For Users
Nuxeo Drive
The main feature of the 5.7.1 with DAM. Nuxeo Drive enables bidirectional synchronization of content between the local desktop and the Nuxeo content repository, on premise or in the Cloud. It works with all applications built on the Nuxeo Platform, including Document Management, Digital Asset Management, Case Management, or a custom content-centric application.
DAM
Customizable with Nuxeo Studio
Redesign from the ground up using ContentView, Layouts and widgets. It makes every part of DAM screen (search panel, result panel, asset view) easy to customize using Nuxeo Studio.
- Define the Left Hand Side with your own search layout
- Define the layout for the fields displayed in the thumbnail
- Define the Right Hand Side data for the selected asset (view/edit, as toggable layout)
- Define the Bulk-edit layout
- Define toolbar buttons, add your own
- Define the document types DAM can handle
Browse all Assets from the Repository
All the assets of the repository are displayed (not just the one under "Media Library")
DAM Drag and Drop
You can now drag and drop as many assets as you want in the New Asset window:Assets Browsing
- "New Asset" button:
- Choose among appropriate document types with different metadata
- Import with D&D
- Also in "List" view
- New "Items/Page" dropdown
- New "Refresh" button
- New "Select all" button
- New "Copy" button
- New "Add to worklist" button
Asset View
- New toolbar, with the following buttons:
- Like
- Lock
- Permanent link
- Follow
- Preview
- Add to worklist
- Go to DM view
- New "Tags" feature
- Multiple tags
- Click on a tag to display the list of assets using it
- New "Creator/LifeCycle/Version" display
- New count of people who liked the document
- Smart "Comments" group: Displayed only if there is at least one comment
- Access to workflow actions directly from the DAM UI
Mobile
A new application based on Apache Cordova, bringing multi-OS support. It can be used as a framework to build your own mobile application based on Nuxeo. Using Nuxeo Webengine and JQuery Mobile, it proposes the following features: Saved search, browsing, upload and download of documents, integration with native phone API.
CSV Importer
We have a new module allowing import of documents from a CSV file (1). Here's how it works: click on Import a CSV, choose the CSV file, click on import and documents will be created using properties from the CSV (only scalar metadata).
You can specify a folder in Nuxeo.conf where the importer will look for binaries. Just make sure you put their relative path in the CSV.
User Experience
The platform screens have been redesigned and improved. More than eighty issues about the user experience, user interface and styles have been resolved.
Safe Edit: Never loose your Forms
When editing a document, if the user tries to exit a page with unsaved changes then a popup window asks him if he really wants to leave the page (and if so discard the changes) or if he wants to stay on the page.
Where supported (i.e. localstorage available in the browser), a modification in the edited form triggers the autosave mechanism which records the new input values of the form. If the editing is accidentally lost (e.g. system / browser crash, network failure, etc ...), then the next time the user edits the page, the previous modifications will be detected from the local storage and the user will be asked whether to restore them or not.
Bulk Edit in listing
We have enabled Bulk Editing for document listing. It's now easy to show a form in a popup, displaying any layout you want, and that applies to documents you've selected.
Content Thumbnails
Thumbnail can be automatically generated for pdf or image documents using the main file of a document. It's also possible to contribute a thumbnail adapter for a specific document type or Facet. This is useful mainly for files other than pictures.
The generation of these thumbs is asynchronous, thanks to the use of workers. There is also a default placeholder showed when the generation isn't finished, or if Nuxeo could not generate the thumb.
Back Navigation
We've enhanced the back navigation of your browser using HTML5 pushState.
Permlink available for any Asset
Every Asset now has an accessible and sharable permlink for you to share.
Search
Use tags in searches
You can now add tags in your search form. Whether you're using the advanced search form, any faceted search, a content view query or a query operation. It works because we've added tag suppport to NXQL.
Saved Search Managment Tab
Every saved search is listed on a home tab, a subtab for dam, a subtab for faceted search. You can share those saved searches with other users using the manage/rights tab.
Search Panel
- Search criteria can be saved
- Search layout re-organized for better user friendly interface
- Search is triggered when user clicks "Filter" or "Clear"
- Rename "Keywords" with "Text Search"
- Search by location renamed
- New search by tags
- New search by creation date
- New search by author
- New search by original author
- Search by subjects with a new, better, interface
- Search by coverage with a new, better, interface
Quota
We've made many improvements in the Quota Marketplace package.
Global Quotas Activation, Quotas can be activated in the admin center
Once it's activated, everything statistical are automatically computed.
Administrators can see (in Manage > Quotas > Stats) the following statistics :
- Total volume used (deleted, live, versions) + "/Available space"
- Volume used by deleted files (trash)
- Volume used by archived versions
A graphical representation of those 3 statistics.
A content view with the title "Sub Folders" with the listing of subfolders
- Columns Title, do:Modified, Last Contributor, and Size
- Buttons Delete and Add to cart (to cut/paste)
Return meaningful error message when encountering a Quota error
User Workspace Quota Management Activation
As the Administrator of the system, you can enable Quota on user workspaces (radio button) with a default value (slider). The value is the same for all the user workspaces.
Quota processing now uses its own work queue.
Issues ListBIRT
Marketplace PackageThe BIRT Connector has been aligned on BIRT 4.2.2. It means that you can create your report in BIRT Designer 4.2.2. We also made some significant ergonomy enhancements on the admin center UI and we've added parameter validation when generating a report.
Content Routing
A main workflow tab can be enabled to list running workflow tasks. This way you can select several tasks, and hence do bulk validation.
Content routing prefetch has been made more efficient, which improves performances.
There is a new operation to start a workflow
Redirect user when she has no more rights to read the document after changing the state of the workflow
Filter system workflow related documents from search
Jenkins Report Module
We have a new module available in the marketplace. It's an integration between Jenkins and Nuxeo that we use internally. It helps us keep track of our CI, see it's evolution and easily send a report of the state of the CI to our developers. Here's an example of the email we receive:Hello devs! Here's a status of our CI main jobs on Jenkins. Current number of failing jobs: 3. Current number of unclaimed jobs: 1. Duty comments: To see the complete report click here. Cheers!
For Administrators
Right Audit
This Marketplace package allows to run an audit on all permissions for all users of a document tree. The result is an XLS matrix for every exported document showing permission for each user, including blocking permissions if any.
You can also do an excel export of all the users and groups.
Kerberos Login Module
A Kerberos module has been contributed by OpenWide, allowing authentication throught the Kerberos protocol.
You can also login to Nuxeo using your OpenID, thanks to Nelson Silva.
Monitoring
Use Coda Hale Yammer Metrics to instrument Nuxeo, providing lots of internal metrics, accessible from JMX or Graphite. Read more in our documentation.
Nuxeo.conf new parameters
| Parameter | Default Value | Description |
|---|---|---|
| org.nuxeo.dnd.upload.timeout | 30000 | Maximum time for uploading a file via Drag & Drop to the server. |
