docs: rename github org

README.md

@@ -1,13 +1,13 @@
 <img src="https://user-images.githubusercontent.com/12534576/192582340-4c9e4401-1fe6-4dbb-95bb-fdbba5493f61.png"/>
 
-![GitHub](https://img.shields.io/github/license/heartexlabs/label-studio?logo=heartex) ![label-studio:build](https://github.com/heartexlabs/label-studio/workflows/label-studio:build/badge.svg) ![GitHub release](https://img.shields.io/github/v/release/heartexlabs/label-studio?include_prereleases)
+![GitHub](https://img.shields.io/github/license/heartexlabs/label-studio?logo=heartex) ![label-studio:build](https://github.com/HumanSignal/label-studio/workflows/label-studio:build/badge.svg) ![GitHub release](https://img.shields.io/github/v/release/heartexlabs/label-studio?include_prereleases)
 
 [Website](https://labelstud.io/) • [Docs](https://labelstud.io/guide/) • [Twitter](https://twitter.com/labelstudiohq) • [Join Slack Community <img src="https://app.heartex.ai/docs/images/slack-mini.png" width="18px"/>](https://slack.labelstud.io/?source=github-1)
 
 
 ## What is Label Studio?
 
-<!-- <a href="https://labelstud.io/blog/release-130.html"><img src="https://github.com/heartexlabs/label-studio/raw/master/docs/themes/htx/source/images/release-130/LS-Hits-v1.3.png" align="right" /></a> -->
+<!-- <a href="https://labelstud.io/blog/release-130.html"><img src="https://github.com/HumanSignal/label-studio/raw/master/docs/themes/htx/source/images/release-130/LS-Hits-v1.3.png" align="right" /></a> -->
 
 Label Studio is an open source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can be used to prepare raw data or improve existing training data to get more accurate ML models.
 
@@ -135,8 +135,8 @@ python label_studio/manage.py runserver
 
 You can deploy Label Studio with one click in Heroku, Microsoft Azure, or Google Cloud Platform: 
 
-[<img src="https://www.herokucdn.com/deploy/button.svg" height="30px">](https://heroku.com/deploy?template=https://github.com/heartexlabs/label-studio/tree/heroku-persistent-pg)
-[<img src="https://aka.ms/deploytoazurebutton" height="30px">](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Fheartexlabs%2Flabel-studio%2Fmaster%2Fazuredeploy.json)
+[<img src="https://www.herokucdn.com/deploy/button.svg" height="30px">](https://heroku.com/deploy?template=https://github.com/HumanSignal/label-studio/tree/heroku-persistent-pg)
+[<img src="https://aka.ms/deploytoazurebutton" height="30px">](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2Fhumansignal%2Flabel-studio%2Fdevelop%2Fazuredeploy.json)
 [<img src="https://deploy.cloud.run/button.svg" height="30px">](https://deploy.cloud.run)
 
 
@@ -211,7 +211,7 @@ Label Studio includes a variety of templates to help you label your data, or you
 
 Connect your favorite machine learning model using the Label Studio Machine Learning SDK. Follow these steps:
 
-1. Start your own machine learning backend server. See [more detailed instructions](https://github.com/heartexlabs/label-studio-ml-backend).
+1. Start your own machine learning backend server. See [more detailed instructions](https://github.com/HumanSignal/label-studio-ml-backend).
 2. Connect Label Studio to the server on the model page found in project settings.
 
 This lets you:

app.json

@@ -6,7 +6,7 @@
     "data labeling"
   ],
   "website": "https://labelstud.io",
-  "repository": "https://github.com/heartexlabs/label-studio",
+  "repository": "https://github.com/HumanSignal/label-studio",
   "logo": "https://labelstud.io/images/opossum/heartex_icon_opossum_green.svg",
   "stack": "container",
   "env": {

deploy/default.conf

@@ -121,7 +121,7 @@ http {
     }
 
     # LabelStudio frontend
-    # Source: https://github.com/heartexlabs/label-studio/blob/HEAD/label_studio/frontend/src
+    # Source: https://github.com/HumanSignal/label-studio/blob/HEAD/label_studio/frontend/src
     location /react-app/ {
         alias /label-studio/web/dist/apps/labelstudio/;
     }

docs/CONTRIBUTING.md

@@ -4,10 +4,10 @@ Thank you for investing your time in contributing to our project! Any contributi
 
 ## Before you start
 
-We value input from each member of the community, and we ask that you follow our [code of conduct](https://github.com/heartexlabs/label-studio/blob/master/CODE_OF_CONDUCT.md). We are a small team, but we try to respond to issues and pull requests within 2 business days. 
+We value input from each member of the community, and we ask that you follow our [code of conduct](https://github.com/HumanSignal/label-studio/blob/develop/CODE_OF_CONDUCT.md). We are a small team, but we try to respond to issues and pull requests within 2 business days. 
 
