Release/0.7.2 (#312)

Release 0.7.2
HumanSignal · Jun 11, 2020 · 95d18d4 · 95d18d4
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diff --git a/.dockerignore b/.dockerignore
@@ -1,32 +1,11 @@
-node_modules
-npm-debug.log
-Dockerfile
-.dockerignore
-build
-dist
-docs
-tests
-tox.ini
-public
-label_studio.egg-info
-.git
-.github
-.vscode
-.editorconfig
-.gitignore
-*.md
-!README.md
-*.txt
-!requirements.txt
-*.yml
-*.json
-*.pem
-.python-version
-
-# shell scripts
-update_pypi.sh
+# Ignore everything:
+**
 
-# misc folders
-tmp
-etc
-my_*
+# Except:
+!images
+!label_studio
+!scripts
+!tools
+!setup.py
+!requirements.txt
+!README.md
diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 # Label Studio &middot; ![GitHub](https://img.shields.io/github/license/heartexlabs/label-studio?logo=heartex) [![Build Status](https://travis-ci.com/heartexlabs/label-studio.svg?branch=master)](https://travis-ci.com/heartexlabs/label-studio) [![codecov](https://codecov.io/gh/heartexlabs/label-studio/branch/master/graph/badge.svg)](https://codecov.io/gh/heartexlabs/label-studio) ![GitHub release](https://img.shields.io/github/v/release/heartexlabs/label-studio?include_prereleases) &middot; :sunny:
 
-[Website](https://labelstud.io/) • [Docs](https://labelstud.io/guide) • [Twitter](https://twitter.com/heartexlabs) • [Join Slack Community <img src="https://go.heartex.net/docs/images/slack-mini.png" width="18px"/>](https://join.slack.com/t/label-studio/shared_invite/zt-cr8b7ygm-6L45z7biEBw4HXa5A2b5pw)
+[Website](https://labelstud.io/) • [Docs](https://labelstud.io/guide/) • [Twitter](https://twitter.com/heartexlabs) • [Join Slack Community <img src="https://go.heartex.net/docs/images/slack-mini.png" width="18px"/>](https://join.slack.com/t/label-studio/shared_invite/zt-cr8b7ygm-6L45z7biEBw4HXa5A2b5pw)
 
 <br/>
 

diff --git a/docs/public/search.xml b/docs/public/search.xml
diff --git a/docs/source/guide/completions.md → docs/source/guide/export.md b/docs/source/guide/completions.md → docs/source/guide/export.md
@@ -1,7 +1,7 @@
 ---
 title: Export results
 type: guide
-order: 104
+order: 105
 ---
 
 Your annotations are stored in [raw completion format](#Completion-format) inside `my_project_name/completions` directory, one file per labeled task named as `task_id.json`.

diff --git a/docs/source/guide/labeling.md b/docs/source/guide/labeling.md
@@ -1,7 +1,7 @@
 ---
 title: Labeling
 type: guide
-order: 103
+order: 104
 ---
 
 Let's explore the complex example of multi-task labeling which includes text + image + audio data objects:

diff --git a/docs/source/guide/ml.md b/docs/source/guide/ml.md
@@ -52,7 +52,36 @@ Here is a quick example tutorial on how to run the ML backend with a simple text
     label-studio start text_classification_project --init --template text_sentiment --ml-backend-url http://localhost:9090
     ```
 
+## Start with docker compose
 
+Label Studio ML scripts include everything you need to create production ready ML backend server, powered by docker. It uses [uWSGI](https://uwsgi-docs.readthedocs.io/en/latest/) + [supervisord](http://supervisord.org/) stack, and handles background training jobs using [RQ](https://python-rq.org/).
+
+After running this command:
+
+```bash
+label-studio-ml init my-ml-backend --script label_studio/ml/examples/simple_text_classifier.py
+```
+
+you'll see configs in `my-ml-backend/` directory needed to build and run docker image using docker-compose. 
+
+Some preliminaries:
+
+1. Ensure all requirements are specified in `my-ml-backend/requirements.txt` file, e.g. place
+
+    ```requirements.txt
+    scikit-learn
+    ```
+   
+2. There are no services currently running on ports 9090, 6379 (otherwise change default ports in `my-ml-backend/docker-compose.yml`)
+
+Then from `my-ml-backend/` directory run
+```bash
+docker-compose up
+```
+
+The server starts listening on port 9090, and you can connect it to Label Studio by specifying `--ml-backend http://localhost:9090`
+ or via UI on **Model** page.
+ 
 ## Create your own ML backend
 
