Merge branch 'main' of https://github.com/allegroai/clearml-docs
@ -41,7 +41,7 @@ error, you are good to go.
|
||||
clearml-session
|
||||
```
|
||||
|
||||
You can add flags to set a Docker image, the remote SSH port, JupyterLab/VS Code versions, and more. See [CLI options](#command-line-options)
|
||||
You can add flags to set a container image, the remote SSH port, JupyterLab/VS Code versions, and more. See [CLI options](#command-line-options)
|
||||
for all configuration options.
|
||||
|
||||
`clearml-session` creates a new [Task](../fundamentals/task.md) that is responsible for setting up the SSH and
|
||||
@ -57,8 +57,8 @@ error, you are good to go.
|
||||
launches it.
|
||||
|
||||
1. Once the agent finishes the initial setup of the interactive Task, the local `cleaml-session` connects to the host
|
||||
machine via SSH, and tunnels both SSH and IDE over the SSH connection. If a Docker is specified, the
|
||||
IDE environment runs inside the Docker.
|
||||
machine via SSH, and tunnels both SSH and IDE over the SSH connection. If a container is specified, the
|
||||
IDE environment runs inside of it.
|
||||
|
||||
1. The CLI outputs access links to the remote JupyterLab and VS Code sessions:
|
||||
|
||||
@ -106,8 +106,8 @@ To connect to an existing session:
|
||||
1. Click on the JupyterLab / VS Code link that is outputted, or connect directly to the SSH session
|
||||
|
||||
## Features
|
||||
### Running in Docker
|
||||
To run a session inside a Docker container, use the `--docker` flag and enter the docker image to use in the interactive
|
||||
### Running in a Container
|
||||
To run a session inside a container, use the `--docker` flag and enter the image to use in the interactive
|
||||
session.
|
||||
|
||||
### Kubernetes Support
|
||||
@ -224,8 +224,8 @@ clearml-session --continue-session <session_id> --store-workspace ~/workspace
|
||||
| `--disable-fingerprint-check` | If set, bypass the remote SSH server fingerprint verification process | `none` |
|
||||
| `--disable-session-cleanup` | If `True`, previous interactive sessions are not deleted | `false`|
|
||||
| `--disable-store-defaults` | If set, do not store current setup as new default configuration| `none`|
|
||||
| `--docker`| Select the docker image to use in the interactive session |`nvidia/cuda:11.6.2-runtime-ubuntu20.04` or previously used docker image|
|
||||
| `--docker-args` | Add additional arguments for the docker image to use in the interactive session | `none` or the previously used docker-args |
|
||||
| `--docker`| Select the image to use in the interactive session |`nvidia/cuda:11.6.2-runtime-ubuntu20.04` or previously used image|
|
||||
| `--docker-args` | Add additional arguments for the docker image to use in the interactive session | `none` or the previously used `docker-args` |
|
||||
| `--force_dropbear`| Force using `dropbear` instead of SSHd |`none`|
|
||||
| `--git-credentials` | If `True`, local `.git-credentials` file is sent to the interactive session.| `false`|
|
||||
| `--init-script` | Specify a BASH init script file to be executed when the interactive session is being set up | `none` or previously entered BASH script |
|
||||
|
||||
@ -18,7 +18,7 @@ line arguments, Python module dependencies, and a requirements.txt file!
|
||||
## How Does ClearML Task Work?
|
||||
|
||||
1. Execute `clearml-task`, specifying the ClearML target project and task name, along with your script (and repository / commit / branch).
|
||||
Optionally, specify an execution queue and Docker image to use.
|
||||
Optionally, specify an execution queue and container image to use.
|
||||
1. `clearml-task` does its magic! It creates a new [ClearML Task](../fundamentals/task.md),
|
||||
and, if so directed, enqueues it for execution by a ClearML Agent.
|
||||
1. While the Task is running on the remote machine, all its console outputs are logged in real-time, alongside your
|
||||
@ -26,9 +26,9 @@ line arguments, Python module dependencies, and a requirements.txt file!
|
||||
(a link to your task details page in the ClearML Web UI is printed as ClearML Task creates the task).
|
||||
|
||||
## Execution Configuration
|
||||
### Docker
|
||||
Specify a Docker container to run the code in with the `--docker <docker_image>` option.
|
||||
The ClearML Agent pulls it from Docker Hub or a Docker artifactory automatically.
|
||||
### Container
|
||||
Specify a container to run the code in with the `--docker <image>` option.
|
||||
The ClearML Agent pulls it from Docker Hub or a container artifactory automatically.
|
||||
|
||||
### Package Dependencies
|
||||
`clearml-task` automatically finds the `requirements.txt` file in remote repositories.
|
||||
@ -61,8 +61,8 @@ errors in identifying the correct default branch.
|
||||
| `--branch` | Select repository branch / tag. By default, latest commit from the master branch | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--commit` | Select commit ID to use. By default, latest commit, or local commit ID when using local repository | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--cwd` | Working directory to launch the script from. Relative to repo root or local `--folder` | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--docker` | Select the Docker image to use in the remote task | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--docker_bash_setup_script` | Add a bash script to be executed inside the Docker before setting up the task's environment | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--docker` | Select the container image to use in the remote task | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--docker_bash_setup_script` | Add a bash script to be executed inside the container before setting up the task's environment | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--docker_args` | Add Docker arguments. Pass a single string in the following format: `--docker_args "<argument_string>"`. For example: `--docker_args "-v some_dir_1:other_dir_1 -v some_dir_2:other_dir_2"` | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--folder` | Execute the code from a local folder. Notice, it assumes a git repository already exists. Current state of the repo (commit ID and uncommitted changes) is logged and replicated on the remote machine | <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
