Topic 1 Question 239
You work for a pet food company that manages an online forum. Customers upload photos of their pets on the forum to share with others. About 20 photos are uploaded daily. You want to automatically and in near real time detect whether each uploaded photo has an animal. You want to prioritize time and minimize cost of your application development and deployment. What should you do?
Send user-submitted images to the Cloud Vision API. Use object localization to identify all objects in the image and compare the results against a list of animals.
Download an object detection model from TensorFlow Hub. Deploy the model to a Vertex AI endpoint. Send new user-submitted images to the model endpoint to classify whether each photo has an animal.
Manually label previously submitted images with bounding boxes around any animals. Build an AutoML object detection model by using Vertex AI. Deploy the model to a Vertex AI endpoint Send new user-submitted images to your model endpoint to detect whether each photo has an animal.
Manually label previously submitted images as having animals or not. Create an image dataset on Vertex AI. Train a classification model by using Vertex AutoML to distinguish the two classes. Deploy the model to a Vertex AI endpoint. Send new user-submitted images to your model endpoint to classify whether each photo has an animal.
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コメント(6)
- 正解だと思う選択肢: A
A. B would also work and I wonder if cost would be lower, but I think going with the google hosted service is most times the most likely choice to be correct.
👍 10b1a8fae2024/01/18 - 正解だと思う選択肢: A
As minimising time and cost are of priority and considering the small subset of images I believe A is the best option
👍 4shadz102024/01/16 - 正解だと思う選択肢: B
I went Option B
👍 2CHARLIE21082024/02/07
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