| org.nuxeo.dnd.exec.timeout | 30000 | Maximum time for executing import of files uploaded via Drag & Drop |
| org.nuxeo.dnd.extendedmode.timeout | 2000 | Mouseover time to switch to extended mode UI (setting to -1 disables the extended mode) |
MarketPlace/Update Center
nuxectl commands
mp-show: Show Marketplace package(s) information. You must provide the package file(s), name(s) or ID(s) as parameter.
For Developers
Content Automation
Even though we have a new version coming out, we've kept Nuxeo 5.7.1 compatible with the 5.6 automation client.
You can fetch dirty properties of a modified document to send only modified properties with automation client
JSON Marshalling enhancement. You can send POJO in input or parameters. (5.7.1 only)
New operations
Add Message
Category: User Interface
Operation Id: Seam.AddMessage
Add a feedback message to be displayed. The message will be internationalized. You can specify the severity of the message using INFO, WARN and ERROR, INFO being the default. Message parameters are extracted from the context using the 'AddMessage.messageParams'.
Add entry into multi-valued metadata
Category: Document
Operation Id: AddEntryToMultivaluedProperty
Add value to the field expressed by the xpath parameter. This field must be a multivalued metadata.
Convert to given mime-type
Category: Conversion
Operation Id: Blob.Convert
Convert the input file to a file of the given mime-type and return the new file.
Create Asset(s) from file(s)
Category: Dam
Operation Id: Dam.Import
Create Asset(s) from Blob(s) using the FileManagerService.
Create Proxy Live
Category: Document
Operation Id: CreateProxyLive
This operation will create a proxy that points the given document as input. This is like a symbolic link for File System. The proxy will be created into the destination specified as parameter.
Creates directory entries
Category: Services
Operation Id: Directory.CreateEntries
Creates directory entries. Entries are sent as a JSON array. Returns the created entry ids as a JSON array.
Deletes directory entries
Category: Services
Operation Id: Directory.DeleteEntries
Deletes directory entries. Entry ids to be delete are sent through a JSON array. Returns the deleted entry ids as a JSON array.
Get Live Document
Category: Document
Operation Id: GetLiveDocument
Get the live document even if this is a Proxy or Version Document.
Get Nuxeo Principal
Category: Users & Groups
Operation Id: NuxeoPrincipal.Get
Retrieve Nuxeo principal and export it as a DocumentModel. If login parameter is not set, the operation will return information about the current user, otherwise Directory Administration rights are required.
QueryAndFetch
Category: Fetch
Operation Id: Resultset.PageProvider
Perform a query or a named provider query on the repository. The result is paginated. The result is returned as a RecordSet (QueryAndFetch) rather than as a List of Document. The query result will become the input for the next operation. If no query or provider name is given, a query returning all the documents that the user has access to will be executed.
Raise Seam events
Category: User Interface
Operation Id: Seam.RaiseEvents
Raise Seam events without parameters. This is a void operation - the input object is returned back as the output
Reads directory entries
Category: Services
Operation Id: Directory.ReadEntries
Reads directory entries. Entry ids to be read are sent as a JSON array. Returns the entries as a JSON array of JSON objects containing all fields.
Remove Entry Of Multivalued Property
Category: Document
Operation Id: RemoveEntryOfMultivaluedProperty
Removes the first entry of the giving value in the multivalued xpath, does nothing if does not exist. If 'is Remove All' is checked, all entry instances in the list will be removed. if not then just the first one found will be removed.
UI Selected documents form list
Category: Fetch
Operation Id: Seam.GetDocumentsFromSelectionList
Fetch the documents selected in the selection list passed as a parameter. If the list name is empty, the current folder selection list is used.
Updates directory entries
Category: Services
Operation Id: Directory.UpdateEntries
Updates directory entries. Entries to be updated are sent as a JSON array. Returns the updated entry ids as a JSON array of JSON objects containing all fields.
CSS 3 Support in Theme Engine
The flute CSS parser has now been replaced by phloc-css, allowing CSS3 to be used in the Theme engine.
UI Style Guide
The Nuxeo UI Style Guide is an online help to design your content, explore all the available CSS classes for the different elements, and to check the list of icons embedded in the platform.
UI Framework
Widget Label properties now accept an EL expression. This allows you to have dynamic labels.
Every richfaces ajax call use a global default ajax event queue. You can of course still specify your own queue. This results in more stable pages.
HTML5 PlaceHolder
You can use the HTML5 placeHolder attribute on inputtext and textarea. It's available as a widget property. You can put text(that will be translated) or an EL.
New drop zone Widget
This widget allows you to execute an operation with the files you've dropped as input.
Widget Actions
One can use automatic JS confirmation popup. If you add a confirmMessage property in the actions, it generates the appropriate js method. It accepts any EL as parameter. Here's an example:
<action id="JenkinsReportSendMail"> <properties> <property name="confirmMessage">label.jenkins.sendMail.confirm</property> <propertyList name="confirmMessageArgs"> <value>#{docSuggestionActions.getDocumentWithId(currentSuperSpace.id) .getPropertyValue('jenkinsreports:report_email')}</value> </propertyList> </properties> </action> messages: label.jenkins.sendMail.confirm=This will send an email to {0}, are you sure that you would like to continue?
You can now include widgets that render actions. This is particularly useful in Nuxeo Studio. This allows us to easily blend different action types like a submit button, an outgoing link and an action that opens a fancybox. You can also merge all of them in any order you want.
We have a better support of form inside fancybox opened by actions. You can submit the associated form without submitting every other form on the page. No need to do nested form anymore.
You can mix any type of action. If one action does not support ajax (like a download), it can be in the same tool bar as an ajax action.
You can associate selected documents of a content view to actions outside the content view. That's how we made bulk edit.
We allow resetting of JSF components state when using ajax. JSF action listener #{jsfResetActions.resetComponents} can be used in actions that need to reset all components in the same JSF naming container.
Nuxeo Visible Content Store (VCS)
Enhancements
Single datasource mode, removes the extra cost of XA transactions when all datasources points to the same database (which is the most common setup). It simplifies configuration and enhances performance.
Soft delete, more efficient deletion using delayed batching.
Optimized id generation, using database-native sequences (PostgreSQL, SQL Server) or UUIDs (PostgreSQL). This improves performance and database size.
Flag to disable proxies, if you don't use proxies, then this removes the extra work at the SQL level and improves performance.
Allow attaching schemas to proxies
Database Support
Microsoft SQL Server 2012 support, including Azure.
PostgreSQL 9.2 support for cluster mode (non-clustered mode already worked in Nuxeo 5.6).
IBM DB2 9.5 preliminary support (non-optimized, therefore only for small databases).
NXQL
See the NXQL Documentation for the current state of NXQL.
ecm:tag: allows NXQL queries on a document's tags.
ecm:proxyTargetId: allows NXQL queries on the id of the target of a proxy.
ecm:proxyVersionableId: allows NXQL queries on the id of the versionable document of a proxy (the versionable document is the one from which the version to which the proxy is pointing was created).
Misc
Various performance enhancements for PostgreSQL, Oracle and SQL Server
Added "NotFulltextIndexable" facet to avoid indexing documents with this facet.
Allow clustering for Oracle on Amazon RDS.
Optimize complex list property update (use UPDATE instead of DELETE + INSERT).


