CVAT, Computer Vision Annotation Tool, is an interactive video and image annotation tool, designed to facilitate the annotation of video and image data and accelerate the creation of high-quality datasets for computer vision tasks. CVAT is available on the UCloud platform, in the Application Store.
The webinar will show how to use CVAT on UCloud to:
Label and annotate data with the help of AI and OpenCV tools, including:
Use of cvat-cli
Run built-in model for detection and auto-annotation
Use of GPUS with built in models for faster annotation
Adding custom models (e.g. YOLO)
Efficiently manage large visual datasets with MinIO:
Allow CVAT to directly pull images from your UCloud MinIO buckets for annotation and export annotated data back, reducing manual imports/exports and ensuring data availability.
Using UCloud allows users to create fully reproducible and secure workflows that leverage high performance computing resources. Those features are often necessary for large dataset and accurate computer vision tasks.
Target audience: Researchers across all Departments, particularly who require high-precision data labeling, AI interested.
I denne videovejledning får du en praktisk introduktion til UCloud, den nationale forskningsplatform for beregning, lagring og applikationer. Sessionen er tilrettelagt til at hjælpe nye brugere med at komme i gang med UCloud og forstå, hvordan platformen kan anvendes til forskning, undervisning og projektarbejde. Bemærk, at denne tutorial foregår på engelsk.
I optagelsen guider vi dig gennem, hvordan du:
Logger ind på UCloud og navigerer i dashboardet
Forstår centrale begreber som projekter, ressourcer og applikationer
Kører dit første job og ansøger om yderligere beregnings- og lagerressourcer
Administrerer filer og samarbejder via projektarbejdsområder
Udforsker applikationskataloget og mulighederne for jobafvikling
Bliver introduceret til nye funktioner i UCloud 4.0
Optagelsen er relevant for studerende, forskere og nye UCloud-brugere på tværs af alle fagområder.
UCloud er begyndervenlig og kræver hverken teknisk baggrund eller forudgående erfaring med cloud computing.
Tidsstempler
00:00 – 02:20: Introduktion Hvad UCloud er, hvem platformen er til, og hvad webinaret dækker.
02:20 – 03:50: Centrale begreber, du skal kende Enkle forklaringer af vigtige begreber, der bruges på tværs af platformen.
03:50 – 04:30: Supportressourcer og nyttige links Hvor du finder hjælp på interactivehpc.dk samt yderligere dokumentation.
04:30 – 06:10: Loginproces og overblik over UCloud-dashboardet Sådan logger du ind og navigerer i hoveddashboardet.
06:10 – 08:30: Kør dit første job En hurtig gennemgang af, hvordan du starter en applikation i UCloud.
08:30 – 14:00: Ansøgning om ressourcer Sådan anmoder du om beregnings- og lagerressourcer til dit projekt.
14:00 – 17:20: Filsystem og drev Hvordan fillagring fungerer, og hvordan du håndterer dine data.
17:20 – 18:00: Personligt arbejdsområde vs. projektarbejdsområde De vigtigste forskelle – og hvornår du bør bruge hvad.
18:00 – 21:30: Administration af et UCloud-projekt Medlemmer, indstillinger, tildelinger og samarbejde.
21:30 – 23:50: Ressourcesiden Offentlige links og IP-links, SSH-nøgler og relaterede indstillinger.
23:50 – 25:40: Applikationskatalog og dokumentation Sådan finder du applikationer og får adgang til relevante vejledninger.
25:40 – 28:50: Indstillinger på siden for jobafvikling Konfiguration af applikationer, før et job startes.
28:50 – 29:50: Visning af kørende job Overvågning af jobs og forståelse af jobstatus.
29:50 – 32:00: Arbejdsmappe, outputfiler og siden Runs Hvor du finder resultater, logfiler og jobhistorik.
32:00 – 35:40: Nyt i UCloud 4.0 Kommandopaletten, filtræet, Syncthing og forbrugssiden.
35:40 – 36:08: Afrunding og næste skridt Opsummering og henvisning til yderligere ressourcer.
I denne webinaroptagelse får du en hands-on introduktion til Dictaphone, som er en ny app på UCloud, der gør det muligt for forskere at optage og transskribere interviews direkte fra deres egne enheder – også selvom du arbejder med fortrolige data. Bemærk, at webinaret foregår på engelsk.
I denne video vil vi guide dig igennem, hvordan du:
Optager interviews og samtaler via Dictaphone direkte fra din laptop eller smartphone. Lyden streames i realtid til den sikre UCloud-backend, så data ikke lagres lokalt på din enhed – hvilket gør Dictaphone velegnet til håndtering af fortrolige data.
Transskribere optagelser automatisk i samme arbejdsgang ved hjælp af Dictaphones indbyggede transskriptionsfunktion, så du hurtigt kan omdanne tale til tekst
Får mest muligt ud af Dictaphone, herunder tips, ekstra funktioner og eksempler på anvendelse i forskning.