 Check examples in `label-studio/ml/examples` directory.
diff --git a/docs/source/guide/setup.md b/docs/source/guide/setup.md
@@ -1,7 +1,7 @@
 ---
 title: Project setup
 type: guide
-order: 102
+order: 101
 ---
 
 **Project** is a directory where all annotation assets are located. It is a self-contained entity: when you start Label Studio for the first time e.g. `label-studio start ./my_project --init`,

diff --git a/docs/source/guide/storage.md b/docs/source/guide/storage.md
@@ -1,12 +1,12 @@
 ---
 title: Cloud storages
 type: guide
-order: 101
+order: 103
 ---
 
 You can integrate the popular cloud storage with Label Studio, collect new tasks uploaded to your buckets, and sync back annotation results to use them in your machine learning pipelines.
 
-Cloud storage type and bucket need to be configured during the start of the server, and further configured during the runtime via UI.
+You can configure storage type, bucket and prefixes during the start of the server or during the runtime via UI on **Tasks** page.
 
 You can configure one or both:
 
@@ -17,6 +17,8 @@ The connection to both storages is synced, so you can see new tasks after upload
 
 The parameters like prefix or matching filename regex could be changed any time from the webapp interface.
 
+> Note: Choose target storage carefully: be sure it's empty when you just start labeling project, or it contains completions that match previously created/import tasks from source storage. Tasks are synced with completions based on internal ids (keys in `source.json`/`target.json` files in your project directory), so if you accidentally connect to the target storage with existed completions with the same ids, you may fail with undefined behaviour.  
+
 ## Amazon S3
 
 To connect your [S3](https://aws.amazon.com/s3) bucket with Label Studio, be sure you have programmatic access enabled. [Check this link](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html#configuration) to learn more how to set up access to your S3 bucket.

diff --git a/docs/source/guide/tasks.md b/docs/source/guide/tasks.md
@@ -1,7 +1,7 @@
 ---
-title: Import tasks
+title: Tasks
 type: guide
-order: 101
+order: 102
 ---
 
 ## Basic format
@@ -176,6 +176,12 @@ http://<host:port>/data/filename?d=<path/to/the/local/directory>
 
 Supported formats are: `.wav` `.aiff` `.mp3` `.au` `.flac`
 
+### Upload resource files on Import page
+
+For label configs with one data key (e.g.: one input image) Label Studio supports a file uploading via GUI, 
+just drag & drop your files (or select them from file dialog) on "Import" page. 
+This option is suitable for limited file number.     
+
 
 ## Import using API
 
@@ -186,6 +192,53 @@ curl -X POST -H Content-Type:application/json http://localhost:8080/api/import \
 --data "[{\"my_key\": \"my_value_1\"}, {\"my_key\": \"my_value_2\"}]"
 ```
 
+## Retrieve tasks using API
+
+You can retrieve project settings including total task count using API in JSON format: 
+
+```json   
+http://<host:port>/api/project
+```
+
+Response example: 
+
+```json
+{
+  ... 
+  "task_count": 3,
+  ...
+}
+```
+
+To get tasks with pagination in JSON format:
+
+```
+http://<host:port>/api/tasks?page=1&page_size=10&order={-}[id|completed_at]
+```
+
+Response example:
+
+```json
+[
+  {
+    "completed_at": "2020-05-29 03:31:15", 
+    "completions": [
+      {
+        "created_at": 1590712275, 
+        "id": 10001, 
+        "lead_time": 4.0, 
+        "result": [ ... ]
+      }
+    ], 
+    "data": {
+      "image": "s3://htx-dev/dataset/training_set/dogs/dog.102.jpg"
+    }, 
+    "id": 2, 
+    "predictions": []
+  }
+]
+```
+
 ## Sampling
 
 You can define the way of how your imported tasks are exposed to annotators. Several options are available. To enable one of them, specify `--sampling=<option>` as command line option.