Owlv2 Base Patch16
OWLv2 is a vision-language pre-trained model focused on object detection and localization tasks.
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Release Time : 2/9/2024
Model Overview
OWLv2 is an efficient vision-language model capable of detecting and localizing objects in images through text descriptions.
Model Features
Efficient Vision-Language Pre-training
By combining visual and linguistic information, the model can understand complex object descriptions.
Transformer-based Architecture
Leverages the powerful capabilities of Transformers to process visual and linguistic data.
ONNX Format Support
The model has been converted to ONNX format for easy deployment and use on the web.
Model Capabilities
Text-driven object detection
Object localization in images
Multimodal understanding
Use Cases
Computer Vision
Intelligent Image Search
Search for specific objects in images through text descriptions.
Improves search accuracy and efficiency
Automated Annotation
Automatically generate annotations for objects in images.
Reduces manual labeling costs
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