Robotics
Capture task sequences in the environments where they occur.
Organize manipulation, navigation, handoff, tool-use, and human–object interactions by task stage, viewpoint, setting, and visible conditions.
Dados baseados em cenários para sistemas incorporados
Dados de vídeo VLA para IA física
Receba clipes organizados por ações, ambientes, pontos de vista e tempo para IA física. Defina seu cenário e analise clipes de amostra com seus metadados.
A carga de trabalho
Comece com o comportamento físico que o modelo deve observar.
Os dados VLA tornam-se úteis quando a ação e sua configuração são explícitas. Escolha a carga de trabalho primeiro, e depois defina quais variações de cena pertencem à coleção.
Autonomous mobility
Build scenario coverage around road-user behavior and changing conditions.
Define maneuvers, intersections, road types, traffic states, weather, lighting, camera perspective, and the event window that makes the scene relevant.
World models
Preserve the sequence between state, action, and visible outcome.
Collect temporally coherent clips that retain environment, actor, object, action, and outcome context for simulation and representation-learning workflows.
Breve cenário
Transforma uma necessidade modelo em critérios de cena pesquisáveis.
O resumo define o que deve acontecer na tela e quais variações importam. target.
Build your scenario brief- 01Action
The behavior, task stage, or interaction that must be visible.
- 02Actor and object
The people, vehicles, tools, surfaces, or items involved in the event.
- 03Environment
The physical setting, layout, road type, workspace, or background context.
- 04Conditions
Lighting, weather, congestion, occlusion, motion, and other useful variation.
- 05Point of view
Egocentric, fixed, mobile, elevated, roadside, or another defined perspective.
- 06Time boundaries
The visible cue that starts the clip and the outcome that closes it.
Campos do registro
Mantenha cada clip conectado ao contexto que o selecionou.
Um envelope de registro consistente permite que as equipes de dados inspecionem a adequação de cenas, juntem arquivos a metadados e comparem lotes sem reconstruir o contexto a partir de nomes de arquivos.
Focused video clip
Defined start and end around the visible action, with file properties kept beside the record.
- Clip identifier
- File reference
- Duration and orientation
Scenario meaning
The behavior, actor, object, task stage, and visible outcome represented in the selected window.
- Action sequence
- Actors and objects
- Start and completion cues
Scene conditions
Environment, point of view, lighting, weather, traffic, occlusion, and other selected dimensions.
- Environment class
- Viewpoint
- Condition values
Delivery metadata
Source reference, collection context, schema version, batch identity, and record-quality state.
- Source reference
- Batch and schema version
- Acceptance state
Fluxo de trabalho operacional
Um breve rege a descoberta, a corte, a qualidade e a entrega.
A WebScrapingAPI trata do fluxo de trabalho de recolha. A sua equipa mantém-se focada na definição do cenário e em saber se os registos de amostra se adequam ao fluxo de trabalho do modelo pretendido.
- 01DefineShared brief
Translate the workload into actions, environments, conditions, viewpoints, time boundaries, exclusions, and sample criteria.
- 02DiscoverWSA operates
Search the selected source universe for scenes that fit the approved context and event pattern.
- 03PrepareWSA operates
Set clip windows, assemble metadata, apply duplicate controls, and test records against the acceptance rules.
- 04DeliverWSA operates
Package accepted files and manifests, report batch quality states, and send them to the selected destination.
WebScrapingAPI ownsCollection, clip preparation, quality monitoring, source-change maintenance, and delivery.
Your team ownsModel objectives, scenario approval, sample acceptance, and downstream training or evaluation.
Design de qualidade
Qualidade significa que o clipe se encaixa no cenário e o registro explica o porquê.
As regras de aceitação são anexadas ao brief antes que o volume se expanda. Cada estado entregue permanece visível, para que a equipe de recepção possa separar registros aceitos de estados de revisão ou rejeição.
Scenario fit
ContextThe required action, actor, object, environment, and selected conditions are visible in the clip.
Time-boundary fit
SequenceThe event begins and ends at the defined cues, with enough surrounding context to interpret the sequence.
