[Colorize] Adding the service & some minor repo fixes.

.circleci/config.yml

@@ -321,6 +321,41 @@ jobs:
           docker_etcd_host_folder: singnet/etcd/${SERVICE_NAME}/
           docker_etcd_container_folder: opt/singnet/${CIRCLE_PROJECT_REPONAME}/${SERVICE_FOLDER}/etcd/
 
+  build-siggraph-colorization:
+    docker:
+      - image: circleci/python:3.6.6-node
+    working_directory: ~/singnet
+    environment:
+      SERVICE_NAME: siggraph-colorization
+      SERVICE_FOLDER: services/siggraph-colorization
+      SERVICE_RUN_COMMAND: bash -c "git pull;python3 run_colorize_service.py"
+      SERVICE_TEST_COMMAND: bash -c "sleep 10;python3 test_colorize_service.py auto"
+    steps:
+      - build_command:
+          docker_nvidia: true
+          docker_image_name: siggraph_colorization
+          docker_container_name: SIGGRAPH_COLORIZATION
+
+  deploy-siggraph-colorization:
+    docker:
+    - image: circleci/python:3.6.6-node
+    working_directory: ~/singnet
+    environment:
+      SERVICE_NAME: siggraph-colorization
+      SERVICE_FOLDER: services/siggraph-colorization
+      CERTS_FOLDER: singnet/.certs
+      SERVICE_RUN_COMMAND: bash -c "git pull;python3 run_colorize_service.py --ssl"
+      SERVICE_TEST_COMMAND: bash -c "sleep 10;python3 test_colorize_service.py auto"
+      SNETD_PORT_MAINNET: 7035
+      SNETD_PORT_ROPSTEN: 7085
+    steps:
+      - deploy_command:
+          docker_nvidia: true
+          docker_image_name: siggraph_colorization
+          docker_container_name: SIGGRAPH_COLORIZATION
+          docker_etcd_host_folder: singnet/etcd/${SERVICE_NAME}/
+          docker_etcd_container_folder: opt/singnet/${CIRCLE_PROJECT_REPONAME}/${SERVICE_FOLDER}/etcd/
+
   build-yolov3-object-detection:
     docker:
       - image: circleci/python:3.6.6-node
@@ -454,6 +489,14 @@ workflows:
             branches:
               only: master
 
+      - build-siggraph-colorization
+      - deploy-siggraph-colorization:
+          requires:
+            - build-siggraph-colorization
+          filters:
+            branches:
+              only: master
+
       - build-yolov3-object-detection
       - deploy-yolov3-object-detection:
           requires:

.gitignore

@@ -15,4 +15,5 @@ config/
 !/services/
 **/etcd/
 !/docs/assets/*.jpg
-!/docs/assets/users_guide/*.jpg
+!/docs/assets/users_guide/*.jpg
+!/docs/assets/users_guide/*.png

README.md

@@ -18,6 +18,17 @@ For more details on how to publish and test a service, select it from the list b
 
