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Identify rooftop solar panels from satellite imagery using Amazon Rekognition Custom Labels

AWS Machine Learning

The following code is an example of one image labeling output in the manifest file: { "source-ref": "s3:// /blog-images/source-image/03-09-2021/source-image-001.png", The following code is an example of one image labeling output in the manifest file: { "source-ref": "s3:// /blog-images/source-image/03-09-2021/source-image-001.png",

APIs 71
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Image augmentation pipeline for Amazon Lookout for Vision

AWS Machine Learning

png') noise=iaa.AdditiveGaussianNoise(10,40) input_noise=noise.augment_image(input_img) contrast=iaa.GammaContrast((0.5, png","s10-label-ref":"s3://pcbtest22/label/s10-label/annotations/consolidated-annotation/output/0_2022-09-08T18:01:51.334016.png","s10-label-ref-metadata":{"internal-color-map":{"0":{"class-name":"BACKGROUND","hex-color":"#ffffff","confidence":0},"1":{"class-name":"IC","hex-color":"#2ca02c","confidence":0},"2":{"class-name":"resistor_1","hex-color":"#1f77b

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Using Amazon SageMaker with Point Clouds: Part 1- Ground Truth for 3D labeling

AWS Machine Learning

png │ │ │ ├── 20180807145028_lidar_frontcenter_000000091.json png │ │ │ ├── 20180807145028_lidar_frontcenter_000000380.json png │ │ │ ├── 20180807145028_lidar_frontcenter_000000380.png png │ │ │ ├──. │ ├── label3D │ │ ├── cam_front_center │ │ │ ├── 20180807145028_lidar_frontcenter_000000091.json npz │ │ │ ├──.