Sold by: Ambarella-Model Preparation
Deployed on AWS
Ambarella's Optimized YOLOv5 for Object Detection
Overview
Ambarella’s Model Garden is a collection of models tuned for Ambarella's chipsets for ease of deployment. Users can select the domain and choose from one of the offered models based on their real world application.
Every model undergoes transfer learning to adapt to user's dataset and then is further optimized using Ambarella's proprietary model compression toolkit to enhance the performance on Ambarella's devices. Users are provided with optimization knobs that influence the trained model's accuracy and performance. Finally, the CVflow SDK compiles the trained model, generating an artifacts tar file containing compiled binaries that can be used to run on the device without any extra code.
Highlights
- The goal is to allow users to bring in their own dataset and train using Ambarella's proprietary backbone or standard backbones to get the best model in terms of accuracy and throughput to deploy on Ambarella's AI SoCs.
Details
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Deployed on AWS
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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
Update in tool license.
Additional details
Inputs
- Summary
Model input format is image/jpg
https://github.com/Ambarella-Inc/amba-mps/blob/2b59ec057595f10751bb2add97680c6843f72025/images/000005.jpg
https://github.com/Ambarella-Inc/amba-mps/blob/2b59ec057595f10751bb2add97680c6843f72025/images/000005.jpg
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