6d68dca2aec44c5b1a73e6c9db5c5fbf6f731fd0,keras_retinanet/bin/evaluate.py,,main,#Any#,130

Before Change

        anchors_path = anchors_path if os.path.exists(anchors_path) else None
    else:
        anchors_path = args.anchors
    anchors_dict = get_anchors_params(anchors_path)
    anchors_params = AnchorParameters(**anchors_dict)

    // create the generator
    //(It"s ok not to update anchors args, as we only use the generator for load images and annotations.)
    generator = create_generator(args)

    // load the model
    print("Loading model, this may take a second...")
    model = models.load_model(args.model, backbone_name=args.backbone, convert=args.convert_model,anchor_parameters = anchors_params)

    // print model summary
    // print(model.summary())

After Change

    // load the model
    print("Loading model, this may take a second...")
    if args.config and "anchor_parameters" in args.config:
        anchor_params = parse_anchor_parameters(args.config)
        model = models.load_model(args.model, backbone_name=args.backbone, convert=args.convert_model, anchor_params=anchor_params)
    else:
        model = models.load_model(args.model, backbone_name=args.backbone, convert=args.convert_model)

    // print model summary
    // print(model.summary())

    // start evaluation
    if args.dataset_type == "coco":
        from ..utils.coco_eval import evaluate_coco
        evaluate_coco(generator, model, args.score_threshold)
    else:

Instances