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Merge pull request #3 from pollfly/enterprise_caps

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Remove redundant styling
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Noam Wasersprung 2021-07-06 16:16:20 +03:00 committed by GitHub
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docs/hyperdatasets/annotations.md
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title: Annotations title: Annotations
--- ---
With **ClearML Enterprise**, annotations can be applied to video and image frames. [Frames](single_frames.md) support With ClearML Enterprise, annotations can be applied to video and image frames. [Frames](single_frames.md) support
two types of annotations: **Frame objects** and **Frame labels**. two types of annotations: **Frame objects** and **Frame labels**.
Annotation Tasks can be used to efficiently organize the annotation of frames in Dataset versions (see Annotation Tasks can be used to efficiently organize the annotation of frames in Dataset versions (see
@ -15,7 +15,7 @@ For information about how to view, create, and manage annotations using the WebA
Frame objects are labeled Regions of Interest (ROIs), which can be bounded by polygons (including rectangles), ellipses, Frame objects are labeled Regions of Interest (ROIs), which can be bounded by polygons (including rectangles), ellipses,
or key points. These ROIs are useful for object detection, classification, or semantic segmentation. or key points. These ROIs are useful for object detection, classification, or semantic segmentation.
Frame objects can include ROI labels, confidence levels, and masks for semantic segmentation. In **ClearML Enterprise**, Frame objects can include ROI labels, confidence levels, and masks for semantic segmentation. In ClearML Enterprise,
one or more labels and sources dictionaries can be associated with an ROI (although multiple source ROIs are not frequently used). one or more labels and sources dictionaries can be associated with an ROI (although multiple source ROIs are not frequently used).
## Frame labels ## Frame labels

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docs/hyperdatasets/dataset.md
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ClearML Enterprise's **Datasets** and **Dataset versions** provide the internal data structure ClearML Enterprise's **Datasets** and **Dataset versions** provide the internal data structure
and functionality for the following purposes: and functionality for the following purposes:
* Connecting source data to the **ClearML Enterprise** platform * Connecting source data to the ClearML Enterprise platform
* Using **ClearML Enterprise**'s GIT-like [Dataset versioning](#dataset-versioning) * Using ClearML Enterprise's GIT-like [Dataset versioning](#dataset-versioning)
* Integrating the powerful features of [Dataviews](dataviews.md) with an experiment * Integrating the powerful features of [Dataviews](dataviews.md) with an experiment
* [Annotating](webapp/webapp_datasets_frames.md#annotations) images and videos * [Annotating](webapp/webapp_datasets_frames.md#annotations) images and videos
@ -29,8 +29,8 @@ it must be published first.
## Example Datasets ## Example Datasets
**ClearML Enterprise** provides Example Datasets, available to in the **ClearML Enterprise** platform, with frames already built, ClearML Enterprise provides Example Datasets, available to in the ClearML Enterprise platform, with frames already built,
and ready for your experimentation. Find these example Datasets in the **ClearML Enterprise** WebApp (UI). They appear and ready for your experimentation. Find these example Datasets in the ClearML Enterprise WebApp (UI). They appear
with an "Example" banner in the WebApp (UI). with an "Example" banner in the WebApp (UI).
## Usage ## Usage
@ -113,10 +113,10 @@ Dataset.delete(dataset_name='MyDataset', delete_all_versions=True, force=True)
## Dataset Versioning ## Dataset Versioning
Dataset versioning refers to the group of **ClearML Enterprise** SDK and WebApp (UI) features for creating, Dataset versioning refers to the group of ClearML Enterprise SDK and WebApp (UI) features for creating,
modifying, and deleting Dataset versions. modifying, and deleting Dataset versions.
**ClearML Enterprise** supports simple and sophisticated Dataset versioning, including **simple version structures** and ClearML Enterprise supports simple and sophisticated Dataset versioning, including **simple version structures** and
**advanced version structures**. **advanced version structures**.
In a **simple version structure**, a parent can have one and only one child, and the last child in the Dataset versions In a **simple version structure**, a parent can have one and only one child, and the last child in the Dataset versions

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docs/hyperdatasets/dataviews.md
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title: Dataviews title: Dataviews
--- ---
Dataviews is a powerful and easy-to-use **ClearML Enterprise** feature for creating and managing local views of remote Dataviews is a powerful and easy-to-use ClearML Enterprise feature for creating and managing local views of remote
Datasets. Dataviews can use sophisticated queries to input data from a subset of a Dataset Datasets. Dataviews can use sophisticated queries to input data from a subset of a Dataset
or combinations of Datasets. or combinations of Datasets.
@ -85,7 +85,7 @@ in steps, where each step is composed of a method, an operation, and a strength
Use any of the following operations: Use any of the following operations:
* Blur - Gaussian smoothing * Blur - Gaussian smoothing
* Noise - **ClearML Enterprise**'s own noise augmentation consisting of: * Noise - ClearML Enterprise's own noise augmentation consisting of:
* **high** noise - like snow on analog televisions with a weak TV signal * **high** noise - like snow on analog televisions with a weak TV signal
* **low** noise - like a low resolution image magnified in localized areas on the image * **low** noise - like a low resolution image magnified in localized areas on the image
* Recolor - using an internal RGB lookup-table * Recolor - using an internal RGB lookup-table

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docs/hyperdatasets/single_frames.md
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A `SingleFrame` contains metadata pointing to raw data, and other metadata and data, which supports experimentation and A `SingleFrame` contains metadata pointing to raw data, and other metadata and data, which supports experimentation and
**ClearML Enterprise**'s Git-like Dataset versioning. ClearML Enterprise's Git-like Dataset versioning.
## Frame Components ## Frame Components
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## WebApp ## WebApp
A frame that has been connected to the **ClearML Enterprise** platform is available to view and analyze on the A frame that has been connected to the ClearML Enterprise platform is available to view and analyze on the
WebApp (UI). WebApp (UI).
When viewing a frame on the WebApp, all the information associated with it can be viewed, including its frame labels and When viewing a frame on the WebApp, all the information associated with it can be viewed, including its frame labels and

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docs/hyperdatasets/webapp/webapp_dataviews.md
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title: Dataviews Table title: Dataviews Table
--- ---
[Dataviews](../dataviews.mda) appear in the same Project as the experiment that stored the Dataview in the **ClearML Enterprise** platform, [Dataviews](../dataviews.mda) appear in the same Project as the experiment that stored the Dataview in the ClearML Enterprise platform,
as well as the **DATAVIEWS** tab in the **All Projects** page. as well as the **DATAVIEWS** tab in the **All Projects** page.
The **Dataviews table** is a [customizable](#customizing-the-dataviews-table) list of Dataviews associated with a project. The **Dataviews table** is a [customizable](#customizing-the-dataviews-table) list of Dataviews associated with a project.

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docs/hyperdatasets/webapp/webapp_exp_comparing.md
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title: Comparing Dataviews title: Comparing Dataviews
--- ---
In addition to [**ClearML**'s comparison features](../../webapp/webapp_exp_comparing.md), the **ClearML Enterprise** WebApp In addition to [**ClearML**'s comparison features](../../webapp/webapp_exp_comparing.md), the ClearML Enterprise WebApp
provides a deep comparison of input data selection criteria of experiment Dataviews, enabling to easily locate, visualize, and analyze differences. provides a deep comparison of input data selection criteria of experiment Dataviews, enabling to easily locate, visualize, and analyze differences.
## Selecting experiments ## Selecting experiments