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Description
Hi, thanks for your great work.
I encountered some problems when I am trying to reproduce the XVerseBench.
When I run the assets/segmentation.py, I found the detector.get_multiple_instances
(line 34) produces empty results on all images in the DreamBench+ dataset.
More extactly, I found this line in grounded_sam2_florence2_autolabel_pipeline.py (line 255) produces empty results.
grounding_results = self.run_florence2('<OPEN_VOCABULARY_DETECTION>', text_input, image)['<OPEN_VOCABULARY_DETECTION>']
Then the program always goes to the if branch in line 257-258.
I download the checkpoints of Florence2 using the provided download_ckpts
script. However, when I load in this weight, the code returns such a warning:
Some weights of Florence2ForConditionalGeneration were not initialized from the model checkpoint at ./checkpoints/Florence-2-large and are newly initialized: ['language_model.lm_head.weight'] You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
I'm not sure whether it is correct. I would be very grateful if you can help me solve this problem. Thanks for your help in advance.