| `--import-offline-session`| Specify the path to the offline session you want to import.| <img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" /> |
|
||||
|
||||
@ -29,7 +29,7 @@ The preceding diagram demonstrates a typical flow where an agent executes a task
|
||||
|
||||
1. Enqueue a task for execution on the queue.
|
||||
1. The agent pulls the task from the queue.
|
||||
1. The agent launches a docker container in which to run the task's code.
|
||||
1. The agent launches a container in which to run the task's code.
|
||||
1. The task's execution environment is set up:
|
||||
1. Execute any custom setup script configured.
|
||||
1. Install any required system packages.
|
||||
@ -39,8 +39,8 @@ The preceding diagram demonstrates a typical flow where an agent executes a task
|
||||
1. The task's script/code is executed.
|
||||
|
||||
:::note Python Version
|
||||
ClearML Agent uses the Python version available in the environment or docker in which it executes the code. It does not
|
||||
install Python, so make sure to use a docker or environment with the version you need.
|
||||
ClearML Agent uses the Python version available in the environment or container in which it executes the code. It does not
|
||||
install Python, so make sure to use a container or environment with the version you need.
|
||||
:::
|
||||
|
||||
While the agent is running, it continuously reports system metrics to the ClearML Server (these can be monitored in the
|
||||
|
||||
@ -39,8 +39,7 @@ clearml-agent build --id <task-id> --docker --target <new-docker-name>
|
||||
|
||||
You can add the Docker container as the base Docker image to a task, using one of the following methods:
|
||||
|
||||
- Using the **ClearML Web UI** - See [Base Docker image](../webapp/webapp_exp_tuning.md#base-docker-image) on the "Tuning
|
||||
Tasks" page.
|
||||
- Using the **ClearML Web UI** - See [Default Container](../webapp/webapp_exp_tuning.md#default-container).
|
||||
- In the ClearML configuration file - Use the ClearML configuration file [`agent.default_docker`](../configs/clearml_conf.md#agentdefault_docker)
|
||||
options.
|
||||
|
||||
|
||||
@ -26,7 +26,7 @@ If you are using pyenv to control the environment where you use ClearML Agent, y
|
||||
* Install poetry with the deprecated `get-poetry.py` installer
|
||||
:::
|
||||
|
||||
## Docker Mode
|
||||
## Docker Mode
|
||||
:::note notes
|
||||
* Docker Mode is only supported in Linux.
|
||||
* Docker Mode requires docker service v19.03 or higher installed.
|
||||
|
||||
@ -13,7 +13,7 @@ so the models are traceable to tasks.
|
||||
|
||||
## Output Models
|
||||
|
||||
### Manually Logging Models
|
||||
### Manually Logging Models
|
||||
|
||||
To manually log a model, create an instance of OutputModel class.
|
||||
|
||||
|
||||
@ -82,7 +82,7 @@ Inference services status, console outputs and machine metrics are available in
|
||||
project (default: "DevOps" project).
|
||||
:::
|
||||
|
||||
## Registering and Deploying New Models Manually
|
||||
## Registering and Deploying New Models Manually
|
||||
|
||||
Uploading an existing model file into the model repository can be done via the `clearml` RestAPI, the Python interface,
|
||||
or with the `clearml-serving` CLI.
|
||||
|
||||
@ -161,7 +161,7 @@ clearml-session==0.3.2
|
||||
#### How can I sort models by a certain metric? <a id="custom-columns"></a>
|
||||
|
||||
To sort models by a metric, in the ClearML Web UI,
|
||||
add a [custom column](webapp/webapp_model_table.md#customizing-the-models-table) to the model table and sort by
|
||||
add a [custom column](webapp/webapp_model_table.md#customizing-the-model-table) to the model table and sort by
|
||||
that metric column. Available custom column options depend upon the models in the table and the metrics that have been
|
||||
attached to them (see [Logging Metrics and Plots](clearml_sdk/model_sdk.md#logging-metrics-and-plots)).
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ title: Executable Task Containers
|
||||
---
|
||||
|
||||
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)'s [`build`](../../clearml_agent/clearml_agent_ref.md#build)
|
||||
command to package a task into an executable container. In this example, you will build a Docker image that, when
|
||||
command to package a task into an executable container. In this example, you will build a Container image that, when
|
||||
run, will automatically execute the [keras_tensorboard.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
|
||||
script.
|
||||
|
||||
@ -44,8 +44,8 @@ script.
|
||||
If the container will not make use of a GPU, add the `--cpu-only` flag.
|
||||
:::
|
||||
|
||||
This command will create a Docker container, set up with the execution environment for this task in the
|
||||
specified `--target` folder. When the Docker container is launched, it will clone the task specified with `id` and
|
||||
This command will create a container, set up with the execution environment for this task in the
