Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
AI DashCam Accident Video Summary
By:
Latest Version:
1.0
AI-powered system condenses DashCam footage into brief videos for streamlined accident insurance claims processing.
Product Overview
Accident Video Summarization AI streamlines insurance claim processing by condensing dash cam footage into concise videos. This AI-powered tool analyzes long recordings, extracting crucial moments and highlighting key events. By automating the summarization process, it improves accuracy and expedites claims handling. The system offers a side-by-side comparison of original and summarized videos, showcasing its effectiveness and facilitating swift decision-making for insurance claims. This innovative solution significantly reduces review time, enabling organizations to efficiently assess incidents and process claims more quickly.
Key Data
Version
By
Type
Algorithm
Highlights
Accident Video Summarization AI enhances insurance claim processing by creating concise videos from lengthy dash cam footage. It uses AI to pinpoint crucial moments, cutting review time significantly. This boosts efficiency and accuracy in claims handling, with comparative studies showing the system's effectiveness in facilitating swift decision-making.
This system considers accident severity and context, capturing essential details in condensed videos. It analyzes patterns and key events to handle various accident scenarios. By extracting crucial moments, it enables insurance agents to swiftly evaluate summarized content, boosting overall workflow efficiency.
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Algorithm Training$10/hr
running on ml.g5.8xlarge
Model Realtime Inference$5.00/hr
running on ml.p3.8xlarge
Model Batch Transform$5.00/hr
running on ml.p3.8xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Algorithm Training$3.06/host/hr
running on ml.g5.8xlarge
SageMaker Realtime Inference$14.688/host/hr
running on ml.p3.8xlarge
SageMaker Batch Transform$14.688/host/hr
running on ml.p3.8xlarge
Algorithm Training
For algorithm training in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Algorithm/hr | |
|---|---|---|
ml.g4dn.4xlarge | $10.00 | |
ml.m5.4xlarge | $10.00 | |
ml.m5.2xlarge | $10.00 | |
ml.p3.16xlarge | $10.00 | |
ml.g5.12xlarge | $10.00 | |
ml.g4dn.2xlarge | $10.00 | |
ml.m4.2xlarge | $10.00 | |
ml.r5.12xlarge | $10.00 | |
ml.r5d.12xlarge | $10.00 | |
ml.r5.xlarge | $10.00 | |
ml.r5d.xlarge | $10.00 | |
ml.p3.2xlarge | $10.00 | |
ml.g4dn.12xlarge | $10.00 | |
ml.m5.24xlarge | $10.00 | |
ml.g4dn.xlarge | $10.00 | |
ml.c6i.16xlarge | $10.00 | |
ml.r5d.24xlarge | $10.00 | |
ml.g5.48xlarge | $10.00 | |
ml.r5d.8xlarge | $10.00 | |
ml.p2.xlarge | $10.00 | |
ml.m5.12xlarge | $10.00 | |
ml.p2.16xlarge | $10.00 | |
ml.g5.8xlarge Vendor Recommended | $10.00 | |
ml.r5.16xlarge | $10.00 | |
ml.r5d.16xlarge | $10.00 | |
ml.g5.16xlarge | $10.00 | |
ml.m4.xlarge | $10.00 | |
ml.p3.8xlarge | $10.00 | |
ml.c6i.32xlarge | $10.00 | |
ml.p2.8xlarge | $10.00 | |
ml.g4dn.8xlarge | $10.00 | |
ml.g5.2xlarge | $10.00 | |
ml.r5.2xlarge | $10.00 | |
ml.g5.24xlarge | $10.00 |
Usage Information
Training
To prepare training data: You need to create a compressed file named input_zip.zip.Inside input_zip.zip, you need to have a single folder named input_zip. This folder will contain two items:
- A CSV file: This file should be named video_labels.csv.It should contain "Video Name", "Start Key Frame Index":This column specifies the frame number where a key event starts in the video. and "End Key Frame Index": This column specifies the frame number where a key event ends in the video.
- A directory named "videos": This directory will contain all the video files that need to be summarized.
Channel specification
Fields marked with * are required
training
*Input modes: File
Content types: application/zip, application/gzip
Compression types: None
Model input and output details
Input
Summary
Inference: To use the trained model for summarizing videos: * Create a ZIP archive: You need to create a compressed file named Inference_Videos.zip. * Content of the ZIP archive: This ZIP archive should only contain the video files that you want the trained model to summarize. There's no need for any folders or additional files within the ZIP.
Limitations for input type
Inference:
The ZIP archive must be named Inference_Videos.zip.
The ZIP archive should only contain video files. No folders or other files are needed.
Input MIME type
application/zip, application/gzipSample input data
Output
Summary
output folder will contain the summarized videos.
Output MIME type
text/plain, application/gzip, application/zipSample output data
Sample notebook
Additional Resources
End User License Agreement
By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)
Support Information
AI DashCam Accident Video Summary
For any assistance reach out to us at:
AWS Infrastructure
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