TIL: More Colored Terminal text on Windows: AnsiCon
A reminder for myself:
ANSI escape characters don't work properly in Windows terminals:
To make them work properly, use
AnsiCon. Unzip it somewhere
permanent (eg. %ProgramFiles%\ansicon
) and install it with:
ansicon.exe -i
start a new terminal, and lo:
Fine tune the appearance of the programs generating the color, for example customise 'hg diff' by editing \~/.hgrc:
[extensions] color = [color] status.modified = yellow bold status.unknown = white status.deleted = red_background white bold diff.deleted = red bold diff.inserted = green bold diff.file_a = white diff.file_b = white diff.diffline = white_background black diff.extended = yellow bold diff.hunk = underline black diff.changed = yellow bold
ANSI is correctly stripped out if the output of a program is not a terminal, so the colored output won't interfere with saving to files nor machine-parsing of the text:
Finally, insert some ANSI codes into your prompt, by setting environment variable PROMPT:
set PROMPT=$E[0;36m$P$_$E[36;1m$G$E[0m$S
Multiple posts on colors and terminal text is perhaps a bit obsessive of me. I think I'm all done now.


Reactive
public extension Reactive where Base: Reachability
-
Global to observe when
Reachability
status changes.Declaration
Swift
static var reachabilityChanged: Observable<Reachability> { get }
-
Global to observe when
Reachability.Connection
status changes.Declaration
Swift
static var status: Observable<Reachability.Connection> { get }
-
Global to observe a
Bool
whenReachability.Connection != .unavailable
.Declaration
Swift
static var isReachable: Observable<Bool> { get }
-
Global to observe a
Void
whenReachability.Connection != .unavailable
.Declaration
Swift
static var isConnected: Observable<Void> { get }
-
Global to observe a
Void
whenReachability.Connection == .unavailable
.Declaration
Swift
static var isDisconnected: Observable<Void> { get }
-
Rx
Observable
to observe whenReachability
status changes.Declaration
Swift
var reachabilityChanged: Observable<Reachability> { get }
-
Rx
Observable
to observe whenReachability.Connection
value changes.Declaration
Swift
var status: Observable<Reachability.Connection> { get }
-
Instance variable to observe a
Bool
whenReachability.Connection != .unavailable
.Declaration
Swift
var isReachable: Observable<Bool> { get }
-
Instance variable to observe a
Void
whenReachability.Connection != .unavailable
.Declaration
Swift
var isConnected: Observable<Void> { get }
-
Instance variable to observe a
Void
whenReachability.Connection == .unavailable
.Declaration
Swift
var isDisconnected: Observable<Void> { get }


--- layout: post title: SAML signout categories: [] tags: serviceapi web-client authentication status: publish type: post published: true meta: {} ---
In a previous post I show how to use Component Space to add SAML support to the Web Client, here I add a sign-out button.
Set useADFS to true in hprmServiceAPI.config, for example:
<setup databaseId="J1" searchAhead="false" advancedSearch="false" workpath="C:\HP Records Manager\ServiceAPIWorkpath\Uploads" useADFS="true"/>
If you plan to sign your logout request then you will need a certificate, either encrypt the password or store the certificate in the Windows certificate store as described in this Component Space document.
To allow for notification when the user's session has expired add the keep alive loop. To do this edit _Initialisation.cshtml (or _Shared.cshtml in later versions) and comment out the RMStayALive function, then add this new version:
var RMStayALive2 = function () { var makeRequest = function () { $.getJSON(HP.HPTRIM.TrimClient.getServiceAPIUrl() + "/Location/me", function (data, status, xhr) { }).fail(function () { if (confirm("Your session has expired, do you wish to re-authenticate?")) { top.location = HPRMWebConfig.virtualDirectory; } }); } setInterval(makeRequest, (60 * 1000)); }();
The process above is shown in this video.


These applications demonstrate reverse geocoding with what3words using ArcGIS API for JavaScript.
View live View code »


You can add a loading message by adding text inside the markup.
You can use loading as block element.
mod-fullPage


Congratulations! If the start of this line is "I've been changed" then the JavaScript ran onload + used jQuery.documentation
Run Some Ajax
This text should get replaced via ajax


Secret Agent Collin:
Right. When you want to resume your training, just let me know. Now go, I have things to do.


| Cards
|
- Complete specical tasks to get cards, such as playing during expansion releases or on specific days.
|
| Dust
|
- Disenchant extra cards via the "Disenchant Extra Cards" button.
- Craft non-golden cards starting with the most useful.
- Craft golden versions of cards that cannot be obtained otherwise, such as the Beckoner of Evil.
- Craft golden cards starting with your favorites.
|
| Gold
|
- Purchase the first tier of every Solo Adventure available for purchase with gold, starting with the oldest. HIGHEST PRIORITY because wild adventures cannot be purchased with gold.
- Unlock and complete Normal and Class Challenges on all Solo Adventure tiers.
- If you need cards from packs that aren't offered as Arena rewards, buy specific card packs with gold.
- Try to get as many wins as possible in the Arena.
- Win 3 games against other players as many times as possible to gain 10 gold each time, up to 100 gold for 30 wins per day.
|
| Packs
|
- Win Tavern Brawl at least once every week. Depending on how much gold you have, you might not have to skip Heroic Tavern Brawl and other paid brawls.
- Complete specical tasks to get packs, such as picking your tournament champions, playing during expansion releases, and playing on specific days.
|
| Quests
|
- Reroll 50 gold quests, then difficult 60+ gold quests.
- You shouldn't end a day with 3 quests remaining. Complete as many quests as possible, as sometimes special quests will be added during special events. These quests will overwrite ordinary quests if you do not have sufficient space.
- You can avoid completing 50 gold quests that you can just reroll another day to maximize gold gain.
|
| Ranked
|
- Win at least 5 standard or wild ranked games every monthly season.
- Get at least rank 20 in standard or wild every monthly season.
- Improve your rank as much as possible, as every additional rank improves your reward at the end of the season. Rewards greatly improve at rank 15, 10, 5, and legend.
|


Search
The api uses a weird calling, you have to use the abbreviation of the currency followed by the suffix btc. For example, ethbtc is used for etherium and bitcoin is btcbtc.


Datasets
Wide Multi-Channel Presentation Attack (WMCA) dataset
Idiap Research Institute
Near Infrared Face Database
IIT Kharagpur
Source codes
Multi-Channel CNN for face presentation attack detection
Idiap Research Institute
Deep Pixelwise Binary Supervision (DeepPixBiS) for face presentation attack detection
Idiap Research Institute
DFace PAD using multi-channel autoencoders
Idiap Research Institute


Other than 1992 and 2018, the average budget of movies is in the ten millions. In our dataset, 1992 had only one movie reported with no budget. Thus in this sense, the year should be disregarded. 2018 has a budget that is significantly less than surrounding years, as well as an extraordinarily greater average revenue. This is interesting since 2018 does not have a significant event that the project looks at. However, looking at the total revenue brought in in the year 2018, we can see that the total revenue is comparable to the total revenue brought in in 2019. This would suggest that 2018 had a low number of movies produced, with a few high-grossing movies that would bring up the average. Considering the trends we found in the finances of the movie industry, one planning to film a movie should put aside a budget that is over ten million dollars.


string ob_deflatehandler ( string $data , int $mode )
Deflate output handler
For use with ob_start(). Note: This output handler can only be used once. The deflate output buffer handler can only be used once. It conflicts with ob_gzhandler() and zlib.output_compression as well and should not be used after mbstring extension's mb_output_handler() and session extension's URL-Rewriter (AKA session.use_trans_sid).


Navy decorates 16 new Rear Admirals
by Agency ReportThe Nigerian Navy on Thursday decorated (Shipping of stripes) 16 newly promoted Rear Admirals with their new ranks.
The Navy Board recently approved the promotion of 140 naval officers to the next ranks in the Nigerian Navy.
Speaking at the decoration of the recently elevated flag officers in Abuja, the Chief of Naval Staff, Vice Admiral Ibok Ete-Ibas, said the 16 senior officers had distinguished themselves over time to earn the confidence and endorsement of President Muhammadu Buhari.
He said the significance of the occasion was the critical need for quality leadership at the peak of every organisation for optimal realisation of its objectives.
“Nowhere is such courageous and astute leadership required like in the armed forces where your decisions on the employment of men and materials have profound impact on national security.
“While the gates are open to many on entry into Service, only the most dedicated and loyal rise to the very pinnacle of the profession.
“Today, I am delighted to introduce our latest addition to the cream of the Nigerian Navy leadership. The beneficiaries of the most revered 2-star flag rank of Rear Admirals,” he said.
He said the support from the Federal Government had enabled the Service to make considerable gains in critical areas such as fleet renewal and infrastructural development with attendant impact on operational service delivery.
“While I will continue to canvass for sustained resource allocation for the Nigerian Navy, I wish to pledge the unalloyed commitment of the officers and ratings of the Service to a safe, secure and stable maritime environment for the prosperity of the nation,” he said.
Also speaking, the Minister of Defence, Maj.-Gen. Bashir Magashi, (Rtd), congratulated the newly promoted senior officers for attaining the enviable rank.
The minister noted that promotion comes with greater responsibilities and urged them to redouble their efforts in the discharge of their duties.
(NAN)


--- layout: post title: What I Did For My Summer Holidays date: 2006-08-21 00:00:00 category: personal ---
I've been away for a couple of weeks, and am now playing catch-up with piles of email and news.
I can't remember ever taking 2 consecutive weeks off any time in the last 11 years that I've been working (though I may have at some point). I've certainly never taken a week off without having any solid plans for it - and it's been fab.
Things I did:
Lots of people have been busy this week too:
And I failed to get around to:
Back to work tomorrow, and whilst it's been a lovely break, I'm actually rather excited about getting stuck into FP things again. I've had a chance to think and refresh myself.