|
||||
specified `--target` folder. When the container is launched, it will clone the task specified with `id` and
|
||||
execute the clone (as designated by the `--entry-point` parameter).
|
||||
|
||||
1. Run the Docker, pointing to the new container:
|
||||
|
||||
@ -3,7 +3,7 @@ title: Task Environment Containers
|
||||
---
|
||||
|
||||
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)'s [`build`](../../clearml_agent/clearml_agent_ref.md#build)
|
||||
command to build a Docker container replicating the execution environment of an existing task. ClearML Agents can make
|
||||
command to build a container replicating the execution environment of an existing task. ClearML Agents can make
|
||||
use of such containers to execute tasks without having to set up their environment every time.
|
||||
|
||||
A use case for this would be manual hyperparameter optimization, where a base task can be used to create a container to
|
||||
@ -36,7 +36,7 @@ be used when running optimization tasks.
|
||||
```
|
||||
This ID will be used in the following section.
|
||||
|
||||
## Building the Docker Container
|
||||
## Building the Container
|
||||
|
||||
Execute the following command to build the container. Input the ID of the task created above.
|
||||
```console
|
||||
@ -56,7 +56,7 @@ Committing docker container to: new_docker
|
||||
sha256:460453b93ct1989fd1c6637c236e544031c4d378581433fc0b961103ce206af1
|
||||
```
|
||||
|
||||
## Using the New Docker Container
|
||||
## Using the New Container
|
||||
Make use of the container you've just built by having a ClearML agent make use of it for executing a new task:
|
||||
|
||||
1. In the [ClearML Web UI](../../webapp/webapp_overview.md), go to the "examples" project, "Keras with TensorBoard
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
title: Extra Docker Shell Script
|
||||
---
|
||||
|
||||
When using `clearml-agent`, an agent recreates an entire execution environment, be it by pulling the docker container or
|
||||
When using `clearml-agent`, an agent recreates an entire execution environment, be it by pulling a container or
|
||||
installing specified packages, and then executes the code on a remote machine. The Agent takes into account required Python packages,
|
||||
but sometimes, when using a Docker container, a user may need to use additional, non-Python tools.
|
||||
|
||||
|
||||
@ -27,7 +27,7 @@ clearml-session --docker nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 --packages
|
||||
|
||||
This sets the following arguments:
|
||||
|
||||
* `--docker nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04` - Docker image
|
||||
* `--docker nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04` - Container image
|
||||
|
||||
* `--packages "clearml" "tensorflow>=2.2" "keras"` - Required Python packages
|
||||
|
||||
@ -39,7 +39,7 @@ name is `DevOps`.
|
||||
:::
|
||||
|
||||
After launching the command, the `clearml-agent` listening to the `default` queue spins a remote Jupyter environment with
|
||||
the specifications. It will automatically connect to the docker on the remote machine.
|
||||
the specifications. It will automatically connect to the container on the remote machine.
|
||||
|
||||
The console should display the session's configuration details:
|
||||
|
||||
|
||||
@ -27,7 +27,8 @@ data lineages can be created, and users can track when and how their data change
|
||||
you can view a dataset's version history, as well as its contents, including annotations, metadata, masks, and other
|
||||
information.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
The basic premise of Hyper-Datasets is that a user-formed query is a full representation of the dataset used by the ML/DL
|
||||
process. Hyper-Datasets decouple metadata from raw data files, allowing you to manipulate metadata through sophisticated
|
||||
|
||||
@ -24,7 +24,8 @@ See how to manage dataset version mask labels pythonically [here](dataset.md#man
|
||||
|
||||
In the UI, you can view the mapping in a dataset version's [Metadata](webapp/webapp_datasets_versioning.md#metadata) tab.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
When viewing a frame with a mask corresponding with the version's mask-label mapping, the UI arbitrarily assigns a color
|
||||
to each label. The color assignment can be [customized](webapp/webapp_datasets_frames.md#labels).
|
||||
@ -32,12 +33,14 @@ to each label. The color assignment can be [customized](webapp/webapp_datasets_f
|
||||
For example:
|
||||
* Original frame image:
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* Frame image with the semantic segmentation mask enabled. Labels are applied according to the dataset version's
|
||||
mask-label mapping:
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
The frame's sources array contains a masks list of dictionaries that looks something like this:
|
||||
|
||||
@ -75,11 +78,13 @@ desired sections of the source are visible.
|
||||
For example:
|
||||
* Original frame:
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* Same frame with an alpha channel mask, emphasizing the troll doll:
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
|
||||
The frame's sources array contains a masks list of dictionaries that looks something like this:
|
||||
|
||||
@ -90,8 +90,10 @@ The following is an example of preview metadata.
|
||||
|
||||
Here's an example of Previews in the ClearML Enterprise WebApp (UI). Each thumbnail is a Preview:
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
If the preview's `uri` is for a video, the thumbnail will display the video with video controls:
|
||||
|
||||

