Topic 1 Question 148
You work for a shipping company that has distribution centers where packages move on delivery lines to route them properly. The company wants to add cameras to the delivery lines to detect and track any visual damage to the packages in transit. You need to create a way to automate the detection of damaged packages and flag them for human review in real time while the packages are in transit. Which solution should you choose?
Use BigQuery machine learning to be able to train the model at scale, so you can analyze the packages in batches.
Train an AutoML model on your corpus of images, and build an API around that model to integrate with the package tracking applications.
Use the Cloud Vision API to detect for damage, and raise an alert through Cloud Functions. Integrate the package tracking applications with this function.
Use TensorFlow to create a model that is trained on your corpus of images. Create a Python notebook in Cloud Datalab that uses this model so you can analyze for damaged packages.
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Should be B.
👍 32[Removed]2020/03/21AutoML is used to train model and do damage detection Auto Vision is used is a pre trained model used to detect objects in images
👍 21[Removed]2020/03/25Answer is B. Cloud Vision API detects lot of things for not damages. The description of Damages can be different for each business . So we need to train the model with test and training data to give our definition of Damages, so we need ML capabilities so answer is B, AutoML.
👍 8nehaxlpb2020/09/13
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