From the course: Hands-On AI: Computer Vision Projects with Ultralytics and OpenCV
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How to use the pose estimation model - OpenCV Tutorial
From the course: Hands-On AI: Computer Vision Projects with Ultralytics and OpenCV
How to use the pose estimation model
- [Instructor] In this video, we will cover how to use the pose estimation model with analytics python package. Pose estimation is a computer V algorithm that involves identifying the location of specific points in an image, usually referred to as key points. Let's say we want to use the key points model on human body. We can use it to detect different key points on human body. For example, hands, nose, legs, elbows, and lot of additional key points. Normally when we use the key points model for human, it provide us 17 different key points on human body. All the resources used in this video are available in the course code subdirectory 0305. Let's go to docs.ultralytics.com/tasks/pose and let's explore how we can use the key points model with analytics Python package. Here we can see different key points that we can detect on human body. For example, nose, left ear, right ear, left shoulder, and so on. Then we also have different models that we can use for pose submission. For…
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Contents
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Overview of Ultralytics tasks and modes14m 52s
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Training an object-detection model and inference16m 54s
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Auto-annotate detection data to segmentation format9m 10s
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Training and inference for an image-segmentation model11m 31s
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How to use the pose estimation model7m 48s
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Validate the model9m 16s
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How to use other computer vision models11m 20s
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How to predict and track the detected objects11m 13s
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How to benchmarks different models9m 28s
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Export models to different formats8m 35s
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