|
||||

|
||||

|
||||
@ -147,7 +147,8 @@ object annotations, its metadata, and other details.
|
||||
|
||||
This image shows a SingleFrame in the ClearML Enterprise WebApp (UI) [frame viewer](webapp/webapp_datasets_frames.md#frame-viewer).
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</Collapsible>
|
||||
|
||||
|
||||
@ -7,7 +7,8 @@ Use the Annotations page to access and manage annotation Tasks.
|
||||
Use annotation tasks to efficiently organize the annotation of frames in Dataset versions and manage the work of annotators
|
||||
(see [Annotating Images and Videos](#annotating-images-and-video)).
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
Click on an annotation task card to open the frame viewer, where you can view the task's frames and annotate them.
|
||||
|
||||
@ -15,7 +16,12 @@ Click on an annotation task card to open the frame viewer, where you can view th
|
||||
Click <img src="/docs/latest/icons/ico-bars-menu.svg" alt="Menu" className="icon size-md space-sm" /> on the top right
|
||||
of an annotation task card to open its context menu and access annotation task actions.
|
||||
|
||||

|
||||
<div class="max-w-75">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
* **Annotate** - Go to annotation task frame viewer
|
||||
* **Info** - View annotation task's definitions: dataset versions, filters, and frame iteration specification
|
||||
@ -32,7 +38,8 @@ Sort the annotation tasks by either using **RECENT** or **NAME** option.
|
||||
|
||||
## Creating Annotation Tasks
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
**To create an annotation task:**
|
||||
|
||||
@ -61,7 +68,7 @@ Sort the annotation tasks by either using **RECENT** or **NAME** option.
|
||||
|
||||
1. Click **Create**.
|
||||
|
||||
## Annotating Images and Video
|
||||
## Annotating Images and Video
|
||||
Annotate images and video by labeling regions of interest in Dataset version frames. The frames presented for annotation
|
||||
depend upon the settings in the annotation task (see [Creating Annotation Tasks](#creating-annotation-tasks)).
|
||||
|
||||
|
||||
@ -20,7 +20,8 @@ Filter the hyper-datasets to find the one you're looking for more easily. These
|
||||
* Filter by the absence of a tag (logical "NOT") by clicking its checkbox twice. An X will appear in the tag's checkbox.
|
||||
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
## Project Cards
|
||||
|
||||
@ -28,7 +29,8 @@ In Project view, project cards display a project's summarized hyper-dataset info
|
||||
|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
@ -45,7 +47,8 @@ In List view, the Hyper-Dataset cards display summarized dataset information:
|
||||
|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
@ -70,9 +73,10 @@ To change the label color coding, hover over a label color, click the hand point
|
||||
Click <img src="/docs/latest/icons/ico-bars-menu.svg" alt="Menu" className="icon size-md space-sm" /> on the top right
|
||||
of a dataset card to open its context menu and access dataset actions:
|
||||
|
||||
<div class="max-w-50">
|
||||
<div class="max-w-75">
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
@ -85,6 +89,11 @@ of a dataset card to open its context menu and access dataset actions:
|
||||
To create a Hyper-Dataset, click the **+ NEW DATASET** button in the top right of the page, which will open a
|
||||
**New Dataset** modal.
|
||||
|
||||

