Speed up inference instance segmentation

[namnguyenhai]

Hi All, I have working instance segmentation, I'm using "mask_rcnn_R_101_FPN_3x" model. When I inference image it takes about 3 second / image on GPU. How can I speed up it faster ?

I code in Google Colab

This is my setup config:

cfg = get_cfg()

cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml"))

cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1 

cfg.OUTPUT_DIR = "/content/drive/MyDrive/TEAM/save/"

cfg.DATASETS.TRAIN = (train_name,)
cfg.DATASETS.TEST = (test_name, )
cfg.MODEL.WEIGHTS = os.path.join(cfg.OUTPUT_DIR, "model_final.pth")

This is inference:

torch.backends.cudnn.benchmark = True
start = time.time()

predictor = DefaultPredictor(cfg) 

im = cv2.imread("/content/drive/MyDrive/TEAM/mcocr_val_145114ixmyt.jpg")

outputs = predictor(im) 

print(f"Inference time per image is : {(time.time() - start)} s")

Return

Image I inference size 1024 x 1024 pixel. I have change different size but it still inference 3 second / image. Am I missing anything about Detectron2 ?

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