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Answer: Use the Vertex AI Vision Occupancy Analytics model.
The correct answer is A. The Vertex AI Vision Occupancy Analytics model is a pre-built and optimized solution specifically designed for counting people in live video streams. This model is ideal for this scenario as it requires minimal configuration and can be deployed quickly. It is tailored for occupancy analysis, which aligns perfectly with the task of detecting the number of customers waiting for service in near real time. Options B, C, and D would require additional data processing, annotation, and training, thereby increasing effort and implementation time.
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You work for a company that captures live video footage of checkout areas in their retail stores to monitor customer activity. The goal is to build a machine learning model to detect the number of customers waiting for service in near real time using this live video footage. Given the need for a quick solution with minimal effort, what approach should you take to build the model?
A
Use the Vertex AI Vision Occupancy Analytics model.
B
Use the Vertex AI Vision Person/vehicle detector model.
C
Train an AutoML object detection model on an annotated dataset by using Vertex AutoML.
D
Train a Seq2Seq+ object detection model on an annotated dataset by using Vertex AutoML.