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Using the Microsoft Face API to detect emotions in photos and video
⚠️ IMPORTANT: the Face API container was retired early 2021. The container image is not available anymore. In a previous post, I blogged about detecting emotions with the ONNX FER+ model. As an alternative, you can use cloud models hosted by major cloud providers such as Microsoft, Amazon and Google. Besides those, there are many Read more
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Detecting emotions with FER+
In an earlier post, I discussed classifying images with the ResNet50v2 model. Azure Machine Learning Service was used to create a container image that used the ONNX ResNet50v2 model and the ONNX Runtime for scoring. Continuing on that theme, I created a container image that uses the ONNX FER+ model that can detect emotions in Read more
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ResNet50v2 classification in Go with a local container
To quickly go to the code, go here. Otherwise, keep reading… In a previous blog post, I wrote about classifying images with the ResNet50v2 model from the ONNX Model Zoo. In that post, the container ran on a Kubernetes cluster with GPU nodes. The nodes had an NVIDIA v100 GPU. The actual classification was done Read more
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Recognizing images with Azure Machine Learning and the ONNX ResNet50v2 model
Featured image from: https://medium.com/comet-app/review-of-deep-learning-algorithms-for-object-detection-c1f3d437b852 In a previous post, I discussed the creation of a container image that uses the ResNet50v2 model for image classification. If you want to perform tasks such as localization or segmentation, there are other models that serve that purpose. The image was built with GPU support. Adding GPU support was pretty Read more
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Creating a GPU container image for scoring with Azure Machine Learning
In a previous post, I discussed how you can add an existing Kubernetes cluster to an Azure Machine Learning workspace. Adding an existing cluster is necessary when the workspace does not support auto creation of a cluster. That is the case when you want to use the Standard_NC6s_v3 virtual machine image. I also used a Read more
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Attaching Kubernetes clusters with NVIDIA V100 GPUs to Azure Machine Learning Service
Azure Machine Learning Service allows you to easily deploy compute for training and inference via a machine learning workspace. Although one of the compute types is Kubernetes, the workspace is a bit picky about the node VM sizes. I wanted to use two Standard_NC6s_v3 instances with NVIDIA Tesla V100 GPUs but that was not allowed. Read more
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