Type Theory for The Working Rustacean
Rust really hits a sweet spot with respect to programming languages on account of a) its usefulness when working at a low level, coupled with b) its style of type system. Because of a), Rust can be—and is—used in places which tend to safety-critical: cyber-physical systems, autonomous vehicle infrastructure, robotics, etc. When building systems for these safety-critical environments, one also often formally proves properties about their software. That’s where b) comes in.
···
Rust’s type system is borne from the same ilk as those used in proof assistants like Agda, Coq, or Lean. Because of this, we can use Rust’s type system in similar ways we’d use a proof assistant to produce safer and more correct programs. This is envisioned by reducing the language of these disparate systems into the lingua franca of type theory.
This talk will explore using (and abusing) Rust’s type system to mimic the proofs one writes about their Rust programs while also enumerating how this mimicry is derived from common ground in the worlds of types or categories.


This week we had 2 projects, first we had to embroid somethhing, I did a hat with a WRA LOGO just like the one they sell in the bookstore for 10 bucks, then we did a pillow case, sewing the tissue together
this is my hat, exactly the same as the ones they sell in the bookstore
my pillow case that has a lot of superheroes on it
Go back Home


EvalAI is an Open Source Platform for organizing and participating in AI challenges
Several partner organizations already host their challenges on EvalAI
PARTICIPATE
Featured Challenges
Lorem ipsum dolor sit amet, cu eam zril postulant, libris dolorum omittantur ad sea. No simul aliquando sea.
-Lorem Ipsum


About
Inspired by travel, nature and culture, I am a visual artist based in Brighton who loves to work with bright colour and bold patterns.
I have a passion for creating large scale murals and enjoy the challenge of upscaling my designs to
suit the space.
I run art classes in the Brighton Lanes at Clarke’s Art Shop studio/gallery, UK. My classes are very relaxed and fun with loads of different themes to choose from including; spray painting, watercolour, Lino printing and fabric
painting.
The classes are suitable for beginners even if you have never picked up a pencil before!
Up-coming classes
Due to Covid-19 I am running free online art classes, which can be found here...
Zieler Live Art Classes


pypcd package¶
Submodules¶
pypcd.nea_pc_format module¶
pypcd.numpy_pc2 module¶
Functions for working with PointCloud2.
-
pypcd.numpy_pc2.
arr_to_fields
(cloud_arr)[source]¶ Convert a numpy record datatype into a list of PointFields.
-
pypcd.numpy_pc2.
array_to_pointcloud2
(cloud_arr, stamp=None, frame_id=None, merge_rgb=False)[source]¶ Converts a numpy record array to a sensor_msgs.msg.PointCloud2.
-
pypcd.numpy_pc2.
array_to_xyz_pointcloud2
(cloud_arr, stamp=None, frame_id=None, merge_rgb=False)[source]¶ convert an Nx3 float array to an xyz point cloud. preserves (scalar) dtype of input. TODO: untested
-
pypcd.numpy_pc2.
array_to_xyz_pointcloud2f
(cloud_arr, stamp=None, frame_id=None, merge_rgb=False)[source]¶ convert an Nx3 float array to an xyz point cloud. beware of numerical issues when casting from other types to float32.
-
pypcd.numpy_pc2.
array_to_xyzi_pointcloud2f
(cloud_arr, stamp=None, frame_id=None, merge_rgb=False)[source]¶ convert an Nx4 float array to an xyzi point cloud. beware of numerical issues when casting from other types to float32.
-
pypcd.numpy_pc2.
array_to_xyzl_pointcloud2f
(cloud_arr, stamp=None, frame_id=None, merge_rgb=False)[source]¶ convert an Nx4 float array to an xyzi point cloud. beware of numerical issues when casting from other types to float32.
-
pypcd.numpy_pc2.
arrays_to_xyzi_pointcloud2f
(cloud_arr, intensity_array, stamp=None, frame_id=None, merge_rgb=False)[source]¶ convert an Nx3 float array and N array to an xyzi point cloud. beware of numerical issues when casting from other types to float32.
-
pypcd.numpy_pc2.
get_xyz_points
(cloud_array, remove_nans=True, dtype=<type 'float'>)[source]¶ Pulls out x, y, and z columns from the cloud recordarray, and returns a 3xN matrix.
-
pypcd.numpy_pc2.
merge_rgb_fields
(cloud_arr)[source]¶ Takes an array with named np.uint8 fields ‘r’, ‘g’, and ‘b’, and returns an array in which they have been merged into a single np.float32 ‘rgb’ field. The first byte of this field is the ‘r’ uint8, the second is the ‘g’, uint8, and the third is the ‘b’ uint8.
This is the way that pcl likes to handle RGB colors for some reason.
-
pypcd.numpy_pc2.
pointcloud2_to_array
(cloud_msg, split_rgb=False, remove_padding=True)[source]¶ Converts a rospy PointCloud2 message to a numpy recordarray
Reshapes the returned array to have shape (height, width), even if the height is 1.
The reason for using np.fromstring rather than struct.unpack is speed… especially for large point clouds, this will be <much> faster.
-
pypcd.numpy_pc2.
pointcloud2_to_dtype
(cloud_msg)[source]¶ Convert a list of PointFields to a numpy record datatype.
pypcd.pdutil module¶
pypcd.pypcd module¶
Read and write PCL .pcd files in python<EMAIL_ADDRESS>2013-2018
- TODO better API for wacky operations.
- TODO add a cli for common operations.
- TODO deal properly with padding
- TODO deal properly with multicount fields
- TODO better support for rgb nonsense
-
class
pypcd.pypcd.
PointCloud
(metadata, pc_data)[source]¶ Bases:
object
Wrapper for point cloud data.
The variable members of this class parallel the ones used by the PCD metadata (and similar to PCL and ROS PointCloud2 messages),
pc_data
holds the actual data as a structured numpy array.The other relevant metadata variables are:
version
: Version, usually .7fields
: Field names, e.g.['x', 'y' 'z']
.size.`: Field sizes in bytes, e.g. ``[4, 4, 4]
.count
: Counts per field e.g.[1, 1, 1]
. NB: Multi-count field support is sketchy.width
: Number of points, for unstructured point clouds (assumed by most operations).height
: 1 for unstructured point clouds (again, what we assume most of the time.viewpoint
: A pose for the viewpoint of the cloud, as x y z qw qx qy qz, e.g.[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]
.points
: Number of points.type
: Data type of each field, e.g.[F, F, F]
.data
: Data storage format. One ofascii
,binary
orbinary_compressed
.
See PCL docs for more information.
-
pypcd.pypcd.
point_cloud_to_fileobj
(pc, fileobj, data_compression=None)[source]¶ Write pointcloud as .pcd to fileobj. If data_compression is not None it overrides pc.data.
-
pypcd.pypcd.
make_xyz_point_cloud
(xyz, metadata=None)[source]¶ Make a pointcloud object from xyz array. xyz array is cast to float32.
-
pypcd.pypcd.
make_xyz_rgb_point_cloud
(xyz_rgb, metadata=None)[source]¶ Make a pointcloud object from xyz array. xyz array is assumed to be float32. rgb is assumed to be encoded as float32 according to pcl conventions.
-
pypcd.pypcd.
make_xyz_label_point_cloud
(xyzl, label_type='f')[source]¶ Make XYZL point cloud from numpy array.
TODO i labels?
-
pypcd.pypcd.
save_txt
(pc, fname, header=True)[source]¶ Save to csv-style text file, separated by spaces.
TODO: - support multi-count fields. - other delimiters.
-
pypcd.pypcd.
cat_point_clouds
(pc1, pc2)[source]¶ Concatenate two point clouds into bigger point cloud. Point clouds must have same metadata.
-
pypcd.pypcd.
add_fields
(pc, metadata, pc_data)[source]¶ Builds copy of pointcloud with extra fields.
Multi-count fields are sketchy, yet again.
-
pypcd.pypcd.
build_ascii_fmtstr
(pc)[source]¶ Make a format string for printing to ascii.
Note %.8f is minimum for rgb.
-
pypcd.pypcd.
encode_rgb_for_pcl
(rgb)[source]¶ Encode bit-packed RGB for use with PCL.
Parameters: rgb – Nx3 uint8 array with RGB values. Return type: Nx1 float32 array with bit-packed RGB, for PCL.
pypcd.sautil module¶
Utilities to operate on structured array files directly,
such as the pc_data
in PointCloud
objects.
-
pypcd.sautil.
get_xyz_array
(pc_data, dtype=<type 'numpy.float32'>)[source]¶ get Nx3 array from structured array
-
pypcd.sautil.
get_xyz_viewpoint_array
(pc_data, dtype=<type 'numpy.float32'>)[source]¶ get Nx3 array from structured array


