
Overview
This is an Object Detection model from PyTorch Hub . It takes an image as input and returns bounding boxes for the objects in the image. The model is pre-trained on COCO 2017 which comprises images with multiple objects and the task is to identify the objects and their positions in the image. A list of the objects that the model can identify is given at the end of the page. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.
Highlights
- This is an Object Detection model from PyTorch Hub: https://pytorch.org/hub/nvidia_deeplearningexamples_ssd/
Details
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Pricing
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g4dn.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $0.00 |
ml.p2.xlarge Inference (Batch) Recommended | Model inference on the ml.p2.xlarge instance type, batch mode | $0.00 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $0.00 |
ml.p3.2xlarge Inference (Real-Time) | Model inference on the ml.p3.2xlarge instance type, real-time mode | $0.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $0.00 |
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Version release notes
This GPU version supports model run on GPU instance types
Additional details
Inputs
- Summary
The input is an image.
- Input MIME type
- application/x-image
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