID to human-readable string
66 |         self.node_id_to_name = {}
67 |         for key, val in node_id_to_uid.items():
68 |             if val not in uid_to_human:
69 |                 tf.logging.fatal('Failed to locate: %s', val)
70 |             name = uid_to_human[val]
71 |             self.node_id_to_name[key] = name
72 | 
73 |     def id_to_string(self, node_id):
74 |         if node_id not in self.node_id_to_name:
75 |             return ''
76 |         return self.node_id_to_name[node_id]
77 | 


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | aiohttp==3.4.4
2 | jsonrpcclient==2.5.2
3 | jsonrpcserver==3.5.6
4 | requests==2.20.0
5 | tensorflow==1.3.0
6 | 


--------------------------------------------------------------------------------
/scripts/build-docker:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env python3
 2 | 
 3 | import pathlib
 4 | import subprocess
 5 | 
 6 | 
 7 | def main():
 8 |     dockerfile_path = pathlib.Path(__file__).absolute().parent.parent
 9 |     subprocess.call(["docker", "build", ".", "-t", "singularitynet/example-service:latest"], cwd=dockerfile_path)
10 | 
11 | 
12 | if __name__ == "__main__":
13 |     main()
14 | 


--------------------------------------------------------------------------------
/scripts/run-snet-service:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env python3
 2 | 
 3 | import pathlib
 4 | import subprocess
 5 | import signal
 6 | import time
 7 | 
 8 | 
 9 | def main():
10 |     def handle_signal(signum, frame):
11 |         snetd_p.send_signal(signum)
12 |         service_p.send_signal(signum)
13 |         snetd_p.wait()
14 |         service_p.wait()
15 |         exit(0)
16 | 
17 |     signal.signal(signal.SIGTERM, handle_signal)
18 |     signal.signal(signal.SIGINT, handle_signal)
19 | 
20 |     root_path = pathlib.Path(__file__).absolute().parent.parent
21 |     snetd_p = start_snetd(root_path)
22 |     service_p = start_service(root_path)
23 | 
24 |     while True:
25 |         if snetd_p.poll() is not None:
26 |             snetd_p = start_snetd(root_path)
27 |         if service_p.poll() is not None:
28 |             service_p = start_service(root_path)
29 |         time.sleep(5)
30 | 
31 | 
32 | def start_snetd(cwd):
33 |     return subprocess.Popen(["./snetd-linux-amd64"], cwd=cwd)
34 | 
35 | 
36 | def start_service(cwd):
37 |     return subprocess.Popen(["python3.6", "image_classification_service"], cwd=cwd)
38 | 
39 | 
40 | if __name__ == "__main__":
41 |     main()
42 | 


