config.conf

general {
    base_exp_dir = ./exp/smpl/examples/yanwen_suit
    recording = [
        ./,
        ./models
    ]
    character_prompt = a  man wearing suit\, short hair 
    character_face_prompt = a  sks man wearing suit\, short hair
    
    sd_path = stablediffusionapi/realistic-vision
    sd_face_path = yif271/yanwenbatch2_500
}

dataset {
    data_dir = ./data/zero_beta_tpose_render
}

train {
    learning_rate = 3e-4
    learning_rate_alpha = 0.1
    end_iter = 15000

    batch_size = 512
    max_ray_num = 4000
    validate_resolution_level = 1
    warm_up_end = 500
    anneal_end = 0
    use_white_bkgd = False

    save_freq = 1000
    val_freq = 100
    val_mesh_freq = 500
    report_freq = 100

    igr_weight = 0.1
    mask_weight = 1.0

    clip_weight = 1.0
    pretrain =  ./pretrained_models/zero_beta_stand_pose.pth

    add_no_texture = True
    texture_cast_light = True
    use_face_prompt = True
    use_back_prompt = True
    use_silhouettes = True
}

clip {
    prompt = a 3D rendering of the superman in unreal engine
    face_prompt = a 3D rendering of the face of the superman in unreal engine
    back_prompt = a 3D rendering of the back of the superman in unreal engine
}

model {
    nerf {
        D = 4,
        d_in = 4,
        d_in_view = 3,
        W = 256,
        multires = 10,
        multires_view = 4,
        output_ch = 4,
        skips=[4],
        use_viewdirs=True
    }

    sdf_network {
        d_out = 257,
        d_in = 3,
        d_hidden = 256,
        n_layers = 4,
        skip_in = [4],
        multires = 6,
        bias = 0.5,
        scale = 1.0,
        geometric_init = True,
        weight_norm = True,
    }

    variance_network {
        init_val = 0.3
    }

    rendering_network {
        d_feature = 256,
        mode = no_view_dir,
        d_in = 6,
        d_out = 3,
        d_hidden = 256,
        n_layers = 2,
        weight_norm = True,
        multires_view = 0,
        squeeze_out = True,
        extra_color = True,
    }

    neus_renderer {
        n_samples = 32,
        n_importance = 32,
        n_outside = 0,
        up_sample_steps = 4 ,    # 1 for simple coarse-to-fine sampling
        perturb = 1.0,
        extra_color = True,
    }
}