 ### Images:
 - [cntk-image-recon](services/cntk-image-recon) ([User's Guide](docs/users_guide/cntk-image-recon.md)) - This service uses ResNet152 model, trained to recognize different types of flowers and dog breeds. [[Reference](https://cntk.ai/pythondocs/CNTK_301_Image_Recognition_with_Deep_Transfer_Learning.html)]
+- [siggraph-colorization](services/siggraph-colorization) ([User's Guide](docs/users_guide/siggraph-colorization.md)) - This service learns to automatically color grayscale images with a deep network.
+    ```
+     @Article{IizukaSIGGRAPH2016,
+       author = {Satoshi Iizuka and Edgar Simo-Serra and Hiroshi Ishikawa},
+       title = {{Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification}},
+       journal = "ACM Transactions on Graphics (Proc. of SIGGRAPH 2016)",
+       year = 2016,
+       volume = 35,
+       number = 4,
+     }
+    ```
 - [yolov3-object-detection](services/yolov3-object-detection) ([User's Guide](docs/users_guide/yolov3-object-detection.md)) - This service uses YOLOv3 model to detect objects on images. [[Reference](https://pjreddie.com/darknet/yolo/)]
     ```
       @article{yolov3,
@@ -74,5 +85,6 @@ Each service is licensed as followed:
 - i3d-video-action-recognition - [Apache License 2.0](https://github.com/deepmind/kinetics-i3d/blob/master/LICENSE)
 - places365-scene-recognition - [MIT License](https://github.com/CSAILVision/places365/blob/master/LICENSE)
 - s2vt-video-captioning - [Attribution 4.0 International (CC BY 4.0)](http://creativecommons.org/licenses/by/4.0/)
+- siggraph-colorization - [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://github.com/satoshiiizuka/siggraph2016_colorization/blob/master/LICENSE)
 - yolov3-object-detection - [Public domain](https://github.com/pjreddie/darknet/blob/master/LICENSE)
 - zeta36-chess-alpha-zero - [MIT License](https://github.com/Zeta36/chess-alpha-zero/blob/master/LICENSE.txt)

docs/index.html

@@ -126,6 +126,22 @@ <h1 class="card-title pricing-card-title">Free</h1>
           </div>
         </div>
 
+        <div class="card mb-4 shadow-sm">
+          <div class="card-header">
+            <h4 class="my-0 font-weight-normal">siggraph-colorization</h4>
+          </div>
+          <div class="card-body">
+            <h1 class="card-title pricing-card-title">Free</h1>
+            <ul class="list-unstyled mt-3 mb-4">
+              <li>Gray Scale</li>
+              <li>Colorization</li>
+              <li>DNN</li>
+              <li><a href="http://iizuka.cs.tsukuba.ac.jp/projects/colorization/en/">Reference</a></li>
+            </ul>
+              <a href="users_guide/siggraph-colorization.html" class="btn btn-lg btn-block btn-outline-primary" role="button">User's Guide</a>
+          </div>
+        </div>
+
         <div class="card mb-4 shadow-sm">
           <div class="card-header">
             <h4 class="my-0 font-weight-normal">zeta36-chess-alpha-zero</h4>

docs/users_guide/cntk-image-recon.md

@@ -37,10 +37,10 @@ You can use this service from [SingularityNET DApp](http://beta.singularitynet.i
 
 You can also call the service from SingularityNET CLI (`snet`).
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel to this service:
 
 ```
-$ snet client call 0 0.00000001 54.203.198.53:7004 flowers '{"model": "ResNet152", "img_path": "https://www.fiftyflowers.com/site_files/FiftyFlowers/Image/Product/Mini-Black-Eye-bloom-350_c7d02e72.jpg"}'
+$ snet client call snet cntk-image-recon flowers '{"model": "ResNet152", "img_path": "https://www.fiftyflowers.com/site_files/FiftyFlowers/Image/Product/Mini-Black-Eye-bloom-350_c7d02e72.jpg"}'
 ...
 Read call params from cmdline...
 

docs/users_guide/i3d-video-action-recognition.md

@@ -33,10 +33,10 @@ You can use this service from [SingularityNET DApp](http://beta.singularitynet.i
 
 You can also call the service from SingularityNET CLI (`snet`).
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel to this service:
 
 ```
-$ snet client call 0 0.00000001 54.203.198.53:7005 video_action_recon '{"model": "400", "url": "http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_CricketShot_g04_c02.avi"}'
+$ snet client call snet i3d-video-action-recognition video_action_recon '{"model": "400", "url": "http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_CricketShot_g04_c02.avi"}'
 ...
 Read call params from cmdline...
 

docs/users_guide/object-detection-image-recon.md

@@ -34,10 +34,10 @@ You can use this service from [SingularityNET DApp](http://beta.singularitynet.i
 
