def setup(args):
"""
Create configs and perform basic setups.
"""
cfg = get_cfg()
add_detr_config(cfg)
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
default_setup(cfg, args)
return cfg
def setup(args):
"""
Create configs and perform basic setups.
"""
cfg = get_cfg()
add_detr_config(cfg)
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
if args.eval_only:
# It's important to set num_worker = 1 for tracking.
cfg.DATALOADER.NUM_WORKERS = 1
cfg.freeze()
default_setup(cfg, args)
return cfg
BASE = '/home/benedikt/PycharmProjects/pytorch-deeplab-xception/data/cityscapes/leftImg8bit/train'
imgs = [
'hamburg/hamburg_000000_027304_leftImg8bit.png',
'hamburg/hamburg_000000_032906_leftImg8bit.png',
'zurich/zurich_000067_000019_leftImg8bit.png',
'ulm/ulm_000014_000019_leftImg8bit.png',
'ulm/ulm_000019_000019_leftImg8bit.png'
]
imgs = list(map(lambda x: os.path.join(BASE, x), imgs))
# Get image
im = cv2.imread(imgs[0])
# Get the configuration ready
cfg = get_cfg()
add_detr_config(cfg)
cfg.merge_from_file("configs/detr_citypersons_256_6_6_torchvision.yaml")
cfg.MODEL.WEIGHTS = "output/model_0001399.pth"
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5
predictor = DefaultPredictor(cfg)
outputs = predictor(im)
v = Visualizer(im[:,:,::-1], MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), scale=1.2)
v = v.draw_instance_predictions(outputs['instances'].to('cpu'))
img = v.get_image()[:, :, ::-1]
cv2.imwrite('output.jpg', img)