Optagelsen er relevant for alle forskere på tværs af discipliner og fakulteter – samt studerende.
Dictaphone er begyndervenlig og kræver ingen teknisk baggrund.
Tidsstempler
00:00 – 06:25: Introduktion og kom godt i gang Krav, dataklassifikationer og den grundlæggende arbejdsgang.
06:25 – 32:15: Live demonstration af Dictaphone Hvordan du optager og transskriberer, og hvordan du arbejder på platformen både under og efter optagelsen.
32:15 – 33:50: Datalagring og sikkerhed rdan Dictaphone lagrer data, og hvorfor appen er egnet til håndtering af fortrolige data.
33:50 – 35:30: Relaterede ressourcer og support Andre webinars, relaterede UCloud-apps og kontaktinformation.
35:30 – 43:15: Spørgsmål og svar (Q&A) Spørgsmål fra deltagerne.
43:15 – 44:22: Afrunding og næste skridt Opsummering og henvisning til yderligere ressourcer.
In this video we will guide you through two different AI based workflows, involving ChatUI and CVAT apps.
You will learn how to:
Use advanced CVAT features including auto-annotation, algorithmic assistance, management and analytics.
Use Chat UI as a flexible interface for hosting of various LLM models, and interact via a chat or API environment.
Use ChatUI for semantic search in a knowledge base.
Use CVAT as a powerful annotation tool, including image classification, object detection, semantic and instance segmentation, and video / 3D annotations.
In this video we will guide you through the complete pipeline of transcribing audio files from speech to text and editing and classifying transcription segments.
In this session, you’ll learn how to:
Use Transcriber for transcribing audio/video files. Transcriber is based on Open AI’s Whisper language model. The app can transcribe speech audio to text in various formats and uses the WhisperX package to perform speaker recognition.
Navigate the new, simple, drag and drop Transcriber user interface to make it easier for you to use AI to transcribe audio files.
Edit and classify the transcriptions with Speech Analyzer. Speech Analyzer is an application built on top of Label Studio, specifically optimized for dialogue analysis. It enables you to label, edit, and annotate transcriptions generated using Transcriber.
Perform a comprehensive dialogue analysis on UCloud involving transcribing audio files using Transcriber, followed by transcription analysis with Speech Analyzer.
All workflows will be executed inside a UCloud project environment with access to GPU resources.
Target audience: Researchers across all Departments, particularly Digital Humanities and Social Science, Students, AI interested.
In this video we will guide you through the complete pipeline of fine-tuning large language models (LLMs) for specialised tasks such as medical question-answering using NeMo Framework and Triton Inference Server.
Prepare and preprocess open-source datasets for fine-tuning.
Apply Parameter-Efficient Fine-Tuning (PEFT) using LoRA with NVIDIA NeMo Framework.
Deploy optimised LLMs using NVIDIATriton Inference Server and TensorRT-LLM.
Generate a synthetic Q&A dataset using Label Studio connected to a live inference backend.
Fine-tune and evaluate your customised LLM for domain-specific applications.
All workflows will be executed inside a UCloud project environment with access to GPU resources.
Target audience: Machine learning practitioners, researchers, and engineers interested in LLM customisation, domain adaptation, or scalable model deployment.
In this video we will go through the process of developing a course on UCloud, using UCloud Courses – a tool for hosting and managing university courses on UCloud. Wnt to know more about this new feature, check out our webinar recording introducing UCloud Courses.
Introduction
00:00 – Outline of the workshop agenda 03:10 – Introduction to the UCloud Courses concept 04:23 – Advantages of using UCloud Courses 05:56 – Outline of the steps involved in developing a UCloud Course 09:54 – Requesting and planning a UCloud Course 10:20 – Example of the planning and structuring of an existing UCloud Course
Developing a UCloud Course step by step
Setting up the environment 15:53 – Preliminary remarks 17:15 – Showing the existing UCloud Course that will be re-developed in the workshop 18:02 – Showing the UCloud-Courses GitHub repository 18:40 – Software requirements and -recommendations 20:22 – Short introduction to Git and GitHub 24:27 – Cloning the repository 25:15 – Creating a working branch 26:12 – What should go in the UCloud-Courses repository and what shouldn’t 27:24 – Installing the required dependencies
Creating a new UCloud Course and modifying the templates 28:00 – Creating a UCloud Course using a prepared script 30:31 – Walk-through of the different auto-generated files/folders in the course folder 33:35 – Short introduction to Docker 38:15 – Modifying the Dockerfile 42:32 – What should go in the UCloud-Courses repository and what shouldn’t 45:28 – Building the Docker image locally using a prepared script 47:54 – Modifying the starting script 01:00:50 – What can, shouldn’t, and mustn’t be changed while the course is running
Building and testing the course locally 01:05:00 – Re-building the Docker image locally using a prepared script 01:05:25 – Running a Docker container locally using a prepared script 01:10:58 – Opening the JupyterLab interface on localhost
Finalising the course app 01:12:48 – Opening a pull request and requesting code review 01:19:44 – Testing the course app on UCloud before it’s deployed
Closing remarks
01:25:44 – Reusing/updating an existing UCloud course 01:28:19 – The financial model in brief 01:29:38 – Useful links and resources
I denne video introducerer vi den nye UCloud Courses-app – et værktøj til at hoste og administrere universitetskurser i UCloud.
