Configure image backend for detection crops

[mihow]

Previously the ML backend was managing crops itself and pushing them directly to S3. This is no longer the case, the ML backend returns just bounding boxes and the platform must create the cropped images for web display.

• Removes hardcoded paths to the S3 storage URLs that the ML backend was using
• Configures detection crops to use Django's storage backend (which connects to our Compute Canada object store)
• Adds methods for finding and creating missing crops - with both a management command and a background task.
• Adds generators for creating test image data for automated testing & dev environments.
• Detection crops are created after a pipeline processing request is returned from an ML backend

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[sentry-io]

Suspect Issues

This pull request was deployed and Sentry observed the following issues:

• ‼️ OperationalError: MISCONF Redis is configured to save RDB snapshots, but it is currently not able to persist on dis... ami.jobs.tasks.run_job View Issue

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