 You can also call the service from SingularityNET CLI (`snet`).
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel  to this service:
 
 ```
-$ snet client call 0 0.00000001 54.203.198.53:7006 detect_recon '{"model_detect": "yolov3", "model_recon": "ResNet152", "img_path": "https://figopetinsurance.com/sites/default/files/styles/blog_detail/public/imagedogsman-and-dog-hiking-mountainsblog.jpg", "confidence": "0.5"}'
+$ snet client call snet object-detection-image-recon detect_recon '{"model_detect": "yolov3", "model_recon": "ResNet152", "img_path": "https://figopetinsurance.com/sites/default/files/styles/blog_detail/public/imagedogsman-and-dog-hiking-mountainsblog.jpg", "confidence": "0.5"}'
 ...
 Read call params from cmdline...
 

docs/users_guide/places365-scene-recognition.md

@@ -30,14 +30,11 @@ And returns as **output**:
 
 You can call the `places365-scene-recognition` service by installing the [SingularityNET Cli](https://github.com/singnet/snet-cli) through its `snet client call` command. Assuming you have an open channel to this service:
 
-1. Use its CHANNEL_ID (e.g.: `270`); 
-2. Specify a price in AGIs (e.g.: `0`, since its a free service);
-3. Point to the endpoint at which this service's [SNET Daemon](https://github.com/singnet/snet-daemon) listens to the blockchain waiting for client calls: `54.203.198.53:7019`. You can obtain this and other information about registered services by running `snet service print_metadata ORGANIZATION SERVICE_NAME`.
-4. Filling in the method and some input data as defined in the service's `.proto` file.
+1. Fill in the method and some input data as defined in the service's `.proto` file.
 
 Example call:
 ```
-$ snet client call 270 0 54.203.198.53:7019 recognize_scene '{"input_image":"https://static1.squarespace.com/static/564783d5e4b077901c4bdc37/t/5a823d47c83025d76ac6ddae/1518484818865/Piccolo-104.jpg?format=1500w", "predict":"io, categories"}'
+$ snet client call snet places365-scene-recognition recognize_scene '{"input_image":"https://static1.squarespace.com/static/564783d5e4b077901c4bdc37/t/5a823d47c83025d76ac6ddae/1518484818865/Piccolo-104.jpg?format=1500w", "predict":"io, categories"}'
 ...
 data: "{\"io\": \"indoor\", \"categories\": \" 0.924 -> beauty_salon, 0.006 -> gymnasium/indoor, 0.005 -> clean_room, 0.005 -> biology_laboratory, 0.004 -> chemistry_lab,\"}"
 ```

docs/users_guide/s2vt-video-captioning.md

@@ -38,10 +38,10 @@ You can use this service from [SingularityNET DApp](http://beta.singularitynet.i
 
 You can also call the service from SingularityNET CLI (`snet`).
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel to this service:
 
 ```
-$ snet client call 0 0.00000001 54.203.198.53:7007 video_cap '{"url": "http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_PlayingGuitar_g05_c01.avi", "start_time_sec": "0", "stop_time_sec": "0"}'
+$ snet client call snet s2vt-video-captioning video_cap '{"url": "http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_PlayingGuitar_g05_c01.avi", "start_time_sec": "0", "stop_time_sec": "0"}'
 ...
 Read call params from cmdline...
 

