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Frame / Image Holder Define an area to place an image and cut it to a variety of shapes, the placed image is auto scaled and cropped to fit. Frames are an essential part of creating re-usable Templates. Keybord shortcut (N)

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Intelligent and assistive features and shortcuts can help you save precious time, like separating your audio from video in one click, and clever keyboard shortcuts. We also enable video grouping to keep all your video assets in place.

Please note that if you add premium stock media files to your project or use a feature that is not included in the plan that your Clipchamp account is on, you will not be able to export and save your video until you upgrade to the plan that includes the premium option.

Want even more features? Install extensions to add new languages, themes, debuggers, and to connect to additional services. Extensions run in separate processes, ensuring they won't slow down your editor. Learn more about extensions.

With Microsoft Azure you can deploy and host your React, Angular, Vue, Node, Python (and more!) sites, store and query relational and document based data, and scale with serverless computing, all with ease, all from within VS Code.

By downloading and using Visual Studio Code, you agree to the license terms and privacy statement. VS Code automatically sends telemetry data and crash dumps to help us improve the product. If you would prefer not to have this data sent please go see How to Disable Crash Reporting to learn how to disable it. Third party licenses for the CLI can be found here.

The RFC Series (ISSN 2070-1721) contains technical and organizational documents about the Internet, including the specifications and policy documents produced by five streams: the Internet Engineering Task Force (IETF), the Internet Research Task Force (IRTF), the Internet Architecture Board (IAB), Independent Submissions, and Editorial.

Tagging and annotation have long been some of the most important tasks that a news organization undertakes. The tags that we attach to articles enable nearly everything that happens to that article after publication: how we recommend related content to readers, how search engines index our site, how ads are targeted and more.

Currently, at The New York Times, those tags are applied at the article level. Yet when we look at an article we can see that it actually contains many smaller component parts, like a fact, a person, a recipe or an event. If we could begin to annotate and tag these components, it would enable us to do so much more with that information. New devices, especially those with smaller screens, could make use of smaller chunks of content. New products could be created by extracting components from their original article context and recombining them to create collections or new kinds of experiences. And rather than the archive being a file cabinet full of articles, it would become a corpus of structured news information that could be interrogated and reasoned across.

Fine-grained annotation within an article is a difficult problem that has historically been approached in two ways, both of which have their own challenges. One approach is computational, building rule sets or machine learning processes to take best guesses at where to apply tags. These approaches can be quite successful, but are still not nearly good enough to stand on their own. The other approach is to have people do the tagging. The person writing the article knows the information needed with a high degree of accuracy, but the burden of work required to highlight and annotate every significant phrase is untenable.

Editor is an experimental text editing interface that explores how collaboration between machine learning systems and journalists could afford fine-grained annotation and tagging of news articles. Our approach applies machine learning techniques interactively, as part of the writing process, rather than retroactively. This approach can offload the burden of work to the computational processes, and can create affordances for journalists to augment, edit and correct those processes with their knowledge.

This prototype is comprised of a simple text editor (shown on the left), supported by a set of networked microservices (visualized on the right). The microservices shown here are recurrent neural networks (using ) that are trained to apply New York Times tags to free text, but you can imagine a host of other services that could do things like try to attribute quotes or that know about specific domains like food or sports. As the journalist is writing in the text editor, every word, phrase and sentence is emitted on to the network so that any microservice can process that text and send relevant metadata back to the editor interface. Annotated phrases are highlighted in the text as it is written. When journalists finish writing, they can simply review the suggested annotations with as little effort as is required to perform a spell check, correcting, verifying or removing tags where needed. Editor also has a contextual menu that allows the journalist to make annotations that only a person would be able to judge, like identifying a pull quote, a fact, a key point, etc.

This widget provides an out-of-the-box editing experience to help streamline editing within a web application. It automatically recognizes if there are editable feature layers within the map. The layers that are editable will automatically be used by the widget. It is possible to configure how the Editor behaves by setting itslayerInfos property.This property takes an array of objects which allows configuring the the editing experience for these layers.

The following model formats are currently supported. For additional information, please refer to the ArcGIS Pro documentation. Please note that only one model can be uploaded at a time and zip files should be used for a model with additional texture files.

Snapping can be configured using the controls in the Editor widget's "Settings" menu. By default,snapping is disabled. Toggle "Enable snapping" to enable it. By default, both geometry constraintsand feature-to-feature snapping is enabled. Geometry constraints allow the editor to specify howthey want their geometries to be drawn. For example, when the segment being drawn is nearlyperpendicular to another segment, the cursor may snap to form a precise right angle.Feature-to-feature snapping allows new or existing geometries to be snapped to other geometries,including those in other layers, as shown within the "Snapping layer" list. By default, all layersthat can be configured for snapping are shown in this list. The available layers can be restrictedby updating the Editor's snappingOptions bysetting the FeatureSnappingLayerSource directly.

It is possible to edit related data via the Editor widget. The relationship element provides the functionality needed to configure the relationship within the formTemplate. These elements must be saved within the form for the Editor to support editing related data. This can be accomplished via the Map Viewer's authoring experience or programmatically using the SDK.

Once the form is authored, the Editor automatically checks if there is a formTemplate set on the editable layer, or the widget's corresponding layerInfo. If the form's template is not set or is not configured to contain relationship elements, the Editor will not display the option to edit the relationship data. Additional considerations when using the Editor to edit related data are provided below.

The Editor displays the date field type inthe MapView's timeZone by default.However, when working with the timestamp-offset type, the data is displayed using the stored datevalues from the service. For example, if the stored value is 2023-09-11T22:39:05.242-0400, thenthe Editor will present three inputs to edit the date (9/11/2023), time (10:39:05 PM), and timezone offset (GMT-4) regardless of the MapView time zone.

The big-integer data type is a 64-bit signed integer that can store very large whole numberinteger values with the range of -9007199254740991 and 9007199254740991.Web applications can only edit whole numbers between -9007199254740991 and 9007199254740991. Anyattempts to edit a number value higher or lower than these thresholds will not work and those editswill not be saved.

Authenticated users that are layer owners, administrators or users with full editing privileges will have their elevated user privileges applied in regards to editing behavior and data access. This mimics the behavior available in Map Viewer. To opt out, set esriConfig.userPrivilegesApplied to false.

An array of string values which specifies what end users are allowed toedit. For example, a feature layer with full editing privileges maybe available, but you may only want the end user to have theability to update existing features. In this scenario, set the allowedWorkflowsto only update. ff782bc1db