I have project requirement to build object detection model using my organization’s dataset for manufacturing defects. I found Roboflow is suitable. I trained , deployed custom dataset and tried inference. I have following questions to proceed further:
Our company image data is stored in S3 , how to train using S3?
How to do MLOPS in Roboflow, for example automatic retraining of new data and deployment?
I want to setup monitoring dashboard to see how many request hit the endpoint URL, model accuracy, data drift if any. How to setup model monitoring dashboard
I want email trigger, if model performance slow or time out, how to setup email alert?
Glad you’re finding good opportunity with the tooling. Some thoughts for your questions:
You can upload and sync data from S3 a few ways, and the best way may depend on the volume of data you’re working with. You can use signed URLs to upload directly or download/upload. Here’s a few documented approaches: AWS S3 Bucket | Roboflow
Yes. The best way to do this is triggering a train job to kickoff via API. For example, once a dataset has greater than X new images, you create a new trained model. A common way to do that is with the Python SDK: Train a Model | Roboflow
You can setup alerts based on model monitoring capabilities in (3). Typically, these alerts are if there’s a prediction that is of a specific confidence or drift in results.
Our team would be happy to show you how to setup many of these capabilities directly. Please feel free to write joseph.nelson [@] roboflow.com to get a guided walkthrough.