uncbiag / mermaid

Image registration using pytorch
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where is the test2d_tst.json? #136

Closed imzhangyd closed 2 years ago

imzhangyd commented 4 years ago

when i run the jupyter --example_simple_interface. the test2d_tst.json can't find in the repository. and there's an error Could not open file = test2d_tst.json; ignoring request.

papasanimohansrinivas commented 3 years ago

yeah me too unable find this test2d_tst.json and not able to run any eregistration methods ! @hbgtjxzbbx

hbgtjxzbbx commented 3 years ago

@yudzhang @papasanimohansrinivas sorry for the late reply. I haven't tracked the issues for a long time. I attach the content of the json. BTW, current mermaid only support pytorch <= 1.7. Pytorch change its interface for FFT. we would make update soon.

{
    "model": {
        "deformation": {
            "compute_similarity_measure_at_low_res": false,
            "map_low_res_factor": null,
            "use_map": true
        },
        "registration_model": {
            "env": {
                "get_momentum_from_external_network": false,
                "reg_factor": 1.0,
                "use_ode_tuple": false,
                "use_odeint": true
            },
            "forward_model": {
                "adjoin_on": true,
                "atol": 1e-05,
                "number_of_time_steps": 20,
                "rtol": 1e-05,
                "smoother": {
                    "multi_gaussian_stds": [
                        0.05,
                        0.1,
                        0.15,
                        0.2,
                        0.25
                    ],
                    "multi_gaussian_weights": [
                        0.06666666666666667,
                        0.13333333333333333,
                        0.19999999999999998,
                        0.26666666666666666,
                        0.3333333333333333
                    ],
                    "type": "multiGaussian"
                },
                "solver": "rk4"
            },
            "loss": {
                "display_max_displacement": false,
                "limit_displacement": false,
                "max_displacement": 0.05
            },
            "similarity_measure": {
                "develop_mod_on": false,
                "sigma": 0.1,
                "type": "ncc"
            },
            "spline_order": 1,
            "type": "svf_scalar_momentum_map",
            "use_CFL_clamping": true
        }
    },
    "optimizer": {
        "gradient_clipping": {
            "clip_display": false,
            "clip_individual_gradient": true,
            "clip_individual_gradient_value": 1.0,
            "clip_shared_gradient": true,
            "clip_shared_gradient_value": 1.0
        },
        "name": "sgd",
        "scheduler": {
            "factor": 0.5,
            "patience": 10,
            "verbose": true
        },
        "sgd": {
            "individual": {
                "dampening": 0.0,
                "lr": 0.1,
                "momentum": 0.9,
                "nesterov": true,
                "weight_decay": 0.0
            },
            "shared": {
                "dampening": 0.0,
                "lr": 0.1,
                "momentum": 0.9,
                "nesterov": true,
                "weight_decay": 0.0
            }
        },
        "single_scale": {
            "nr_of_iterations": 100,
            "rel_ftol": 1e-07
        },
        "use_step_size_scheduler": true,
        "weight_clipping_type": "none",
        "weight_clipping_value": 1.0
    }
}