Sold by: RocketML
Deployed on AWS
Singular Value Decomposition on a batch of videos
Overview
Video Embeddings using Singular Value Decomposition (SVD) can be used for semantic search, dimentioanlity reduction, and anomaly detection. Give a batch of videos singular values and vectors are computed using these algorithms.
Highlights
- Frames are automatically extracted, resized, reshaped to 1D to create data matrix before performing SVD
Details
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Deployed on AWS
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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.c5.2xlarge Inference (Batch) Recommended | Model inference on the ml.c5.2xlarge instance type, batch mode | $5.00 |
ml.c5.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.c5.2xlarge instance type, real-time mode | $5.00 |
ml.c5.2xlarge Training Recommended | Algorithm training on the ml.c5.2xlarge instance type | $5.00 |
ml.c5.18xlarge Inference (Batch) | Model inference on the ml.c5.18xlarge instance type, batch mode | $5.00 |
ml.c5.xlarge Inference (Batch) | Model inference on the ml.c5.xlarge instance type, batch mode | $5.00 |
ml.c5.9xlarge Inference (Batch) | Model inference on the ml.c5.9xlarge instance type, batch mode | $5.00 |
ml.c5.4xlarge Inference (Batch) | Model inference on the ml.c5.4xlarge instance type, batch mode | $5.00 |
ml.c5.18xlarge Inference (Real-Time) | Model inference on the ml.c5.18xlarge instance type, real-time mode | $5.00 |
ml.c5.xlarge Inference (Real-Time) | Model inference on the ml.c5.xlarge instance type, real-time mode | $5.00 |
ml.c5.9xlarge Inference (Real-Time) | Model inference on the ml.c5.9xlarge instance type, real-time mode | $5.00 |
Dimensions summary
You pay by the hour based on three activities and the compute instance you pick. Training builds the model, while inference generates video embeddings in either batch mode or real-time mode. For each activity, you choose one of five ml.c5 instance sizes, from ml.c5.xlarge up to ml.c5.18xlarge. Larger instance types carry more compute capacity and bill at higher hourly rates. All fifteen dimensions charge per host hour (HostHrs), so your total cost depends on instance size and how many hours you run each task.
Top-of-mind questions for buyers
One HostHrs is one hour that a single ml.c5 instance runs your task. Billing counts each hour the instance is active for training or inference. If you run multiple instances, each one accrues its own host hours. Your bill reflects instance size multiplied by hours run.
Both meter per host hour on the same ml.c5 instance types. Batch mode processes a group of videos together, so instances run only while the batch job executes. Real-time mode keeps an instance running to serve requests on demand, so hours accrue for as long as the endpoint stays active.
Yes. Training builds the model and bills per host hour on your chosen instance. Inference generating embeddings bills separately on its own host hours. The two activities meter independently, so a complete project combines training hours plus batch or real-time inference hours on the instance sizes you pick for each.
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Delivery details
Amazon SageMaker algorithm
An Amazon SageMaker algorithm is a machine learning model that requires your training data to make predictions. Use the included training algorithm to generate your unique model artifact. Then deploy the 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
Singular Value Decomposition on Videos
Additional details
Inputs
- Summary
See example notebook for example usage.
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
RocketML offers free support with email response as well as one-on-one office hours with our experienced solution architects. The service helps customers of all sizes and technical abilities to make best use of RocketML products and features. Subscribers and prospecting customers can contact us at the URL below or email support@rocketml.net <www.rocketml.net >
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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