docs/users_guide/siggraph-colorization.html

@@ -0,0 +1,81 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
+    <meta name="description" content="">
+    <meta name="author" content="">
+    <link rel="shortcut icon" href="https://singularitynet.io/wp-content/uploads/2018/05/favicon.ico" />
+
+    <title>SingularityNET Service - siggraph-colorization</title>
+
+    <!-- Bootstrap core CSS -->
+    <link href="../css/bootstrap.min.css" rel="stylesheet">
+
+    <!-- Custom styles for this template -->
+    <link href="../css/pricing.css" rel="stylesheet">
+    <link href="../css/style.css" rel="stylesheet">
+  </head>
+
+  <body>
+
+    <div class="d-flex flex-column flex-md-row align-items-center p-3 px-md-4 mb-3 bg-white border-bottom shadow-sm">
+      <h5 class="my-0 mr-md-auto font-weight-normal">SingularityNET</h5>
+      <a class="btn btn-outline-primary" href="../index.html">User's Guide Hub</a>
+    </div>
+
+    <div class="pricing-header px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center">
+      <h1 class="display-4">siggraph-colorization</h1>
+      <p class="lead">Service User's Guide</p>
+    </div>
+
+    <div class="container">
+        <div id="preview"> </div>
+    </div>
+
+    <footer class="pt-4 my-md-5 pt-md-5 border-top"></footer>
+
+    <!-- Bootstrap core JavaScript
+    ================================================== -->
+    <!-- Placed at the end of the document so the pages load faster -->
+    <script src="../js/jquery-slim.min.js"></script>
+    <script src="../js/popper.min.js"></script>
+    <script src="../js/bootstrap.min.js"></script>
+    <script src="../js/holder.min.js"></script>
+    <script>
+      Holder.addTheme('thumb', {
+        bg: '#55595c',
+        fg: '#eceeef',
+        text: 'Thumbnail'
+      });
+    </script>
+        <script type="text/javascript" src="../js/showdown.min.js"></script>
+        <script>
+          function Editor(preview) {
+            this.update = function () {
+                var rawFile = new XMLHttpRequest();
+                var allText = "# Fail!";
+                rawFile.open("GET", "siggraph-colorization.md", false);
+                rawFile.onreadystatechange = function ()
+                {
+                    if(rawFile.readyState === 4)
+                    {
+                        if(rawFile.status === 200 || rawFile.status === 0)
+                        {
+                            allText = rawFile.responseText;
+                        }
+                    }
+                };
+                rawFile.send(null);
+                let converter = new showdown.Converter({ tables: true });
+                let html = converter.makeHtml(allText);
+                preview.innerHTML = converter.makeHtml(html);
+            };
+            this.update();
+          }
+          var $ = function (id) { return document.getElementById(id); };
+          new Editor($("preview"));
+        </script>
+    </body>
+    <script src="../js/bootstrap.min.js"></script>
+</html>

docs/users_guide/siggraph-colorization.md

@@ -0,0 +1,61 @@
+[issue-template]: ../../../issues/new?template=BUG_REPORT.md
+[feature-template]: ../../../issues/new?template=FEATURE_REQUEST.md
+
+![singnetlogo](../assets/singnet-logo.jpg?raw=true 'SingularityNET')
+
+# Let there be Color!
+
+This service uses [Let there be Color!](http://iizuka.cs.tsukuba.ac.jp/projects/colorization/en/) to perform colorization on grayscale images.
+
+It is part of our third party [DNN Model Services](https://github.com/singnet/dnn-model-services).
+
+### Welcome
+
+The service receives a grayscale image and uses it as an input for a pre-trained Torch model.
+
+The model was trained on the [Places dataset](http://places.csail.mit.edu/) and thus best performance is for natural outdoor images.
+
+### What’s the point?
+
+The service can colorize grayscale images.
+
+### How does it work?
+
+The user must provide the following input in order to start the service and get a response:
+
+Input:
+  - `img_input`: A grayscale image URL.
+
+You can use this service from [SingularityNET DApp](http://beta.singularitynet.io/).
+
+You can also call the service from SingularityNET CLI (`snet`).
+
+Assuming that you have an open channel to this service:
+
+```
+$ snet client call snet siggraph-colorization colorize '{"img_input": "https://snet-models.s3.amazonaws.com/bh/Colorize/carnaval.jpg"}'
+
+[Base64 Image]
+```
+
+### What to expect from this service?
+
+Input Image:
+
+![Carnaval Grayscale](../assets/users_guide/carnaval.png)
+
+
+Response:
+
+![BackpackManDog Splash 1](../assets/users_guide/carnaval_colorized.png)
+
+
+Input Image:
+
+![Carnaval Grayscale](../assets/users_guide/jucelino.png)
+
+
+Response:
+
+![BackpackManDog Splash 1](../assets/users_guide/jucelino_colorized.png)
+

docs/users_guide/yolov3-object-detection.md

@@ -34,10 +34,10 @@ You can use this service from [SingularityNET DApp](http://beta.singularitynet.i
 
