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| Dataset | Mode | Download |
|---|---|---|
| PIDray | text-grounded inpainting | HF Hub |
| OPIXray | text-grounded inpainting | HF Hub |
| HiXray | text-grounded inpainting | HF Hub |
--ckpt_path. Then run:python gligen_inference.py--output_path: the path to save your generated x-ray security images--annotation_path: the path to save the refined annotation (stored in txt format)--vis_path: the path to save visualization compared with gt--ca_vis_path: the path to save cross-attention maps--image_path: the path to load images you want to inpaint--ckpt_path: the generation model checkpoint path--gligen_caption_pt: the file to prepare your training/test data in GLIGEN format--gen_method: set to 1 for Xsyn-M and 3 for Xsyn-A--refine_anno: set to True for CAR--latent_redist: set to True for BOMdownstream_test.sh to test the performance of our synthetic data. Our downstream detection environment is mmdetection.