Project: Resource-Hub
Project: Resource-Hub Home
Project: Resource-Hub : Testing
Created by
Bryan Guner
on Mar 12, 2021
Instructions
Related articles
Page:
Testing


Sample form:
* marked fields are required
First Name: *
Last Name: *
Email: *
Phone: *
Subject: *
Comments:


Figure 1: Warning dialog: non-fatal
Figure 2: Error dialog: fatal
Figure 3: Warning messages detailed in the Message window
During any of the processes Extrapolate, Transform or Extract parameters, which can be executed by selecting the required item from the Actions menu, the user may be presented with a warning (see Figure 1) or error dialog (see Figure 2). In both cases, the warning or error message will be recorded at the point it occurred in the Message window (see Figure 3). A warning message indicates a non-fatal error i.e. the process has been completed despite the warning. An error dialog indicates that the process was terminated before completion and must be executed again, once the necessary changes have been made to the input parameters.
The most common warnings and errors occur during Extrapolation
and are described below:
4.4.1 Common Warnings
| Warning message | Cause | Remedy |
| Ran out of iterations before convergence | Maximum number of tail-fitting iterations reached and no convergence achieved | If necessary, increase the maximum number of iterations allowed (see Extrapolation) |
| Positive gradient during estimation of sigma | Initial guess at sigma before fitting the sigmoid tail was poor | If necessary, change the tail-fitting limits (see Extrapolation) |
| POLINT failed | Two q values in the extrapolated dataset were identical within rounding errors | Adjust the input data accordingly |
4.4.2 Common Errors
| Error message | Cause | Remedy |
| Back-extrapolate channel optimisation has failed | Problems with back-extrapolation (e.g. due to no upturn in intensity as the beamstop is approached) | Change the start of data limit (see Extrapolation) |
| Negative intensities in experimental data, or Data contains negative intensities | The scattering data contains negative intensities | Edit the values or add a constant to the data using OTOKO |
| X axis should be a static image dynamic found, or Expecting static Q axis received dynamic | The q-axis file contains multiple frames | Check that the correct file is being used (if necessary a "dummy" q-axis file can be generated with the OTOKO .XAX command |
| READASCII_ returning IRC=0 | There is a problem with the file that the program is attempting to access (check the Message Window for any additional details) | |
| Exceeded maximum number of steps for F.T. | The maximum number of steps for the Fourier transform is 511 | Change the maximum value of d and/or the step in d in the Edit - Parameters... - Transform tab |
| More than 2048 channels in extrapolation | The subroutines for generating a volume fraction profile cannot handle data with more than 2048 q-points | Adjust the input data accordingly |


{% from "macros/_form.html" import render_form %} {% set page_title = "Make a proposal" %} {% extends "layouts/base.html" %} {% block body_classes %}{% endblock %} {% block body %}
Which school do you want to propose the class to?


You have been invited to join an ongoing game. Click the play button below to join the game.
Total players: {{ game.players.length }}
Game Winner
{{ game.meta.gameWinner.username }}


Get WEB HOSTING FROM INDIA'S #1 HOSTING COMPANY @ reliable price and with maximum service like personal emailing,search engine otimisation.
We are creative thinkers with a focus on modern web production. We use the latest tools available to help build your brand's digital presence.
With an increasing importance being given to smart phones, and mobile apps, it has become immensely important to include app development as part of web design services.


| gdata.tlslite.api | index /usr/local/google/home/afshar/src/external-gdata-release/google3/src/gdata/tlslite/api.py |
Import this module for easy access to TLS Lite objects.
The TLS Lite API consists of classes, functions, and variables spread
throughout this package. Instead of importing them individually with::
from tlslite.TLSConnection import TLSConnection
from tlslite.HandshakeSettings import HandshakeSettings
from tlslite.errors import *
.
.
It's easier to do::
from tlslite.api import *
This imports all the important objects (TLSConnection, Checker,
HandshakeSettings, etc.) into the global namespace. In particular, it
imports::
from constants import AlertLevel, AlertDescription, Fault
from errors import *
from Checker import Checker
from HandshakeSettings import HandshakeSettings
from Session import Session
from SessionCache import SessionCache
from SharedKeyDB import SharedKeyDB
from TLSConnection import TLSConnection
from VerifierDB import VerifierDB
from X509 import X509
from X509CertChain import X509CertChain
from integration.HTTPTLSConnection import HTTPTLSConnection
from integration.POP3_TLS import POP3_TLS
from integration.IMAP4_TLS import IMAP4_TLS
from integration.SMTP_TLS import SMTP_TLS
from integration.XMLRPCTransport import XMLRPCTransport
from integration.TLSSocketServerMixIn import TLSSocketServerMixIn
from integration.TLSAsyncDispatcherMixIn import TLSAsyncDispatcherMixIn
from integration.TLSTwistedProtocolWrapper import TLSTwistedProtocolWrapper
from utils.cryptomath import cryptlibpyLoaded, m2cryptoLoaded,
gmpyLoaded, pycryptoLoaded, prngName
from utils.keyfactory import generateRSAKey, parsePEMKey, parseXMLKey,
parseAsPublicKey, parsePrivateKey
| Data | ||
| cryptlibpyLoaded = False gmpyLoaded = False m2cryptoLoaded = False prngName = 'os.urandom' pycryptoLoaded = True |


hermes
site is working correctly.Now go to any folder with a static website and type hermes deploy
. Optionally you may define deploy target in the command with hermes deploy --target=s3://mywebsite.com
.
If you have any questions, read the full documentation at hermes.simse.io/docs


Exhibition marks centenary of artist Modigliani's death
The figures are distinctly Modigliani, the elongated faces and bodies, sometimes the blank eyes. Each portrait telling a different story about the artist's life.
He experienced sickness in childhood which would later impact on his health in later life and also his ability to pursue his art.
Several of these portraits are of Jeanne Hébuterne whom he loved and lived with on the Cote d'Azur.
An exhibition in the artist's birthplace of Livorno, Italy, curated by Marc Restellini with Sergio Risaliti, has fourteen of Modigliani's paintings and twelve of his drawings which the museum says are rarely shown to the public.
Alongside Modigliani's works are 100 or so other masterpieces collected by Jonas Netter, which represent the École de Paris.
Highlights at Museo della Città in Livorno include paintings by Chaïm Soutine, Maurice Utrillo, Suzanne Valadon and Andrè Derain.
"It's very important exhibition even because it's in Livorno, native city of Amedeo Modigliani, 100 years from the death of the painter who became permanently famous when he moved to Paris, capital city of the twentieth century" Sergio Risaliti, art historian explains
The exhibition is called "Modigliani and the adventure of Montparnasse".
Paris' Montparnasse became a magnet for artists before the First World War.
As well as Modigliani and other artists, the district drew writers, poets politicians, and businessmen from all over the world.
It was where Modigliani could immerse himself in the latest schools and trends in art.
This exhibition includes a large selection of works the painters who shared passion for art.
They all come from the prestigious Netter and Aleksandre collections.
Modigliani was just 35 years old when he died of TB in 1920.
His artistic life spanned a little more than ten years, and even this was sometimes marred by his poor health and reduced finances.
Modigliani gained the esteem of his contemporaries during an era of artistic renewal.
Even Pablo Picasso, insisted on having one of his paintings for his private collection and he introduced him to his circle of artists, collectors and art dealer.
Risaliti believes Modigliani was deeply influenced by his environment.
"Modigliani knew how to soak up influences from everyone, especially where to find new life and inspiration in the non-European and non-traditional world. As a sea-faring man, someone who lived in a city with a harbour, the port of Livorno, he understood that you can't live there without encountering people coming into the port from elsewhere, with their primitive arts, archaic cultures, and far Eastern influences, that gave new vigour to the incredible language of Modigliani, he says.
Modigliani died poor and mostly underrated, but according to Restellini that did not stop him becoming a landmark in the world of art.
The exhibition will continue until February 16, 2020.


Congratuation!! You found it!!
<
Now!
You are one of them
Somebody
Dapibus ac facilisis in
Morbi leo risus
Porta ac consectetur ac
Vestibulum at eros
Rate the treasure difficulty


Trump says he met with the "president of the Virgin Islands." *cough* he is the president of the Virgin islands, which is a US territory pic.twitter.com/8MLjqjTGb7— David Mack (@davidmackau) October 13, 2017
Trump says he met with the "president of the Virgin Islands." *cough* he is the president of the Virgin islands, which is a US territory pic.twitter.com/8MLjqjTGb7


In the early 1960s, my paternal grandmother went mad and was carted off to a Mercy Home for the Baffled and Bewildered. It was run by an order called the Sisters of Charity of Jesus and Mary, and my grandmother spent her final decade contented and happy. Surrounded by nuns, she perhaps believed that she had realised a lifelong ambition, and become a nun herself. The home, in Lytham St Annes, was—still is—called Stella Matutina.
More than half a century later, at the beginning of last year, my brother acquired a dog. It was the first time he had ever had a pet pooch and, by all accounts, possession of the dog “changed his life”. The name he gave to this dog was Stella Matutina.
I find this psychologically fascinating. It would be intriguing to plumb the depths of my brother's psyche in relation to dogs and mad grandmothers and nuns. As the psychiatrist remarked in Fawlty Towers, “there's enough material there for an entire conference”.


tailscale up
Connects the client to the Tailscale network.
In version 1.8 and above, command line arguments are stored and reused until they're overwritten or `--reset` is called.
More information: home page
- Connect to Tailscale:
sudo tailscale up
- Connect and offer the current machine to be an exit node for internet traffic:
sudo tailscale up --advertise-exit-node
- Connect using a specific node for internet traffic:
sudo tailscale up --exit-node=exit_node_ip
- Connect and block incoming connections to the current node:
sudo tailscale up --shields-up
- Connect and don't accept DNS configuration from the admin panel (defaults to `true`):
sudo tailscale up --accept-dns=false
- Connect and configure Tailscale as a subnet router:
sudo tailscale up --advertise-routes=<IP_ADDRESS>/24,<IP_ADDRESS>/24
- Connect and accept subnet routes from Tailscale:
sudo tailscale up --accept-routes
- Reset unspecified settings to their default values and connect:
sudo tailscale up --reset


@import gospeak.core.domain.{Comment, Event, Group, User} @import gospeak.web.pages.published.groups.routes.GroupCtrl @import gospeak.web.utils.UserReq @(group: Group, event: Event, orga: User, comment: Comment)(implicit req: UserReq[AnyContent])
Hi @orga.firstName,
@req.user.name.value sent a message for the @event.name.value event:
You can view it on Gospeak to answer if you want.
The Gospeak team


@*
* Copyright 2023 HM Revenue & Customs
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*@
@(params: Map[String, Any])
Valuation Office Agency
|
|
|
GOV.UK |
|
Valuation Office Agency
|
Rent and lease details
@params("referenceNumber")
@params("postcode")
@params("expiryDate")
|
|
|
|


Spring Data REST
HAL index
Builtin HTML browser for all entities
schema in Application-Level Profile Semantics (ALPS)
schema in JSON-Schema (use "Accept: application/schema+json" request header!),
Listing of all entries in the "persons" collection (using the Excerpt projection)
First entry of the "persons" collection
First entry of the "persons" collection in "justFullname" projection
Search entry point for the "persons" collection


Main Page Class Hierarchy Alphabetical List Compound List File List Compound Members File Members
TDisplay Class Reference
Display information.
More...
#include <system.h>
Inheritance diagram for TDisplay::
List of all members.
Public Types |
| enum | videoModes { smBW80 = 0x0002,
smCO80 = 0x0003,
smMono = 0x0007,
smFont8x8 = 0x0100
} |
Detailed Description
TDisplay provides low-level video functions for its derived class TScreen.
These, and the other system classes in `system.h', are used internally by TVision and you would not need to use them explicitly for normal applications.
Some old stuff is removed.
Definition at line 458 of file system.h.
Member Enumeration Documentation
|
enum TDisplay::videoModes
|
|
|
|
Mnemonics for the video modes used by TDisplay.
This port uses smCO80 and smMono only.
Definition at line 466 of file system.h. |
The documentation for this class was generated from the following file:
Generated at Sat Sep 22 20:19:23 2001 for TVision by
<IP_ADDRESS> written by Dimitri van Heesch,
© 1997-2001


Kabosu is a build server, designed for it's ease of use and small memory footprint.
--- layout: default title: Kabosu permalink: /software/kabosu/ section: software ---
Kabosu is a build server, designed for it's ease of use and small memory footprint.


The Pomodoro Technique
It is a time management method developed by Francesco Cirillo in the late 1980s. The technique uses a timer to break down work into intervals, traditionally 25 minutes in length, separated by short breaks. Each interval is known as a pomodoro.
The original six steps
- Decide on the task to be done.
- Set the pomodoro timer (traditionally to 25 minutes).
- Work on the task.
- End work when the timer rings and put a checkmark on a piece of paper.
- If you have fewer than four checkmarks, take a short break (3–5 minutes), then go to step 2.
- After four pomodoros, take a longer break (15–30 minutes), reset your checkmark count to zero, then go to step 1.


Radius
Coverage
Upper Percentile
November, 2020
October, 2020
September, 2020
August, 2020
July, 2020
June, 2020
May, 2020


Global Functions in Global Namespace C++
in Sourcefile environment.h
- uno_Environment_enter
- extern "C"
void uno_Environment_enter(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Enter an environment explicitly.
- Parameters
| pEnv |
the environment to enter; NULL leaves all environments
|
- Since
- UDK 3.2.7
- uno_Environment_invoke
- extern "C"
void uno_Environment_invoke(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Invoke the passed function in the given environment.
- Parameters
| pEnv |
the target environment
|
| pCallee |
the function to call
|
| ... |
the parameters passed to the function
|
- Since
- UDK 3.2.7
- uno_Environment_invoke_v
- extern "C"
void uno_Environment_invoke_v(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Invoke the passed function in the given environment.
- Parameters
| pEnv |
the target environment
|
| pCallee |
the function to call
|
| pParam |
the parameter pointer passed to the function
|
- Since
- UDK 3.2.7
- uno_Environment_isValid
- extern "C"
int uno_Environment_isValid(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Check if a particular environment is currently valid, so
that objects of that environment might be called.
- Parameters
| pEnv |
the environment
|
| rtl_uString |
** pReason the reason, if it is not valid
|
- Return
1 == valid, 0 == invalid
- Since
- UDK 3.2.7
- uno_createEnvironment
- extern "C"
void uno_createEnvironment(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Creates an environment. The new environment is anonymous (NOT publicly registered/ accessible).
- Parameters
| ppEnv |
out parameter of environment; given environment will be released
|
| pEnvDcp |
descriptor of environment
|
| pContext |
context pointer (e.g., to distinguish java vm); set 0 if not needed
|
- uno_dumpEnvironment
- extern "C"
void uno_dumpEnvironment(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Dumps out environment information, i.e. registered interfaces.
- Parameters
| stream |
output stream (FILE *)
|
| pEnv |
environment to be dumped
|
| pFilter |
if not null, filters output
|
- uno_dumpEnvironmentByName
- extern "C"
void uno_dumpEnvironmentByName(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Dumps out environment information, i.e. registered interfaces.
- Parameters
| stream |
output stream (FILE *)
|
| pEnvDcp |
descritpro of environment to be dumped
|
| pFilter |
if not null, filters output
|
- uno_getCurrentEnvironment
- extern "C"
void uno_getCurrentEnvironment(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Description
Returns the current Environment.
In case no Environment has explicitly been entered, a purpose free
default environment gets returned (e.g. the "uno" or "gcc3" Environment).
- Parameters
| ppEnv |
inout parameter; a given environment will be released
|
| pTypeName |
the optional type of the environment, falls back to "uno"
|
- Since
- UDK 3.2.7
- uno_getEnvironment
- extern "C"
void uno_getEnvironment(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Gets a specific environment. If the specified environment does not exist, then a default one
is created and registered. The environment revokes itself on last release() call.
- Parameters
| ppEnv |
inout parameter of environment; given environment will be released
|
| pEnvDcp |
descriptor of environment
|
| pContext |
some context pointer (e.g., to distinguish java vm; set 0 if not needed)
|
- uno_getRegisteredEnvironments
- extern "C"
void uno_getRegisteredEnvironments(
-
| virtual |
abstract |
const |
volatile |
template |
static |
inline |
C-linkage |
| NO |
NO |
NO |
NO |
NO |
NO |
NO |
YES |
- Summary
Gets all specified environments. Caller has to release returned environments and free allocated
memory.
- Parameters
| pppEnvs |
out param; pointer to array of environments
|
| pnLen |
out param; length of array
|
| memAlloc |
function for allocating memory that is passed back
|
| pEnvDcp |
descriptor of environments; 0 defaults to all
|
Top of Page
Copyright © 2012, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