|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
This creates a new Hyper-Dataset that contains a single, empty draft version.
|
||||
|
||||
@ -7,14 +7,16 @@ of frames and enables viewing SingleFrames and FramesGroups, and editing SingleF
|
||||
Before opening the frame viewer, you can filter the frames by applying [simple](webapp_datasets_versioning.md#simple-frame-filtering) or [advanced](webapp_datasets_versioning.md#advanced-frame-filtering)
|
||||
filtering logic.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
## Frame Viewer
|
||||
|
||||
Use the frame viewer to view and edit annotations (ROIs and frame labels), frame details (see [frames](../frames.md)),
|
||||
and frame metadata, as well as view frame masks of your dataset version frames.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
### Frame Viewer Controls
|
||||
|
||||
@ -93,13 +95,15 @@ Viewing and editing frames in a FrameGroup is similar to viewing and editing Sin
|
||||
Click the FrameGroup in the Hyper-Dataset. In the frame viewer, select SingleFrame to view / modify from
|
||||
a dropdown list in the **Current Source** section.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
If an annotation applies to all frames in a FrameGroup, it is displayed with a `Multi Source` indicator:
|
||||
|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
@ -171,7 +175,8 @@ Click the color circle in the label name to manually set the label's color.
|
||||
|
||||
<div class="max-w-75">
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
@ -179,7 +184,8 @@ Click the color circle in the annotation header to manually set the annotation
|
||||
|
||||
<div class="max-w-75">
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</div>
|
||||
:::
|
||||
|
||||
@ -5,7 +5,8 @@ title: Dataset Versions
|
||||
Use the Dataset versioning WebApp (UI) features for viewing, creating, modifying, and
|
||||
deleting [Dataset versions](../dataset.md#dataset-versioning).
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
## Dataset Version History
|
||||
The WebApp (UI) presents your dataset version structure in tree view <img src="/docs/latest/icons/ico-tree-view.svg" alt="Tree view" className="icon size-md space-sm" />
|
||||
@ -13,11 +14,21 @@ or list view <img src="/docs/latest/icons/ico-list-view.svg" alt="List view" cla
|
||||
|
||||
The tree view shows the lineage of the dataset's versions.
|
||||
|
||||

|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
The list view lists the dataset's versions chronologically by last update time.
|
||||
|
||||

|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
Click <img src="/docs/latest/icons/ico-sort.svg" alt="Sort order" className="icon size-md space-sm" /> to order the
|
||||
dataset versions in ascending or descending order based on their last update time.
|
||||
@ -27,7 +38,12 @@ all versions that match the query.
|
||||
|
||||
In tree view, parent versions that do not match the query where a child version does appear in a muted color.
|
||||
|
||||

|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
### Version Actions
|
||||
|
||||
@ -43,7 +59,13 @@ Access dataset version actions, by right-clicking a version, or through the menu
|
||||
When publishing a version, you can create an additional working copy. The new version is created in a *draft* state, and
|
||||
inherits all the published version's frames.
|
||||
|
||||

|
||||
<div class="max-w-75">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
:::
|
||||
|
||||
## Version Data
|
||||
@ -67,12 +89,14 @@ Use the thumbnail view for a visual preview of the version's frames. You can inc
|
||||
and decrease <img src="/docs/latest/icons/ico-zoom-out.svg" alt="Zoom out" className="icon size-md space-sm" /> the size of
|
||||
the previews.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
Use the table view to list the version's frames in a customizable table. Click <img src="/docs/latest/icons/ico-settings.svg" alt="Setting Gear" className="icon size-md" />
|
||||
for column customization options.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
The dataset version's frames can be filtered by multiple criteria. The resulting frames can be [exported as a JSON file](#exporting-frames).
|
||||
|
||||
@ -88,11 +112,13 @@ Simple frame filtering returns frames containing at least one annotation with a
|
||||
* The **FRAMES** tab in the image below contains 101 frames.
|
||||
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* A simple label filter for `teddy bear` shows three frames, each containing at least one ROI labeled `teddy bear`.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</Collapsible>
|
||||
|
||||
@ -121,7 +147,8 @@ A frame filter can contain a number of rules. For each frame filter, the rules a
|
||||
|
||||
The returned frames are those that match the first rule AND the second rule within the frame filter.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
Create additional frame filters by clicking <img src="/docs/latest/icons/ico-add.svg" alt="Add new" className="icon size-md space-sm" />.
|
||||
Multiple frame filters are applied with a logical OR operator.
|
||||
@ -130,7 +157,8 @@ For example, the dataset version in the image below has two frame filters. "Fram
|
||||
described in the example above. "Frame Filter 2" specifies an ROI rule for the frame to contain an ROI with the label
|
||||
`dog`. So the frames returned are those that match ALL of Frame Filter 1's rules OR ALL of Frame Filter 2's rules.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
To clear all filters click <img src="/docs/latest/icons/ico-filter-reset.svg" alt="Clear filters" className="icon size-md" />.
|
||||
|
||||
@ -141,28 +169,33 @@ To clear all filters click <img src="/docs/latest/icons/ico-filter-reset.svg" al
|
||||
|
||||
* Create one ROI rule for the `teddy bear` label, which shows the same three frames as the simple frame filter (above).
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* In the ROI rule, add a second label. Add `partially_occluded`. Only frames containing at least one ROI labeled as both
|
||||
`teddy bear` and `partially_occluded` match the filter.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* By opening a frame in the frame viewer, you can see an ROI labeled with both.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* To find frames that contain multiple ROIs, each with a different label, use separate ROI rules. Create an ROI rule for
|
||||
the `teddy bear` label and, in the same filter, add another ROI rule for the `person` label. This will return all
|
||||
frames that include at least one ROIs with a `person` label AND at least one (other) ROI with a `teddy bear` label.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* You can also exclude certain ROI labels. Create an ROI rule to include `teddy bear` and, in the same filter, an ROI
|
||||
rule to exclude `person`. This will return all frames that include at least one ROI with the label `teddy bear` AND have
|
||||
NO ROI with the `person` label
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</Collapsible>
|
||||
|
||||
@ -172,11 +205,13 @@ Filter by metadata using Lucene queries.
|
||||
|
||||
* Add a frame rule to filter by the metadata key `dangerous` for the value of `yes`.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
* Open a frame in the frame viewer to see its metadata.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
</Collapsible>
|
||||
|
||||
@ -186,7 +221,8 @@ Filter by sources using Lucene queries.
|
||||
|
||||
* Add a source rule to filter for source URIs with wildcards.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
Lucene queries can also be used in ROI label filters and frame rules.
|
||||
|
||||
@ -204,7 +240,8 @@ Sort the dataset version’s frames by any of the following attributes:
|
||||
|
||||
Click <img src="/docs/latest/icons/ico-sort.svg" alt="Sort order" className="icon size-md space-sm" /> to toggle between ascending and descending sort orders.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
### Exporting Frames
|
||||
|
||||
@ -214,7 +251,12 @@ To export (download) the filtered frames as a JSON file, click <img src="/docs/l
|
||||
Click <img src="/docs/latest/icons/ico-bars-menu.svg" alt="Menu" className="icon size-md space-sm" /> to open the
|
||||
frame browser configuration settings.
|
||||
|
||||

