Implement ObjectDetection support #205
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Summary
This PR is an attempt to implement support for ObjectDetection models in optimum ExecuTorch. This PR adds
ExecuTorchModelForObjectDetection,ObjectDetectionExportableModule, a task for object-detection, and a test for DETR type models.Notes
ObjectDetectionExportableModuletraces an object detection model, and storesnum_channels,image_size,get_label_idsandget_label_namesnum_channelsis not consistently defined in configs for the existing object detection models, so the ObjectDetectionExportableModule will try a few different config options, and if it can't resolve it it'll default to 3 (RGB), which I feel like is a sensible default. the priority goeskwargs defined num_channels -> config defined num_channels -> 3image_sizeis also not defined in configurations typically, as some models have dynamic sizes; there's not really a sensible default, since users would pick a size to use at inference/deployment time. So for this, the image size is passed in via the CLI and will only be used for object-detection modelsget_label_idsandget_label_namesare two flat lists that are used to construct id2label; for some reason executorch doesn't seem to support storing dicts as values in constant_methods (it gets flattened)ExecuTorchModelForObjectDetectionhas 3 attributes: num_channels, image_size, and id2label, which is a dict of class ids to labels.timmas a dev dependency for DETRTesting
This is my first PR in this repo, so I'm open to any feedback!