--------------------------------------------------------------------------------
/scripts/test-call:
--------------------------------------------------------------------------------
  1 | #!/usr/bin/env python3
  2 | 
  3 | import jsonrpcclient
  4 | from pathlib import Path
  5 | import sys
  6 | sys.path.append(str(Path(__file__).absolute().parent.parent))
  7 | from image_classification_service import configuration as config
  8 | 
  9 | 
 10 | bucket_image_64 = '/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEAAkGBxAQEBUQEhAQFRUQEg8SEA8VEBUQFRAPFRUWFhUVFRUYHSggGBolGxUVITEhJSkr' \
 11 |                   + 'Li4uFx8zODMtNygtLisBCgoKDg0OFxAQGi0lHR0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0t' \
 12 |                   + 'LS0tLf/AABEIAOEA4QMBEQACEQEDEQH/xAAbAAEAAgMBAQAAAAAAAAAAAAAAAgMBBQYEB//EAEEQAAIBAgIHBAgEBAMJAAAAAAAB' \
 13 |                   + 'AgMRBCEFBhIxQVFhInGBkRMyUmKhscHRFEJykkOC4fAHU/EVFhcjM1RjotL/xAAaAQEBAQEBAQEAAAAAAAAAAAAAAQIDBQQG/8QA' \
 14 |                   + 'LBEBAQABAwMEAQMDBQAAAAAAAAECAwQREiExBRNBUSIyYaEVcZEjUoGx8P/aAAwDAQACEQMRAD8A+4gAAAAAAAAAAAAAAAAAAAAA' \
 15 |                   + 'AAAAAAAAAAAAAAAAAAAAAAAGGwK54iC3zgu+SQZuUnyqlpGgt9an++P3Ce5h9xB6Xw6/jU/3Icp72n9xH/bOG/zqfmOU97T+4ktL' \
 16 |                   + 'Yd/xqf7kOV97D7iyOPovdVp/vQX3MftdGtF7pRfc0w1zEwoAAAAAAAAAAAAAAAAAGB4cTpahT9apG/Jdp/AcuWWthj5rUYvXGhD1' \
 17 |                   + 'Yyl1bUUTl8+e+wx8NHjNfJ7o7Ee5bT+Ji6kj5M/Uvpp8RrhiJfxZ+D2fkZurHy5eoZ35a+tpytPfOT75NmLquN3Wd+Xnljqj4k9y' \
 18 |                   + 'se7lUPxM+bJ11OvI9NLmx106qyq0uZeunVU44qfTyLNStddWLGy5R8mX3KvuVNaSa/L5SaNTUX37HqpadnHdOqu6dy+5HWbrKfNb' \
 19 |                   + 'DDa211urS/njf7l647Y7/P7bWhrtUXrRpyXFrJ/34GuX0Y+oWeY22E1woT9aMo9cpL7l5fRhvtPLy3GF0pQq+pUi3yvZ+TK+nHVw' \
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 27 |                   + 'DOOrjz3fBu9Pn840iifM+LhJILwykGuEkF4SQaSTCs3Cs3KMoKyVWbgCjJVZuAAFAIBWQAGYQcnZK7e5Fk5JLe0bmhS2IqPLe+b4' \
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 29 |                   + '6dl7j3fyv6Hz56PPeOGe3+cf8NVUpOLtJNPk1Y+e42eXzXGztUSIAZuFZuFLgSTKrNwrNyqzcDJeVZuUAMlAAAuBko9NHBSlv7K6' \
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 80 |                   + 'AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD//2Q=='
 81 | 
 82 | cup_image_64 = '/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEAAkGBxAPDw0PDQ0PDg0PDQ0PDQ0PDQ8ODQ0NFRIWFhUSExUYHyghGB4lJxMWITEhJSor' \
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100 |                + '1P8AC802tipl0lp/sctrUj3UvvEfY4/inUXkjedJrcWSee1NRinHM/epv8io4HUWre2ovjiYx31WovjiY2mMd8k2pvHumGtyOy4l' \
101 |                + '0O1ugwXnXY6xvetaXpkjJS0RTaNp8fKPGHH6iNpUY9lmy5ZasCiUJlAJhMKd1UAyNNG9ofS/VTwzuOG4rTG1s8zln29nwr8v2vn7' \
102 |                + 'olwy2q1enwUjnkyRX3R5z9kRMvqzSYK4sePHSNqY6UpWPZWsbQir4jc3BIjdIAAAAAAAAAAAAAAAANV0m4VGs0ubBPjakzjn2ZI5' \
103 |                + '1l8x8b0VsOTJS9drVtatonymJ2fWEw8f65OjG141uGm9cnLP2a8q5IjlafZv84XDXit1qWTnpsxpEUShMqQSrqt7tl0f4Xk1eoxY' \
104 |                + 'MUb3yWiPbFY352n0jxQeudRnAezGXX5K7bTOHTzPtmI7do+O3xevd40PCNPTS4MOnxRtjxUiseU2nztPrM82dXNuK2PeJ7xg1uuR' \
105 |                + 'YGZFlcSxK2X6SC8IhIAAAAAAAAAAAAAACm9ItExaImJ8YmN4mFQDlOK9XfCtVM2y6GlbT9fDfJgn9yYhodR1M8Jn6P4VT0jUzaP3' \
106 |                + 'ol6SpsDyfN1K6D6up1cfexz/ALWPHUvoonnqdVMe/HH8nrlqLU4geZYOqDhlfpVz5PztRav8OzpODdEtJo940unri35WtG83mPW0' \
107 |                + 'zM/tdT3SYxA11NIvV07N7tVFAY1MK53a92U9kFqtF2tVUQkBKEgAAAAAAAAAAAAAAAAI2SApmDZUAp2TskBGxskBAkBAkAAAAAAA' \
108 |                + 'AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB//2Q=='
109 | 
110 | if __name__ == '__main__':
111 |     jsonrpcclient.request("http://127.0.0.1:{}".format(config.SERVER_PORT), "classify", image_type="jpg", image=bucket_image_64)
112 |     jsonrpcclient.request("http://127.0.0.1:{}".format(config.SERVER_PORT), "classify", image_type="jpg", image=cup_image_64)
113 | 


--------------------------------------------------------------------------------
/service.json:
--------------------------------------------------------------------------------
 1 | {
 2 |     "name": "ExampleService",
 3 |     "service_spec": "service_spec",
 4 |     "organization": "SingularityNET",
 5 |     "path": "",
 6 |     "price": 1000000,
 7 |     "endpoint": "http://18.233.195.25:8080",
 8 |     "tags": [
 9 |         "SingularityNET",
10 |         "Example",
11 |         "TensorFlow",
12 |         "Image Classification"
13 |     ],
14 |     "metadata": {
15 |         "description": "SingularityNET TensorFlow example image classification service"
16 |     },
17 |     "networks": {
18 |         "42": {
19 |             "agentAddress": "0xf2B35821409baEe26aFcC955D7a332031003D95D"
20 |         }
21 |     }
22 | }
23 | 


--------------------------------------------------------------------------------
/service_spec/ExampleService.proto:
--------------------------------------------------------------------------------
 1 | syntax = "proto3";
 2 | 
 3 | service ExampleService {
 4 |   rpc classify(ClassifyRequest) returns (ClassifyResponse);
 5 | }
 6 | 
 7 | message ClassifyRequest {
 8 |   string image_type = 1;
 9 |   string image = 2;
10 | }
11 | 
12 | message ClassifyResponse {
13 |   repeated string predictions = 1;  
14 |   repeated float confidences = 2;
15 | }
16 | 
17 | 


--------------------------------------------------------------------------------