|
||||
<div class="max-w-75">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||
#### Grouping Previews
|
||||
|
||||
@ -223,10 +265,11 @@ Use the **Grouping** menu to set how to display frames that share a common prope
|
||||
* **Group by URL** - Show a single preview for all FrameGroups with the same context ID. For example, users can set the
|
||||
same `context_id` to multiple FrameGroups that represent frames in a single video.
|
||||
* **Sample by Property** - Specify a frame or ROI property whose value to group frames by and set the number of frames
|
||||
to preview for each group. For example, in the image below, frames are grouped by ROI labels. Each group displays six
|
||||
to preview for each group. For example, in the image below, frames are grouped by ROI labels. Each group displays five
|
||||
samples of frames that contain an ROI with the same label.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
**To sample by property:**
|
||||
1. In the **Grouping** menu, click **Sample by Property**
|
||||
@ -240,12 +283,18 @@ samples of frames that contain an ROI with the same label.
|
||||
to use in grouping by their properties. For example, in a Hyper-Dataset where ROIs have object labels and type labels,
|
||||
view a sample of frames with different types of the same object by grouping frames according to `label.keyword`
|
||||
with a match query for the object of interest.
|
||||
<br/>
|
||||
<div class="max-w-50">
|
||||
|
||||

|
||||

|
||||
|
||||
</div>
|
||||
|
||||

|
||||
|
||||
The image below shows a sample of 3 frames which have ROIs of each type (`pedestrian`, `rider`, `sitting`) of `person`.
|
||||
|
||||

|
||||

|
||||

|
||||
:::note Property N/A group
|
||||
If there are frames which have no value for the grouped by property, a sample of them will be provided as a final
|
||||
group. If you sample according to an ROI property, this group will NOT include frames that have no ROIS at all.
|
||||
@ -273,7 +322,8 @@ Choose the `All sources` option to present all the FrameGroup’s sources in a g
|
||||
shows annotations grouped by their respective sources. Additionally, annotation tools (e.g. create/delete/modify
|
||||
annotations) are not available in this view.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
:::note Unavailable Source
|
||||
If a FrameGroup doesn't have the selected preview source, the preview displays the "Source not available" message.
|
||||
@ -298,7 +348,8 @@ be included in the calculation.
|
||||
For example, calculating the distribution for the `label` ROI property, specifying `rois.confidence: 1` for ROI matching
|
||||
will show the label distribution across only ROIs with a confidence level of 1.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
By default, the ROI label distribution across the entire Hyper-Dataset version is shown.
|
||||
The tab displays the following information
|
||||
@ -310,7 +361,8 @@ The tab displays the following information
|
||||
* The pie chart visualizes this distribution. Hover over a chart segment and its associated property and count will
|
||||
appear in a tooltip and its usage percentage will appear at the center of the chart.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
## Metadata
|
||||
The **Metadata** tab presents any additional metadata that has been attached to the dataset version.
|
||||
@ -321,7 +373,8 @@ The **Metadata** tab presents any additional metadata that has been attached to
|
||||
1. Edit the section contents (JSON format)
|
||||
1. Click **OK**
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
## Info
|
||||
|
||||
@ -339,5 +392,6 @@ The **Info** tab presents a version's general information:
|
||||
* Percentage of annotated frames
|
||||
* Version description (editable, hover over element and click <img src="/docs/latest/icons/ico-edit.svg" alt="Edit pencil" className="icon size-md space-sm" />)
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
|
||||
@ -25,7 +25,8 @@ and choosing one of these options:
|
||||
|
||||
The downloaded data consists of the currently displayed table columns.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
The Dataview table includes the following columns:
|
||||
|
||||
@ -97,11 +98,13 @@ Select multiple Dataviews, then use either the context menu, or the batch action
|
||||
operations on the selected Dataviews. The context menu shows the number of Dataviews that can be affected by each action.
|
||||
The same information can be found in the batch action bar, in a tooltip that appears when hovering over an action icon.
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
## Creating a Dataview
|
||||
|
||||
Create a Dataview by clicking **+ NEW DATAVIEW**, which opens a
|
||||
**NEW DATAVIEW** window.
|
||||
|
||||

