This pull request introduces a new model, DiffusionDet, and its associated components. The changes include the addition of configuration, head, loss, and model files, as well as a temporary debug script to test the model.
This is a first draft, nothing ready to use right now, I am creating this PR to get some feedback as it is my first time.

Key changes:

New Model Addition:

• src/diffusers/models/diffusiondet/modeling_diffusiondet.py: Added the DiffusionDet class to implement the DiffusionDet model. This includes the model's initialization and forward pass.

Configuration:

• src/diffusers/models/diffusiondet/configuration_diffusiondet.py: Added the DiffusionDetConfig class to handle the configuration settings for the DiffusionDet model.

Head Implementation:

• src/diffusers/models/diffusiondet/head.py: Added the DiffusionDetHead class and supporting functions for the model's head, including the ROIPooler class for region of interest pooling.

Loss Computation:

• src/diffusers/models/diffusiondet/loss.py: Added the DynamicCriterion class to compute the loss for the DiffusionDet model, including the process for Hungarian assignment and supervision of matched pairs.

Debug Script:

• debug_diffusiondet.py: Added a script to create and test the DiffusionDet model using the configuration and model classes.# What does this PR do?

Fixes # (issue)

• DiffusionDet: Diffusion models for object detection #1350

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@patrickvonplaten and @ShoufaChen participated in the previous implementation trial.