Sold by: CopernicAIÂ
Overview
Classifies the whole scene of a 360 image within 365 classes. Additionally, it provides center-of-attention maps for each class and measures the likelihood that attributes (natural, open-space, vegetation, etc..) are represented within a scene. Finallty, it decides whether a scene is indoors or outdoors.
Highlights
- Scene classification for 360 images.
- Attributes for 350 images.
- Center of attention maps for each scene category
Details
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $0.00 |
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $0.00 |
ml.m6g.xlarge Inference (Real-Time) | Model inference on the ml.m6g.xlarge instance type, real-time mode | $0.00 |
ml.m6g.large Inference (Real-Time) | Model inference on the ml.m6g.large instance type, real-time mode | $0.00 |
ml.g5.xlarge Inference (Real-Time) | Model inference on the ml.g5.xlarge instance type, real-time mode | $0.00 |
ml.c5.large Inference (Real-Time) | Model inference on the ml.c5.large instance type, real-time mode | $0.00 |
ml.m5.xlarge Inference (Real-Time) | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.00 |
ml.m6gd.large Inference (Real-Time) | Model inference on the ml.m6gd.large instance type, real-time mode | $0.00 |
ml.m4.xlarge Inference (Real-Time) | Model inference on the ml.m4.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 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Scene classification. Presence or absence of attributes in scene. Center of attention maps.
Additional details
Inputs
- Summary
JPEG image
- Limitations for input type
- Images are best provided with a size of 1024 by 512 pixels. Images are resized before being submitted to the model.
- Input MIME type
- application/x-image
https://gitlab.com/kagenova/copernicai/aws-marketplace-tutorial/-/tree/main/assets/bedroom.jpg
https://gitlab.com/kagenova/copernicai/aws-marketplace-tutorial/-/tree/main/assets/
Resources
Vendor resources
Support
AWS infrastructure support
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