Media integrity
FileThe delivered file can be opened, identified, and connected to its record and manifest.
Metadata completeness
RecordRequired context fields, source reference, batch identity, and schema version are present and readable.
Duplicate control
BatchRepeated files and near-identical scene records follow the program’s defined handling policy.
Design de entrega
Receber um lote inspecionável uma vez ou manter o fornecimento do cenário ativo.
Escolha uma coleção única para um marco modelo definido ou um programa recorrente que adicione novos registros em uma cadência planejada.
Build a bounded scenario collection.
Use a fixed source scope, collection window, record schema, acceptance policy, and delivery event for training or evaluation.
- Versioned clip files
- Record index and manifest
- Batch quality summary
Refresh the scenario set on a planned cadence.
Retain the record contract while adding new files, condition coverage, or time periods to the selected secure destination.
- Consistent schema
- Duplicate and version policy
- Delivery-by-delivery states
Delivery envelope
- Media
- Video clips
- Index
- Structured metadata
- Control
- Manifest + schema version
- Destination
- Selected secure destination
Escolha o caminho certo
Use o caminho VLA quando o contexto físico define se um clip pertence.
O conjunto de dados mais amplo da IA oferece às equipes rotas claras para vídeo geral, pacotes prontos para avaliação, coleta gerenciada e planejamento de registros multimodal.
CaminhoMelhor ajusteObjeto de definiçãoPróximo passo
Need a broader training, RAG, or agent data route? Explore Data for AI.
Orientação dos preços
Preça o programa de cenários, não uma contagem de mídia abstrata.
O escopo segue o trabalho necessário para encontrar, preparar, verificar, organizar e entregar registros úteis para a carga de trabalho definida da IA física.
Discuss your VLA data brief- Scenario breadth
- Actions, environments, conditions, viewpoints, and exclusions
- Media work
- Source scope, collection window, clip preparation, and file organization
- Record depth
- Metadata fields, schema, manifests, and quality states
- Delivery options
- Volume, one-time or recurring cadence, destination, and support
FAQ
Perguntas para avaliação de dados de vídeo VLA.
Use as respostas para moldar um cenário breve, revisão de amostras, design de entrega e limites operacionais.
Talk to a data expertWhat is VLA video data?
VLA video data organizes visible actions and their surrounding scene context for vision-language-action and physical-AI workloads. A delivery can pair focused clips with point of view, environment, conditions, time boundaries, and descriptive metadata.
How do we define the right physical-AI scenarios?
Start with the action the model must observe, then define the actor or object, environment, operating conditions, point of view, clip start and end, and useful exclusions. WebScrapingAPI turns that brief into discovery and acceptance criteria.
What can each delivered record contain?
A record can connect the video clip to its source reference, action and scene description, point of view, environment, conditions, time boundaries, file properties, capture context, and schema version. The selected fields follow the program brief.
Can delivery be one-time or recurring?
Yes. A one-time delivery can support a defined training or evaluation window. A recurring program can add new scenario-matched records on a planned cadence while retaining the same record structure and acceptance rules.
What does WebScrapingAPI operate?
WebScrapingAPI operates source discovery and collection, clip preparation, metadata assembly, quality monitoring, source-change maintenance, duplicate controls, and delivery to the selected secure destination.
How is this different from general Video Data for AI Training?
The broader Video Data service supports multimodal model workloads across video, audio, transcripts, clips, and metadata. The VLA path adds a physical-scenario brief that makes action, environment, conditions, point of view, and time boundaries central to every record.
How is VLA video data delivered?
Video clips and their record index can be organized into versioned batches and sent to the selected secure destination. The delivery design covers file organization, manifest structure, schema version, cadence, and acceptance reporting.
What shapes pricing?
Pricing reflects scenario breadth, source scope, collection window, clip preparation, metadata depth, quality rules, volume, cadence, duplicate policy, file organization, delivery destination, and the operating support required.
O teu primeiro cenário
Transformar um cenário de IA física em um resumo de dados prontos para amostras.
Compartilhe a ação, o ambiente, as condições, o ponto de vista, os limites temporais e o destino preferido.