 For changes that you contribute to any of the Label Studio repositories, please do the following:
-- Review the general [contributor guidelines](https://github.com/heartexlabs/label-studio/blob/master/CONTRIBUTING.md).
+- Review the general [contributor guidelines](https://github.com/HumanSignal/label-studio/blob/develop/CONTRIBUTING.md).
 - Create issues for any major changes and enhancements that you want to make. 
 - Keep pull requests specific to one issue. Shorter pull requests are preferred and are easier to review. 
 

docs/source/guide/export.md

@@ -106,7 +106,7 @@ For a large labeling project with hundreds of thousands of tasks, do the followi
 
 ## Export formats supported by Label Studio
 
-Label Studio supports many common and standard formats for exporting completed labeling tasks. If you don't see a format that works for you, you can contribute one. For more information, see the [GitHub repository for the Label Studio Converter tool](https://github.com/heartexlabs/label-studio-converter).
+Label Studio supports many common and standard formats for exporting completed labeling tasks. If you don't see a format that works for you, you can contribute one. For more information, see the [GitHub repository for the Label Studio Converter tool](https://github.com/HumanSignal/label-studio-converter).
 
 ### ASR_MANIFEST
 
@@ -200,7 +200,7 @@ Export object detection annotations in the YOLOv3 and YOLOv4 format. Supports ob
 
 
 ## Manually convert JSON annotations to another format
-You can run the [Label Studio converter tool](https://github.com/heartexlabs/label-studio-converter) on a directory or file of completed JSON annotations using the command line or Python to convert the completed annotations from Label Studio JSON format into another format. 
+You can run the [Label Studio converter tool](https://github.com/HumanSignal/label-studio-converter) on a directory or file of completed JSON annotations using the command line or Python to convert the completed annotations from Label Studio JSON format into another format. 
 
 !!! note
     If you use versions of Label Studio earlier than 1.0.0, then this is the only way to convert your Label Studio JSON format annotations into another labeling format. 

docs/source/guide/frontend.md

@@ -14,11 +14,11 @@ section: "Integrate & Extend"
 !!! attention
     As of [Label Studio 1.11.0](https://github.com/HumanSignal/label-studio/releases/tag/1.11.0), the Label Studio frontend has been deprecated as a separate library and is no longer supported as a standalone distribution. For information about using the frontend library within Label Studio, see [the README](https://github.com/HumanSignal/label-studio/blob/develop/web/libs/editor/README.md). 
 
-The [Label Studio Frontend](https://github.com/heartexlabs/label-studio-frontend) (LSF) is the main labeling interface distributed within Label Studio and as a separate package via NPM and Unpkg. You can integrate the LSF into your projects without Label Studio to provide data labeling capabilities to your users.
+The [Label Studio Frontend](https://github.com/HumanSignal/label-studio-frontend) (LSF) is the main labeling interface distributed within Label Studio and as a separate package via NPM and Unpkg. You can integrate the LSF into your projects without Label Studio to provide data labeling capabilities to your users.
 
 LSF can be customized and extended to fit your needs, and you can use a custom version of LSF standalone or in your LS installation. For more information see [Custom LSF + LS integration](#custom-lsf-in-label-studio).
 
-LSF is located as a separate GitHub repository: https://github.com/heartexlabs/label-studio-frontend
+LSF is located as a separate GitHub repository: https://github.com/HumanSignal/label-studio-frontend
 
 <br>
 <img src="/images/frontend/lsf-in-ls.jpg" class="gif-border">
@@ -243,13 +243,13 @@ Refer to the [Frontend Reference](frontend_reference.html) when developing with
 
 ### Manual builds
 
-If you want to build a new tag or change the behaviour of default components inside of LSF, then you need to go into the LSF repo and review the [Development part](https://github.com/heartexlabs/label-studio-frontend#development) of the README file. Making any changes requires that you have a good knowledge of React and Javascript.build.js `<branch-name-from-official-lsf-repo>`
+If you want to build a new tag or change the behaviour of default components inside of LSF, then you need to go into the LSF repo and review the [Development part](https://github.com/HumanSignal/label-studio-frontend#development) of the README file. Making any changes requires that you have a good knowledge of React and Javascript.build.js `<branch-name-from-official-lsf-repo>`
 
 ### GitHub Artifacts
 
 Use GitHub Artifacts to download a zip-formatted archive with LSF builds. Branches from the official LSF repo are built automatically and hosted on GitHub Artifacts.
 
-See the [GitHub Actions for the LSF repository](https://github.com/heartexlabs/label-studio-frontend/actions) to access them.
+See the [GitHub Actions for the LSF repository](https://github.com/HumanSignal/label-studio-frontend/actions) to access them.
 