|
||||

|
||||

|
||||
@ -29,4 +29,5 @@ on the task that will be the new base.
|
||||
* Hover and click <img src="/docs/latest/icons/ico-drag.svg" alt="Pan icon" className="icon size-md space-sm" /> on the new base task and drag it all the way to the left
|
||||
|
||||
|
||||

|
||||

|
||||

|
||||
@ -16,7 +16,8 @@ In a task's page, go to the **DATAVIEWS** tab to view all the task's Dataview de
|
||||
* [Label enumeration](#label-enumeration)
|
||||
* [Iteration controls](#iteration-control)
|
||||
|
||||

|
||||

|
||||

|
||||
|
||||
### Input
|
||||
|
||||
|
||||
|
Before Width: | Height: | Size: 94 KiB |
|
Before Width: | Height: | Size: 18 KiB |
|
Before Width: | Height: | Size: 32 KiB |
BIN
docs/img/hyperdatasets/annotation_label_color.png
Normal file
|
After Width: | Height: | Size: 13 KiB |
|
Before Width: | Height: | Size: 13 KiB After Width: | Height: | Size: 13 KiB |
BIN
docs/img/hyperdatasets/annotation_label_opacity.png
Normal file
|
After Width: | Height: | Size: 13 KiB |
|
Before Width: | Height: | Size: 13 KiB After Width: | Height: | Size: 13 KiB |
BIN
docs/img/hyperdatasets/annotation_page.png
Normal file
|
After Width: | Height: | Size: 113 KiB |
BIN
docs/img/hyperdatasets/annotation_page_dark.png
Normal file
|
After Width: | Height: | Size: 116 KiB |
|
Before Width: | Height: | Size: 94 KiB After Width: | Height: | Size: 143 KiB |
BIN
docs/img/hyperdatasets/annotation_task_01_dark.png
Normal file
|
After Width: | Height: | Size: 95 KiB |
BIN
docs/img/hyperdatasets/annotation_task_card.png
Normal file
|
After Width: | Height: | Size: 40 KiB |
BIN
docs/img/hyperdatasets/annotation_task_card_dark.png
Normal file
|
After Width: | Height: | Size: 42 KiB |
BIN
docs/img/hyperdatasets/compare_dataviews.png
Normal file
|
After Width: | Height: | Size: 134 KiB |
BIN
docs/img/hyperdatasets/compare_dataviews_dark.png
Normal file
|
After Width: | Height: | Size: 134 KiB |
|
Before Width: | Height: | Size: 722 KiB After Width: | Height: | Size: 1.1 MiB |
BIN
docs/img/hyperdatasets/dataset_alpha_masks_1_dark.png
Normal file
|
After Width: | Height: | Size: 1015 KiB |
|
Before Width: | Height: | Size: 474 KiB After Width: | Height: | Size: 662 KiB |
BIN
docs/img/hyperdatasets/dataset_alpha_masks_2_dark.png
Normal file
|
After Width: | Height: | Size: 625 KiB |
BIN
docs/img/hyperdatasets/dataset_example_frame_editor.png
Normal file
|
After Width: | Height: | Size: 1.3 MiB |
BIN
docs/img/hyperdatasets/dataset_example_frame_editor_dark.png
Normal file
|
After Width: | Height: | Size: 1.3 MiB |
|
Before Width: | Height: | Size: 1.4 MiB After Width: | Height: | Size: 1.2 MiB |
BIN
docs/img/hyperdatasets/dataset_frame_sorting_dark.png
Normal file
|
After Width: | Height: | Size: 1.2 MiB |
|
Before Width: | Height: | Size: 35 KiB After Width: | Height: | Size: 35 KiB |
BIN
docs/img/hyperdatasets/dataset_metadata_dark.png
Normal file
|
After Width: | Height: | Size: 37 KiB |
|
Before Width: | Height: | Size: 916 KiB After Width: | Height: | Size: 1.4 MiB |
BIN
docs/img/hyperdatasets/dataset_pixel_masks_1_dark.png
Normal file
|
After Width: | Height: | Size: 1.4 MiB |
|
Before Width: | Height: | Size: 124 KiB After Width: | Height: | Size: 179 KiB |
BIN
docs/img/hyperdatasets/dataset_pixel_masks_2_dark.png
Normal file
|
After Width: | Height: | Size: 181 KiB |
|
Before Width: | Height: | Size: 1.1 MiB After Width: | Height: | Size: 772 KiB |
BIN
docs/img/hyperdatasets/dataset_sample_by_roi_property_dark.png
Normal file
|
After Width: | Height: | Size: 771 KiB |
BIN
docs/img/hyperdatasets/dataset_simple_adv_01.png
Normal file
|
After Width: | Height: | Size: 128 KiB |
BIN
docs/img/hyperdatasets/dataset_simple_adv_01_dark.png
Normal file
|
After Width: | Height: | Size: 128 KiB |
BIN
docs/img/hyperdatasets/dataset_simple_adv_02.png
Normal file
|
After Width: | Height: | Size: 106 KiB |
BIN
docs/img/hyperdatasets/dataset_simple_adv_02_dark.png
Normal file
|
After Width: | Height: | Size: 74 KiB |
|
Before Width: | Height: | Size: 68 KiB After Width: | Height: | Size: 68 KiB |
BIN
docs/img/hyperdatasets/dataset_version_info_panel_dark.png
Normal file
|
After Width: | Height: | Size: 68 KiB |
|
Before Width: | Height: | Size: 26 KiB After Width: | Height: | Size: 26 KiB |
BIN
docs/img/hyperdatasets/dataset_version_metadata_dark.png
Normal file
|
After Width: | Height: | Size: 26 KiB |
|
Before Width: | Height: | Size: 88 KiB After Width: | Height: | Size: 86 KiB |
BIN
docs/img/hyperdatasets/dataset_version_statistics_dark.png
Normal file
|
After Width: | Height: | Size: 87 KiB |
|
Before Width: | Height: | Size: 7.1 KiB After Width: | Height: | Size: 7.7 KiB |
BIN
docs/img/hyperdatasets/dataset_version_statistics_roi_dark.png
Normal file
|
After Width: | Height: | Size: 7.8 KiB |
BIN
docs/img/hyperdatasets/dataset_versions.png
Normal file
|
After Width: | Height: | Size: 1.5 MiB |
BIN
docs/img/hyperdatasets/dataset_versions_dark.png
Normal file
|
After Width: | Height: | Size: 1.5 MiB |
|
Before Width: | Height: | Size: 408 KiB After Width: | Height: | Size: 160 KiB |
BIN
docs/img/hyperdatasets/datasets_01_dark.png
Normal file
|
After Width: | Height: | Size: 160 KiB |
BIN
docs/img/hyperdatasets/dataview_tab.png
Normal file
|
After Width: | Height: | Size: 65 KiB |
BIN
docs/img/hyperdatasets/dataview_tab_dark.png
Normal file
|
After Width: | Height: | Size: 64 KiB |
|
Before Width: | Height: | Size: 167 KiB After Width: | Height: | Size: 170 KiB |
BIN
docs/img/hyperdatasets/frame_browser_list_dark.png
Normal file
|
After Width: | Height: | Size: 175 KiB |
|
Before Width: | Height: | Size: 17 KiB After Width: | Height: | Size: 41 KiB |
BIN
docs/img/hyperdatasets/frame_browser_menu_dark.png
Normal file
|
After Width: | Height: | Size: 43 KiB |
|
Before Width: | Height: | Size: 1.4 MiB After Width: | Height: | Size: 1.4 MiB |
BIN
docs/img/hyperdatasets/frame_browser_thumbnails_dark.png
Normal file
|
After Width: | Height: | Size: 1.4 MiB |
|
Before Width: | Height: | Size: 1.6 MiB After Width: | Height: | Size: 1.4 MiB |
BIN
docs/img/hyperdatasets/frame_filtering_01_dark.png
Normal file
|
After Width: | Height: | Size: 1.4 MiB |
|
Before Width: | Height: | Size: 200 KiB After Width: | Height: | Size: 202 KiB |
BIN
docs/img/hyperdatasets/frame_filtering_02_dark.png
Normal file
|
After Width: | Height: | Size: 201 KiB |
|
Before Width: | Height: | Size: 227 KiB After Width: | Height: | Size: 204 KiB |
BIN
docs/img/hyperdatasets/frame_filtering_03_dark.png
Normal file
|
After Width: | Height: | Size: 205 KiB |
|
Before Width: | Height: | Size: 102 KiB After Width: | Height: | Size: 95 KiB |
BIN
docs/img/hyperdatasets/frame_filtering_04_dark.png
Normal file
|
After Width: | Height: | Size: 96 KiB |
|
Before Width: | Height: | Size: 1.9 MiB After Width: | Height: | Size: 1.9 MiB |
BIN
docs/img/hyperdatasets/frame_filtering_05_dark.png
Normal file
|
After Width: | Height: | Size: 1.9 MiB |
|
Before Width: | Height: | Size: 2.8 MiB After Width: | Height: | Size: 846 KiB |
BIN
docs/img/hyperdatasets/frame_filtering_06_dark.png
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