 You can also call the service from SingularityNET CLI (`snet`).
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel to this service:
 
 ```
-$ snet client call 0 0.00000001 54.203.198.53:7008 detect '{"model": "yolov3", "img_path": "https://hips.hearstapps.com/amv-prod-cad-assets.s3.amazonaws.com/images/media/51/2017-10best-lead-photo-672628-s-original.jpg", "confidence": "0.5"}'
+$ snet client call snet yolov3-object-detection detect '{"model": "yolov3", "img_path": "https://hips.hearstapps.com/amv-prod-cad-assets.s3.amazonaws.com/images/media/51/2017-10best-lead-photo-672628-s-original.jpg", "confidence": "0.5"}'
 ...
 Read call params from cmdline...
 

docs/users_guide/zeta36-chess-alpha-zero.md

@@ -71,10 +71,10 @@ You can use this service from [SingularityNET DApp](http://beta.singularitynet.i
 
 You can also call the service from SingularityNET CLI (`snet`).
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel to this service:
 
 ```
-$ snet client call 0 0.00000001 54.203.198.53:7077 play '{"uid": "my_uid","move": "c2c4"}'
+$ snet client call snet zeta36-chess-alpha-zero play '{"uid": "my_uid","move": "c2c4"}'
 
 response:
 UID: my_uid

services/cntk-image-recon/README.md

@@ -1,7 +1,7 @@
 [issue-template]: ../../../../../issues/new?template=BUG_REPORT.md
 [feature-template]: ../../../../../issues/new?template=FEATURE_REQUEST.md
 
-![singnetlogo](../../../docs/assets/singnet-logo.jpg?raw=true 'SingularityNET')
+![singnetlogo](../../docs/assets/singnet-logo.jpg 'SingularityNET')
 
 # CNTK Image Recognition
 
@@ -14,7 +14,7 @@ It is part of our third party [DNN Model Services](https://github.com/singnet/dn
 ### Requirements
 
 - [Python 3.6.5](https://www.python.org/downloads/release/python-365/)
-- [Node 8+ w/npm](https://nodejs.org/en/download/)
+- [SNET CLI](https://github.com/singnet/snet-cli)
 - Pre-trained models (dogs and flowers)
 
 ### Development
@@ -125,19 +125,13 @@ Image (Link): https://cdn2-www.dogtime.com/assets/uploads/2011/01/file_22950_sta
 
 Through SingularityNET (follow this [link](https://dev.singularitynet.io/tutorials/publish/) to learn how to publish a service and open a payment channel to be able to call it):
 
-Assuming that you have an open channel (`id: 0`) to this service:
+Assuming that you have an open channel to this service:
 
 ```
 $ snet client call snet cntk-image-recon flowers '{"model": "ResNet152", "img_path": "https://www.fiftyflowers.com/site_files/FiftyFlowers/Image/Product/Mini-Black-Eye-bloom-350_c7d02e72.jpg"}'
-...
-Read call params from cmdline...
-
-Calling service...
-
-    response:
-        delta_time: '1.5536'
-        top_5: '{1: ''98.93%: sunflower'', 2: ''00.64%: black-eyed susan'', 3: ''00.16%:
-            barbeton daisy'', 4: ''00.14%: oxeye daisy'', 5: ''00.03%: daffodil''}'
+Price for this call will be 0.00000001 AGI (use -y to remove this warning). Proceed? (y/n): y
+delta_time: "2.5509"
+top_5: "{1: \'98.93%: sunflower\', 2: \'00.64%: black-eyed susan\', 3: \'00.16%: barbeton daisy\', 4: \'00.14%: oxeye daisy\', 5: \'00.03%: daffodil\'}"
 ```
 
 ## Contributing and Reporting Issues