options/depth.yaml

group: depth
name: depth_est
load: 

batch_size: 44
debug: false
image_size: [224,224]
gpu: 0
max_epoch: 15
output_root: output
resume: false
seed: 0
yaml:

arch:
    depth:
        pretrained: model/depth/pretrained_weights/omnidata_dpt_depth_v2.ckpt

eval:
    batch_size: 44
    n_vis: 50
    depth_cap: 
    d_thresholds: [1.02,1.05,1.1,1.2]

data:
    num_classes_test: 15
    max_img_cat: 
    dataset_train: synthetic
    dataset_test: synthetic
    num_workers: 6
    bgcolor: 1
    pix3d:                       
        cat: 
    ocrtoc:                       
        cat: 
        erode_mask: 10
    synthetic:        
        subset: objaverse_LVIS,ShapeNet55
        percentage: 1
    train_sub:
    val_sub:

training:
    n_sdf_points: 4096
    depth_loss:
        grad_reg: 0.1
        depth_inv: true
        mask_shrink: false

loss_weight:
    depth: 1
    intr: 10
    
optim:
    lr: 3.e-5
    weight_decay: 0.05
    clip_norm: 
    amp: false
    accum: 1
    sched: false

tb:
    num_images: [4,8]

freq:
    print: 200
    print_eval: 100
    scalar: 1000 # iterations
    vis: 1000 # iterations
    save_vis: 1000
    ckpt_latest: 1000 # iterations
    eval: 1