Train a DepthNet to predict cloth depth map

[lyk412]

Thanks for your great and solid work! I noticed that the ICON pipeline includes a Normal model that predicts cloth normal map. Now I'm trying to train a Depth model to predict cloth depth map with the help of Normal's training code, but the results are bad. The train and val losses are on the rise. What do I need to do to fix this? Thanks again!

The visualized training results from tensorboard are as follows.

the training configs are:

name: depth ckpt_dir: "./data/ckpt/" resume_path: "./data/ckpt/depth.ckpt" results_path: "./results"

dataset: root: "./data/" rotation_num: 36 train_bsize: 1.0 val_bsize: 1.0 test_bsize: 1.0 types: ["thuman2"] scales: [100.0]

net: in_depth: (('image',3), ('T_depth_F',3), ('T_depth_B',3))

lr_N: 1e-4 weight_decay: 0.0 momentum: 0.0 batch_size: 8 num_threads: 8 gpus: [0] test_gpus: [0]

fast_dev: 0 resume: False test_mode: False num_sanity_val_steps: 1

momentum: 0.0 optim: Adam

overfit: False num_epoch: 20 freq_show_train: 0.1 freq_show_val: 0.01 freq_plot: 0.01 freq_eval: 0.1 schedule: [18]