INNER CODE UNIT · Python

keep

aangelopoulos/conformal-prediction · generation-scripts/generate-coco.py:36

    keep = labels.sum(dim=1) > 0
    scores = scores[keep].numpy()
    labels = labels[keep].numpy()
    paths = np.array(paths)[keep.numpy()]
    
    return scores, labels, paths 

if __name__ == "__main__":
    with torch.no_grad():
        args = { 'num_classes': 80, 'model_path': str(ABSPATH) + '/coco_utils/tresnet_xl_COCO_640_91_4.pth', 'model_name': 'tresnet_xl', 'input_size': 640, 'use_ml_decoder': 1 }

        # Setup model
        print('creating model {}...'.format(args['model_name']))
        if not os.path.exists(args['model_path']):
            os.system('wget https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ML_Decoder/tresnet_xl_COCO_640_91_4.pth -O ' + args['model_path'])
        model = create_model(args, load_head=True).cuda()
        model = model.cpu()
        model = InplacABN_to_ABN(model)

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