DALI: The MICCAI Workshop on Data Augmentation, Labeling, and Imperfections
With the proliferation of data-intensive methods for supervised learning, the demand for large quantities of annotated data has never been higher. Unfortunately, large-scale collections of medical images are exceptionally challenging to collect and require rare and expensive expertise to annotate. Moreover, medical data are often noisy and imperfect due to missing entries and sensing heterogeneity. A forum for discussing contemporary and practical approaches for dealing with these challenges is urgently needed.
The MICCAI Workshop on Data Augmentation, Labeling, and Imperfections (DALI) aims to provide a venue for researchers to present and discuss their experiences working on these important topics.
Important Dates
- Paper Submission Opens: April 30, 2021
- Paper Submission Deadline:
June 25July 2, 2021 - Notification to Authors:
July 30August 2, 2021 - Camera Ready Deadline:
August 6August 7, 2021 - Workshop Day: Oct. 1, 2021
Call For Papers
Training machine learning systems for image recognition, object detection and image segmentation often requires a huge amount of expert annotated data to reach a high level of accuracy. Having a large number of labeled images helps to increase the performance of machine learning models by generalizing better and thereby reducing overfitting. Most popular benchmark datasets for general image recognition tasks have a few thousand to millions of images.
Obtaining such huge amounts of labeled data is very challenging in the medical imaging domain, however, due to costly annotation by domain experts and lack of high-quality anonymized data out of privacy concerns. Furthermore, there are unique challenges to collecting annotated medical datasets. For instance, examples of rare pathological conditions, although hard to obtain, are extremely important for accurate representation of the data distribution; there are often variations among experts who provide labels, especially for conditions that human experts are most confused about and need help the most.
The goal of this workshop is to bring together and create a discussion forum for researchers in the MICCAI community who are interested in the rigorous study of medical data as it relates to machine learning systems, who are developing and promoting novel techniques in data augmentation, labeing, and learning from small or imperfect data, who would like to contribute benchmark datasets, open challenges and tasks that enable fair comparisons among existing and new techniques, and who are applying such techniques to improving the performance of medical image computing systems. The workshop will have keynote speakers who will speak about popular and emerging approaches for data augmentation or imputation, and learning from small or noisy medical data. The workshop welcomes submissions that present new ideas, new results, new datasets, as well as discussion and evaluation of existing approaches. The topics of interest include but are not limited to:
- Training and evaluation with noisy or uncertain labels
- Data annotation tools and practices
- Synthetic data for medical image analysis
- One-shot/few-shot learning
- Active learning
- Semi-, weakly-, self-supervised learning
- Deep learning for small, noisy and imperfect data
- Domain adaptation/generalization
- Erroneous label detection
- Data augmentation
- Data imputation
- Principles and/or case studies of annotated datasets and benchmarks
- Anonymization, PHI detection
Submissions to our workshop will be managed using the same platform as the main MICCAI conference, using the Microsoft CMT. Tentative conference submission website is at: https://cmt3.research.microsoft.com/DALI2021
Papers submitted to this workshop are limited to 8 pages including references. Papers should be formatted in Lecture Notes in Computer Science style, and should be anonymized in order to allow for double blind review. Authors should consult Springer’s authors’ guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Supplemental material submission is optional, which may include:
- Videos of results that cannot be included in the main paper
- Anonymized related submissions to other conferences and journals
- Appendices or technical reports containing extended proofs and mathematical derivations that are not essential for the understanding of the paper
Contents of the supplemental material should be referred to appropriately in the paper and that reviewers are not obliged to look at it.
Program
Keynote Speakers
- 11:30 UTC: GLPathNet: Exploiting data size and resolution of histopathologic images with a Global-Local Pathology Network, Margrit Betke (Boston University); [Info]
- 12:20 UTC: Constructing Real World AI Applications to Improve Clinical Care: Imaging Cases in Alzheimer’s Drug Discovery, Cancer Screening, and Stroke Detection, Stephen Wong (Houston Methodist); [Info]
- 14:00 UTC: How and why does data augmentation improve generalization?, Ekin Dogus Cubuk (Google Brain); [Info]
- 15:00 UTC: Progress in Disentangling Anatomy and Contrast for MRI Harmonization, Jerry Prince (Johns Hopkins University); [Info]
- 16:00 UTC: Augmentation and Synthesis for Learning Domain Invariances in Medical Image Analysis, Adrian Dalca (Massachusetts Institute of Technology); [Info]
- 17:00 UTC: Respecting the variation among physicians in labeling the clinical data, Steve Jiang (UT Southwestern); [Info]
Full Oral Presentations
- 9:20 UTC: An efficient data strategy for the detection of brain aneurysms from MRA with deep learning, Youssef Assis (University of Lorraine); Liang Liao (CHRU Nancy); Fabien Pierre (University of Lorraine); René Anxionnat (CHRU Nancy); Erwan Kerrien (Inria)
- 9:40 UTC: DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization, Turkay Kart (Imperial College London); Wenjia Bai (Imperial College London); Ben Glocker (Imperial College London); Daniel Rueckert (Imperial College London)
- 11:10 UTC: Zero-Shot Domain Adaptation in CT Segmentation by Filtered Back Projection Augmentation, Talgat Saparov (MIPT); Anvar Kurmukov (Artificial Intelligence Research Institute, Russia, Moscow); Boris Shirokikh (Skoltech); Mikhail Belyaev (Skoltech)
- 14:40 UTC: Medical image segmentation with imperfect 3D bounding boxes, Ekaterina Redekop (Philips); Alexey Chernyavskiy (Philips Innovation Lab RUS)
- 15:40 UTC: Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph, Xiao-Yun Zhou (PAII INC.); Bolin Lai (Ping An Technology (Shanghai) Co.,Ltd.); Weijian Li (University of Rochester); Yirui Wang (PAII Inc.); Kang Zheng (PAII Inc.); Fakai Wang (University of Maryland, College Park); Chihung Lin (CGMH); Le Lu (PAII Inc.); Lingyun Huang (PingAn Technology); Mei Han (PAII Labs); Guotong Xie (Ping An Technology (Shenzhen) Co. Ltd.); Jing Xiao (Ping An Insurance (Group) Company of China); Kuo Chang-Fu (Chang Gung Memorial Hospital); Adam P Harrison (PAII Inc.); Shun Miao (PAII)
- 16:40 UTC: One-shot Learning for Landmarks Detection, Zihao Wang (Inria); Clair Vandersteen (Université Côte d’Azur, Centre Hospitalier Universitaire de Nice); RAFFAELLI CHARLES (Centre Hospitalier Universitaire de Nice); Nicolas Guevara (Université Côte d’Azur, Centre Hospitalier Universitaire de Nice); François Patou (Oticon Medical, Research & Technology group); Herve Delingette (Inria)
Short Oral Presentations
- 10:00 UTC: FS-Net: a new paradigm of data expansion for medical image segmentation, Xutao Guo (Harbin Institute of Technology, Shenzhen); Yanwu Yang (HIT at shenzhen); Ting Ma (Harbin Institute of Technology,Shenzhen)
- 10:10 UTC: Data Augmentation with Variational Autoencoders and Manifold Sampling, Clément Chadebec (Université de Paris); Stéphanie Allassonnière (Université de Paris)
- 10:20 UTC: MetaHistoSeg: A Python Framework for Meta Learning in Histopathology Image Segmentation, Zheng Yuan (Salesforce Research); Andre Esteva (Salesforce Research); Ran Xu (Salesforce Research)
- 10:30 UTC: Label noise in segmentation networks : mitigation must deal with bias, Eugene Vorontsov (Polytechnique Montreal); Samuel Kadoury (Polytechnique Montréal)
- 10:40 UTC: How few annotations are needed for segmentation using a multi-planar U-Net?, William M Laprade (University of Copenhagen); Mathias Perslev (University of Copenhagen); Jon Sporring (University of Copenhagen)
- 10:50 UTC: Evaluation of Active Learning Techniques on Medical Image Classification with Unbalanced Data Distributions, Quok Zong Chong (Imperial College London; Metalynx); William J Knottenbelt (Imperial College London); Kanwal K Bhatia (Metalynx)
- 11:00 UTC: Semi-supervised Surgical Tool Detection Based on Highly Confident Pseudo Labeling and Strong Augmentation Driven Consistency, Wenjing Jiang (Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences); Tong Xia (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences); Zhiqiong Wang (Northeastern University); Fucang Jia (Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences)
- 12:10 UTC: Compound Figure Separation of Biomedical Images with Side Loss, Tianyuan Yao (Vanderbilt University); Chang Qu (Vanderbilt University); Quan Liu (Vanderbilt University); Ruining Deng (Vanderbilt University); Yuanhan Tian (Vanderbilt University); Jiachen Xu (Vanderbilt University); Aadarsh Jha (Vanderbilt University); Shunxing Bao (Vanderbilt University); Mengyang Zhao (Dartmouth College); Agnes fogo (VUMC); Bennett A Landman (Vanderbilt University); Catie Chang (Vanderbilt University); Haichun Yang (Vanderbilt University Medical Center); Yuankai Huo (Vanderbilt University)
- 17:40 UTC: Automated Iterative Label Transfer Improves Segmentation of Noisy Cells in Adaptive Optics Retinal Images, Jianfei Liu (National Eye Institute); Nancy aguilera (National Institutes of Health); Tao Liu (National Institutes of Health); Johnny Tam (National Institutes of Health)
People
Co-Chairs
- Nicholas Heller, University of Minnesota, USA
- Sharon Xiaolei Huang, The Pennsylvania State University, USA
- Hien V. Nguyen, University of Houston, USA
Editorial Chairs
- Raphael Sznitman, University of Bern, Switzerland
- Yuan Xue, Johns Hopkins University, USA
Award Committee
- Dimitris N. Metaxas, Rutgers University, New Brunswick, NJ, USA
- Diana Mateus, Centrale Nantes, France
Advisory Board
- Stephen Wong, Houston Methodist Hospital, Houston, TX, USA
- Jens Rittscher, University of Oxford, Oxford, UK
- Margrit Betke, Boston University, Boston, MA, USA
- Emanuele Trucco, University of Dundee, Scotland
Program Committee
- Alison C Leslie, University of Minnesota
- Amelia Jiménez-Sánchez, Pompeu Fabra University
- Anjali Balagopal, UT Southwestern
- Brett Norling, University of Minnesota
- Chandra Kambhamettu, University of Delaware
- Chao Chen, Stony Brook University
- Christoph M. Friedrich, University of Applied Sciences and Arts Dortmund
- Devante F Delbrune, University of Minnesota
- Edward Kim Drexel, University
- Emanuele Trucco, University of Dundee
- Filipe Condessa, Instituto Superior Tecnico, Portugal / Carnegie Mellon University
- Haomiao Ni, Penn State University
- Hui Qu, Adobe Inc.
- Jiarong Ye, Penn State University
- Jue Jiang, Memorial Sloan Kettering Cancer Center
- Kelvin Wong, Houston Methodist Hospital Research Institute
- Li Xiao, Chinese Academy of Science
- Michael Goetz, German Cancer Research Center DFKZ
- Nicha Dvornek, Yale University
- Niklas E.P. Damberg, University of Minnesota
- Pengyu Yuan, University of Houston
- Pietro Antonio, Cicalese University of Houston
- Rafat Solaiman, University of Minnesota Medical School
- Samira Zare, University of Houston
- Ti Bai, UT Southwestern Medical Center
- Weidong Cai, University of Sydney
- Wen Hui Lei, University of Electronic Science and Technology of China
- Xiao Liang, UT Southwestern
- Xiaoxiao Li, Princeton University
- Xiaoyang Li, Adobe
Sponsor
Prizes for best paper and people’s choice are sponsored by Histosonics.
Previous Editions
DALI is the result of a merger between three proposals submitted to the 2021 MICCAI Conference:


| backlog | key results | |
|---|---|---|
| 1 | first backlog item that is really really reallly loooooong | the first result one two |
| 2 | first backlog item | the first result one two that is also suuuuuper looong..... |
| 3 | first backlog item that is really really reallly loooooong | the first result one two |
| 4 | first backlog item | the first result one two that is also suuuuuper looong..... |
| 5 | first backlog item that is really really reallly loooooong | the first result one two |
| 6 | first backlog item | the first result one two that is also suuuuuper looong..... |
| blockers | |
|---|---|
| 1 | jira |
| 1 | my ancient css skills |
| backlog | key results | |
|---|---|---|
| 1 | first backlog item that is really really reallly loooooong | the first result one two |
| 2 | first backlog item | the first result one two that is also suuuuuper looong..... |
| 3 | first backlog item that is really really reallly loooooong | the first result one two |
| 4 | first backlog item | the first result one two that is also suuuuuper looong..... |
| 5 | first backlog item that is really really reallly loooooong | the first result one two |
| 6 | first backlog item | the first result one two that is also suuuuuper looong..... |