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Owlvit Base Patch32

alaradirik

🐍

The owlvit-base-patch32 model is a zero-shot / open vocabulary object detection tool. By inputting an image URL and a query listing of items to identify, the model outputs the coordinates of the queried items within the image, along with the confidence level of each identification. The model can also provide a visualisation of the identified objects within the image, overlaying bounding boxes around the detected objects. The model accomplishes this without being previously trained on the specific objects, operating on a zero-shot detection basis.

Use cases

The AI model, owlvit-base-patch32, is designed for zero-shot or open vocabulary object detection, an advanced image-to-text translation tool that could prove to be revolutionary in multiple fields. One of the key use cases is in the realm of surveillance and security, wherein it could be used to interpret surveillance images and thereby facilitate seamless object detection in real-time, potentially improving response times. This model could also be utilized in the field of healthcare, more specifically in diagnostics, where it can be used to identify and label anomalies in medical images such as MRI scans, X-rays, and CT scans, making diagnosis processes more efficient. Additional use cases could be in the e-commerce sector where this model could be deployed to automatically describe product images, thus improving online shopping experiences for visually impaired customers. It might facilitate the automated tagging and categorization of a large number of product images, improving search efficiency. In terms of products, this model could be integrated into surveillance software systems, healthcare diagnostic tools, and mobile apps or web platforms for e-commerce. It could also be used to create smart cameras for wildlife monitoring that can identify and label various animal species. Even in recreational activities, like bird-watching or stargazing, it could assist users in identifying different species or celestial bodies.

Pricing

Cost per run
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Avg run time
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Prediction

Creator Models

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Lightweight Openpose$?1,442
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Overview

Summary of this model and related resources.

PropertyValue
Creatoralaradirik
Model NameOwlvit Base Patch32
Description
Zero-shot / open vocabulary object detection
Tags
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv

Popularity

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PropertyValue
Runs8,400
Model Rank
Creator Rank

Cost

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PropertyValue
Cost per Run$-
Prediction Hardware-
Average Completion Time-