 You can also configure a GitHub token to obtain artifacts automatically:
 ```
@@ -263,14 +263,14 @@ yarn download:lsf <branch-name-from-official-lsf-repo>
 
 ## Custom LSF in Label Studio
 
-LS Frontend (LSF) with Backend (LSB) integration is similar what is described in the [Frontend integration guide](#Frontend-integration-guide). The JavaScript integration script is placed in [lsf-sdk.js](https://github.com/heartexlabs/label-studio/blob/master/label_studio/static/js/lsf-sdk.js) in the Label Studio Backend. The main idea of this integration based on LSF callbacks.
+LS Frontend (LSF) with Backend (LSB) integration is similar what is described in the [Frontend integration guide](#Frontend-integration-guide). The JavaScript integration script is placed in [lsf-sdk.js](https://github.com/HumanSignal/label-studio/blob/develop/label_studio/static/js/lsf-sdk.js) in the Label Studio Backend. The main idea of this integration based on LSF callbacks.
 
 Check out a quick guide on how to use custom LSF in Label Studio.
 
 <iframe width="800" height="500" src="https://www.youtube.com/embed/QSGgiXie2SE" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
 
 ### Prepare a custom LSF build
-1. Make your custom LSF build by following these [instructions](https://github.com/heartexlabs/label-studio-frontend#development).
+1. Make your custom LSF build by following these [instructions](https://github.com/HumanSignal/label-studio-frontend#development).
 2. Finalize your development with `npm run build:module` to generate `main.css` and `main.js` files.
 3. Confirm files appearance in the `build/static` folder.
 

docs/source/guide/install_requirements.md

@@ -122,7 +122,7 @@ python -m pip install label-studio
 If you want to use nightly builds or extend the functionality, consider downloading the source code using Git and running Label Studio locally:
 
 ```bash
-git clone https://github.com/heartexlabs/label-studio.git
+git clone https://github.com/HumanSignal/label-studio.git
 cd label-studio
 # Install all package dependencies
 pip install -e .

docs/source/guide/install_troubleshoot.md

@@ -51,7 +51,7 @@ It is advised to use non-root containers for the following reasons:
 
 - Platform limitations: Some Kubernetes distributions such as [OpenShift](https://www.openshift.com/), execute containers with random UUIDs. This method is incompatible with root containers, which must always run using the root user's UUID. In these situations, only non-root container images will operate, making them a necessity.
 
-Our [Dockerfile](https://github.com/heartexlabs/label-studio/blob/develop/Dockerfile) contains the line `USER 1001` which assigns a non-root user UID to the image, enabling the container to run as an unprivileged user. This implementation applies the security enhancements and other restrictions mentioned above to the container.
+Our [Dockerfile](https://github.com/HumanSignal/label-studio/blob/develop/Dockerfile) contains the line `USER 1001` which assigns a non-root user UID to the image, enabling the container to run as an unprivileged user. This implementation applies the security enhancements and other restrictions mentioned above to the container.
 
 ### File permissions for non-root user
 

docs/source/guide/predictions.md

@@ -687,7 +687,7 @@ You can sort the prediction scores for each labeled region using the **Regions**
 
 ## Import brush segmentation pre-annotations in RLE format
 
-If you want to import pre-annotations for brush mask image segmentation using the [BrushLabels tag](/tags/brushlabels.html), you must convert the masks to RLE format first. The [Label Studio Converter](https://github.com/heartexlabs/label-studio-converter) package has some helper functions for this. See the following for common conversion cases and guidance.
+If you want to import pre-annotations for brush mask image segmentation using the [BrushLabels tag](/tags/brushlabels.html), you must convert the masks to RLE format first. The [Label Studio Converter](https://github.com/HumanSignal/label-studio-converter) package has some helper functions for this. See the following for common conversion cases and guidance.
 
