predictions.py

from detectron2.utils.visualizer import ColorMode

#Use the final weights generated after successful training for inference  
cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final.pth")

cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.8  # set the testing threshold for this model
#Pass the validation dataset
cfg.DATASETS.TEST = ("boardetect_val", )

predictor = DefaultPredictor(cfg)

dataset_dicts = get_board_dicts("Text_Detection_Dataset_COCO_Format/val")
for d in random.sample(dataset_dicts, 3):    
    im = cv2.imread(d["file_name"])
    outputs = predictor(im)
    v = Visualizer(im[:, :, ::-1],
                   metadata=board_metadata, 
                   scale=0.8,
                   instance_mode=ColorMode.IMAGE   
    )
    v = v.draw_instance_predictions(outputs["instances"].to("cpu")) #Passing the predictions to CPU from the GPU
    cv2_imshow(v.get_image()[:, :, ::-1])