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Image feature extraction and ImageNet category prediction using ResNet50-v1d network, provided by GluonCV
Overview
This model provides intermediate image feature extraction functionality for image classification. It can also provide top-5 category predictions out of 1000 classes on ImageNet.
This network is one of the best models that are both highly efficient and accurate. As a result, it also provides high-quality features for various tasks.
Highlights
- This model can extract high-quality image features efficiently.
- This model can predict top-5 predictions on ImageNet.
- The state-of-the-art performance with accuracy of 79.15 vs. 75.3 in the original paper (https://arxiv.org/abs/1512.03385)
Details
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Delivery method
Latest version
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.c4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.c4.xlarge instance type, real-time mode | $0.00 |
ml.c4.xlarge Inference (Batch) Recommended | Model inference on the ml.c4.xlarge instance type, batch mode | $0.00 |
ml.m4.4xlarge Inference (Real-Time) | Model inference on the ml.m4.4xlarge instance type, real-time mode | $0.00 |
ml.m5.4xlarge Inference (Real-Time) | Model inference on the ml.m5.4xlarge instance type, real-time mode | $0.00 |
ml.m5.12xlarge Inference (Real-Time) | Model inference on the ml.m5.12xlarge instance type, real-time mode | $0.00 |
ml.m4.16xlarge Inference (Real-Time) | Model inference on the ml.m4.16xlarge instance type, real-time mode | $0.00 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $0.00 |
ml.c4.4xlarge Inference (Real-Time) | Model inference on the ml.c4.4xlarge 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.c5.9xlarge Inference (Real-Time) | Model inference on the ml.c5.9xlarge 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
Initial release
Additional details
Inputs
- Summary
Supported content types are image/jpeg, image/png and image/bmp.
AWS APIs can be used to invoke the model after endpoint creation, e.g., using aws-cli:
aws sagemaker-runtime invoke-endpoint --endpoint-name your_endpoint_name --body fileb://img.jpg --accept image/jpeg --custom-attributes '{"feature": "flat"}' feat.out
This command will extract 2048-dim feature prior to fully-connected layer.
Supported layers: ('conv1', 'bn1', 'relu', 'maxpool', 'layer1', 'layer2', 'layer3', 'layer4', 'avgpool', 'flat', 'fc'), if you don't speficy custom-attributes, this model will return top-5 predictions.
- Input MIME type
- image/jpeg, image/png, image/bmp
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
Model supported is available from GluonCV. Search for questions and open new issues to ask questions.
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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