 Install Label Studio Converter:
 ```
@@ -707,15 +707,15 @@ from label_studio_converter import brush
     ```
 
 - To convert OpenCV contours, use 
-[`brush.contour2rle(contours, contour_id, img_width, img_height)`](https://github.com/heartexlabs/label-studio-converter/blob/master/label_studio_converter/brush.py#L310).
+[`brush.contour2rle(contours, contour_id, img_width, img_height)`](https://github.com/HumanSignal/label-studio-converter/blob/master/label_studio_converter/brush.py#L310).
 
 - To convert an image from path (jpg, png. bmp), use 
-[`brush.image2rle(path)`](https://github.com/heartexlabs/label-studio-converter/blob/master/label_studio_converter/brush.py#L343).
+[`brush.image2rle(path)`](https://github.com/HumanSignal/label-studio-converter/blob/master/label_studio_converter/brush.py#L343).
 
 - To prepare the pre-annotation, use 
-[`brush.image2annotation(path, label_name, from_name, to_name, ground_truth=False, model_version=None, score=None)`](https://github.com/heartexlabs/label-studio-converter/blob/master/label_studio_converter/brush.py#L361)
+[`brush.image2annotation(path, label_name, from_name, to_name, ground_truth=False, model_version=None, score=None)`](https://github.com/HumanSignal/label-studio-converter/blob/master/label_studio_converter/brush.py#L361)
 
-For more assistance, review this [example code creating a Label Studio task with pre-annotations](https://github.com/heartexlabs/label-studio-converter/blob/master/tests/test_brush.py#L11) for brush labels.
+For more assistance, review this [example code creating a Label Studio task with pre-annotations](https://github.com/HumanSignal/label-studio-converter/blob/master/tests/test_brush.py#L11) for brush labels.
 
 ## Import OCR pre-annotations 
 

docs/source/guide/setup.md

@@ -52,7 +52,7 @@ To accept a suggestion, you can click to select it, or press the Tab key while t
 
 ## Customize a template
 
-You can customize a [labeling config template](/templates) or use a custom configuration that you create from scratch using [tags](/tags). If you create a custom configuration that might be useful to other Label Studio users, consider [contributing the configuration as a template](https://github.com/heartexlabs/label-studio/tree/develop/label_studio/annotation_templates).
+You can customize a [labeling config template](/templates) or use a custom configuration that you create from scratch using [tags](/tags). If you create a custom configuration that might be useful to other Label Studio users, consider [contributing the configuration as a template](https://github.com/HumanSignal/label-studio/tree/develop/label_studio/annotation_templates).
 
 The labeling configuration for a project is an XML file that contains three types of tags specific to Label Studio.
 

docs/source/guide/start.md

@@ -115,7 +115,7 @@ docker run -it -p 9001:8080 -v $(pwd)/mydata:/label-studio/data heartexlabs/labe
 !!! attention "important"
     As this is a non-root container, the mounted files and directories must have the proper permissions for the `UID 1001`.
 
-Or, if you're using Docker Compose, update the `docker-compose.yml` file that you're using to expose a different port for the NGINX server used to proxy the connection to Label Studio. For example, this portion of the [`docker-compose.yml`](https://github.com/heartexlabs/label-studio/blob/master/docker-compose.yml) file exposes port 9001 instead of port 80 for proxying Label Studio:
+Or, if you're using Docker Compose, update the `docker-compose.yml` file that you're using to expose a different port for the NGINX server used to proxy the connection to Label Studio. For example, this portion of the [`docker-compose.yml`](https://github.com/HumanSignal/label-studio/blob/develop/docker-compose.yml) file exposes port 9001 instead of port 80 for proxying Label Studio:
 ```
 ...
 nginx:
@@ -214,7 +214,7 @@ Then you can specify the required environment variables for a PostgreSQL connect
 Our Heroku manifest uses [postgresql addon](https://elements.heroku.com/addons/heroku-postgresql) out of the box.
 Please notice that the storage capacity is limited.
 
-[<img src="https://www.herokucdn.com/deploy/button.svg" height="30px">](https://heroku.com/deploy?template=https://github.com/heartexlabs/label-studio/tree/master)
+[<img src="https://www.herokucdn.com/deploy/button.svg" height="30px">](https://heroku.com/deploy?template=https://github.com/HumanSignal/label-studio/tree/master)
 
 Please notice that all uploaded data via import will be lost after a dyno replace since [filesystem is ephemeral](https://devcenter.heroku.com/articles/dynos#ephemeral-filesystem).
 Using S3 storage is recommended.

docs/source/guide/storedata.md

@@ -55,7 +55,7 @@ MinIO is a blob storage solution that is compatible with Amazon S3. You can use
 
 ### Starting the containers
 For local development, you can host a local MinIO server to emulate an S3-based production environment more closely. 
-An example docker-compose file for this is available in the [Label Studio repository](https://github.com/heartexlabs/label-studio).
+An example docker-compose file for this is available in the [Label Studio repository](https://github.com/HumanSignal/label-studio).
 
 To run MinIO alongside your Label Studio instance, use the following command:
 ````bash
@@ -110,7 +110,7 @@ docker run -it -p 8080:8080 -v <yourvolume>:/label-studio/data heartexlabs/label
 !!! attention "important"
     As this is a non-root container, the mounted files and directories must have the proper permissions for the `UID 1001`.
 
-If you're using Docker Compose with the [config included in the Label Studio repository](https://github.com/heartexlabs/label-studio/blob/master/docker-compose.yml), you can set up Docker volumes in the `docker-compose.yml` file for Label Studio:
+If you're using Docker Compose with the [config included in the Label Studio repository](https://github.com/HumanSignal/label-studio/blob/develop/docker-compose.yml), you can set up Docker volumes in the `docker-compose.yml` file for Label Studio:
 ```
 version: "3.3"
 services: