rareplane_segmentation_1_7

from detectron2.utils.visualizer import ColorMode
json_file_test = "/mnt/d/RarePlanes/datasets/synthetic/metadata_annotations/instances_test_aircraft.json"
coco_test=COCO(json_file_test)

catIds = coco_test.getCatIds(catNms=['aircraft']);
imgIds = coco_test.getImgIds(catIds=catIds);

img = coco_test.loadImgs(imgIds[np.random.randint(0,len(imgIds))])[0]
im = cv2.imread("/mnt/d/RarePlanes/datasets/synthetic/test/images/" + img['file_name'])
plt.axis('off')
# plt.imshow(im)
# plt.show()
plt.imsave('input.png',im)
outputs = predictor(im)  # format is documented at https://detectron2.readthedocs.io/tutorials/models.html#model-output-format
v = Visualizer(im[:, :, ::-1],
               metadata=MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), 
               scale=0.5, 
               instance_mode=ColorMode.IMAGE_BW   # remove the colors of unsegmented pixels. This option is only available for segmentation models
)
out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
# plt.imshow(out.get_image()[:, :, ::-1])
# plt.show()
plt.imsave('out_put.png',out.get_image()[:, :, ::-1])