Object Recognition Datasets for AI Training
License image and video datasets from Wavebreak Media's owned archive, or commission capture of specific objects and products. We produce the source media and prepare collections for classification, product identification and visual search.
Featured Datasets
Explore sample licensed datasets across image, video, audio, and text collections.
Object Recognition Data by Task
Select data by what your model must identify or locate. For broader visual tasks, see computer vision datasets.
Object Classification
Images or video frames grouped into your target categories, such as appliances, tools or food items.
Instance and Product Recognition
Multiple views linked to the same physical object or product, using confirmed source relationships or controlled capture.
Object Detection
Objects shown in context, with bounding boxes commissioned where the model must locate each target.
Fine-Grained Recognition
Examples that distinguish similar classes, models or variants through visible attributes and agreed label definitions.
Visual Search
Query and reference images paired with identity or relevance labels for image-based retrieval.
Recognition Evaluation
Test examples for difficult classes and viewing conditions. See model evaluation datasets for dedicated testing projects.
Object Categories and Coverage
Coverage can be assessed for consumer goods, food, household objects, electronics, workplace tools and sports or travel equipment. The Forklift Images Dataset is one industrial-equipment collection.
Choose an existing collection or curate a subset of our image and video datasets. Custom production can fill agreed coverage gaps, subject to sourcing and capture feasibility.
Frequently Asked Questions (FAQ)
Existing files may include descriptions, categories and technical metadata. Class labels, object IDs, bounding boxes, masks and other task-specific annotations are confirmed or commissioned separately, with agreed review criteria.
Exact SKU, variant and branded-packaging coverage is confirmed per project. Archive images alone may not establish product identity. Custom capture may be needed, with agreed access to the products and a verified ID list.
A brief can specify viewpoints, scale, lighting, clutter, partial occlusion and object states. Hard negatives should be defined as examples that resemble a target but fall outside its class. Availability and capture feasibility are checked against those requirements.
Split rules depend on whether the model must recognize known objects or generalize to unseen ones. Define which object identities may appear across splits, and how query and reference sets relate. Related shots, adjacent frames and near-duplicates need separate checks to avoid unintended overlap.
Selected images, clips or extracted frames can be packaged with asset IDs, source relationships, labels and JSON, JSONL or CSV manifests. Media formats, dataset versions and transfer requirements are agreed per project. See dataset delivery and security.
Available provenance and applicable releases can be reviewed for the selected files. Permitted AI uses and restrictions are defined in the agreement. See dataset licensing and compliance.
Request an Object Recognition Dataset
Send your target objects or products, model task, approximate volume and an example of the required image or label. We will assess suitable collections and production options.
