Sold by: Appen (fka Figure Eight)Â
Overview
Classify skin images which potentially contain diseases. This model was trained on acne rosacea, actinic keratosis, bascell cell carcinoma, benign keratosis, eczema, melanoma, nevus, or vascular issues. This model is not intended for medical use or diagnosis.
Highlights
- Classify skin images which potentially contain diseases.
Details
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Delivery method
Latest version
Deployed on AWS
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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
For CPU: We recommend using a ml.c5.xlarge (CPU) instance type. Our tests on these took 2.5 seconds prediction time for average payloads of 225 KB when invoked from a desktop.
Additional details
Inputs
- Summary
Example for the /invocations endpoint:
Input (application/json): Image with peoples faces that needs to be blurred [base64 encoded]
Payload: {"instances": [{"image": {"b64": "BASE_64_ENCODED_IMAGE_CONTENTS"}}]}
Output (application/json): Classification scores for acne rosacea, actinic keratosis, bascell cell carcinoma, benign keratosis, eczema, melanoma, nevus, vascular
Content: {"labels": ["acne_rosacea", … ], "predictions": [ { "label": "bascell_cell_carcinoma", "scores": [0.1, ...]}]}
- Input MIME type
- json
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
If you need any support, have questions, or suggestions, please email ml-support@figure-eight.comÂ
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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