Sold by: NavInfo Europe B.V.
Deployed on AWS
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Detection and blurring of faces and license plates.
4.3
Overview
NavInfo Europe's face and license plate anonymizer detects and blurs recognisable faces and license plates in images. The blurring of faces and license plates helps to reach global privacy standards. The models are trained using images taken from a dashcam. For any specific solution, contact us to create a model to solve your needs
The average precision, average recall and F1-score for License Plates are 98.5, 99.42 and 98.96 respectively when testing on public datasets (CCPD). For faces these are 95.59, 98.05 and 96.80 respectively (IJB-C). Training set that was used was created by Navinfo Europe.
Highlights
- NavInfo Europe Face and License Plate Anonymizer can use a number of different models for detecting license plates and faces. All models that were used are available under MIT license or Apache License. The models were trained using a dedicated training set that was developed by Navinfo Europe. Images in this dataset were created by Navinfo Europe or used under license. Latency metrics: measured on g4dn.xl : 41fps measured on g4dn.12xl : 77fps
- The models and the training data for this pipeline can be used commercially.
- Navinfo Europe has created these models using more than 5 years of experience in the area of machine learning and AI.
Details
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor.
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.p3.2xlarge Inference (Batch) Recommended | Model inference on the ml.p3.2xlarge instance type, batch mode | $0.50 |
ml.g4dn.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $0.50 |
ml.p2.xlarge Inference (Batch) | Model inference on the ml.p2.xlarge instance type, batch mode | $0.50 |
ml.p3.8xlarge Inference (Batch) | Model inference on the ml.p3.8xlarge instance type, batch mode | $0.50 |
ml.p2.8xlarge Inference (Batch) | Model inference on the ml.p2.8xlarge instance type, batch mode | $0.50 |
ml.p2.16xlarge Inference (Batch) | Model inference on the ml.p2.16xlarge instance type, batch mode | $0.50 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $0.50 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $0.50 |
ml.g4dn.4xlarge Inference (Real-Time) | Model inference on the ml.g4dn.4xlarge instance type, real-time mode | $0.50 |
ml.m5.4xlarge Inference (Real-Time) | Model inference on the ml.m5.4xlarge instance type, real-time mode | $0.50 |
Dimensions summary
You pay by the hour for the compute instance that runs the anonymization model, which blurs faces and license plates in visual data. Pricing splits into two modes. Batch inference processes stored datasets on six GPU instance types. Real-time inference handles live requests across fourteen instance types, including GPU, general-purpose, and burstable options. Within each mode, cost scales with the size and power of the chosen instance. You select the mode and instance that fit your workload, and charges accrue only for the hours each instance runs.
Top-of-mind questions for buyers
Batch mode processes stored datasets, so you run instances only while jobs execute. Real-time mode keeps an instance running to handle live requests as they arrive. Batch fits recurring dataset processing. Real-time fits on-demand blurring where results are needed within minutes. Both bill per host-hour.
One host-hour is one hour that a single chosen instance runs the anonymization model. Charges accrue for every hour the instance stays running, whether or not it actively processes data. Stop the instance to end software charges. Underlying AWS resource fees may still apply separately.
Each instance type offers different compute power and memory. GPU instances handle heavier vision workloads faster, while general-purpose and burstable types suit lighter loads. Your hourly rate reflects the size and capability of the instance you select. Larger, more powerful instances carry higher hourly rates.
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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
This solution is based on the Nanodet and HardNet68 models which have been improved by Navinfo Europe B.V. Other variations also exist (Yolo, SSD, …) and are available on request.
Additional details
Inputs
- Summary
Upload the images you want to anonymize by blurring, we support the most common formats.
- Limitations for input type
- Each image should not exceed 5 MB. Maximum image resolution: 4096 x 2048.
- Input MIME type
- image/jpeg, image/png, image/x-ms-bmp, image/x-portable-pixmap, image/x-portable-anymap, image/tiff, image/jp2
https://github.com/Navinfo-Europe/anonymizer/tree/main/data/input/new
https://github.com/Navinfo-Europe/anonymizer/tree/main/data/input/new
Resources
Vendor resources
Support
Vendor support
Navinfo Europe provides support upon request by the customer. Please contact our support engineers or sales representatives using the following e-mail address: awssupport@navinfo.eu
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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This model blurs the faces of people in an image to preserve privacy
Customer reviews
Ritik R.
Anonymizer helps in Maintaining Privacy
Reviewed on Jun 01, 2023
Review provided by G2
What do you like best about the product?
Anonymizer helps to maintain the privacy of the people in the videos I use.
What do you dislike about the product?
It's a little slow for me sometimes, but overall it's good.
What problems is the product solving and how is that benefiting you?
It is helping me creating videos with exploiting anyone's data.
Nadeem P.
Face and License plate anonymizer review
Reviewed on Apr 06, 2023
Review provided by G2
What do you like best about the product?
The best thing about Face and License plate Anonymizer is data privacy.
What do you dislike about the product?
I didn't find personally any fact that makes Face and License plate anonymizer to dislike.
What problems is the product solving and how is that benefiting you?
For building a multi model.