Dr. Federica Lo Verso guider dig igennem appens koncept og baggrund. Du får en praktisk demonstration af, hvordan du tilgår og bruger værktøjet, udforsker dets integration med GitHub, og hører direkte fra Dr. Himanshu Khandelia, som deler sine erfaringer med at bruge UCloud Courses i virkelige undervisningssituationer.
Vi guider dig også gennem ansøgningsprocessen, viser dig de tekniske og økonomiske krav og giver dig en forsmag på et kommende praktisk kursus.
Tidskoder:
00:00 – Introduktion ved Dr. Federica Lo Verso 01:23 – Baggrund: Lanceringen af den nye UCloud Courses-app 04:12 – Gennemgang: Hvor du finder Courses-appen, og hvordan du bruger den 07:00 – Opsummering af demonstrationen af UCloud Courses-appen 07:56 – Gennemgang: Sådan fungerer GitHub-repositoriet 10:07 – Fordele ved at bruge Courses på UCloud 11:12 – Introduktion til brugsscenarie: Dr. Himanshu Khandelia 11:58 – Dr. Khandelia deler sine erfaringer med at bruge UCloud Courses 14:00 – Live-demo: Dr. Khandelia viser sin brug af Courses og GitHub-integration 23:00 – Sådan ansøger du: Ansøgningsprocessen for UCloud Courses 24:21 – Påkrævede ressourcer til at køre et UCloud-kursus 25:28 – Sådan genbruger og opdaterer du eksisterende UCloud Courses 26:20 – Økonomisk model: Omkostninger og tilgængelig støtte 27:12 – Outro og teaser til det kommende praktiske kursus
00:00 – Introduction and welcome 00:50 – Introduction to UCloud 05:27 – DeiC Interactive HPC website 06:07 – UCloud: Log in 07:06 – UCloud: HPC providers on the UCloud platform 11:08 – UCloud: Initial resource allocations in “My workspace” 12:27 – UCloud: Storage in “My workspace” 13:28 – UCloud: Resources and applications for new resource allocations 13:50 – UCloud: Completing the resource application 21:05 – UCloud: Resource pools and limits (what does it cost?) 23:05 – UCloud: Apps, the app store, applications index in UCloud docs 26:00 – UCloud: Advanced use cases and integration patterns
27:45 – UCloud: Transcriber: Intro and resource needs 30:08 – UCloud: Transcriber: Uploading files inside a project 31:20 – UCloud: Transcriber: Finding and launching Transcriber 32:00 – UCloud: Transcriber: Run Transcriber for the first time (Completing the app launch screen) 34:28 – UCloud: Transcriber: Running multiple Transcriber jobs simultaneously 35:00 – UCloud: Transcriber: Import previous Transcriber job parameters 35:35 – UCloud: Transcriber: Opening running jobs from the “Recent runs” pane 37:15 – UCloud: Transcriber: Transcriber output directories (Jobs folder) 38:26 – UCloud: Transcriber: Transcriber outputs in “Recent runs” 39:54 – UCloud: Transcriber: Output inspection and data download of zip file
41:36 – UCloud: Chat UI: Introduction 43:27 – UCloud: Chat UI: Run Chat UI for the first time (Completing the app launch screen) 48:40 – UCloud: Chat UI: First look at the Chat UI interface (disable new sign-ups and download a model) 52:36 – UCloud: Chat UI: Including documents to support Retrieval Augmented Generation (RAG) (i.e. supplementing the model with an additional document) 57:18 – UCloud: Chat UI: Extend the job time on any UCloud job (if needed) 58:28 – UCloud: Chat UI: Text-to-image generation (stable diffusion with a standard LLM model) 1:01:45 – UCloud: Chat UI: RAG for (best guess) document summarization (beware of model hallucinations)
1:04:45 – UCloud: Label Studio: Introduction 1:05:15 – UCloud: Label Studio: Run Label Studio for the first time (Completing the app launch screen) 1:07:55 – UCloud: Label Studio: First look at the Label Studio interface 1:09:40 – UCloud: Label Studio: Brief view of the Label Studio documentation 1:10:52 – UCloud: Label Studio: Introduction to the coming “Speech Analyser” application 1:15:45 – UCloud: Label Studio: Documentation
