config/unet_hyperism.yaml

dataset_params_shading:
  im_path: '/home/project/dataset/Hyperism/hyperism_ldr_shading_ground_truth_256'
  im_channels : 1
  im_size : 256
  name: 'ldr_to_sh_flow'

dataset_params:
  im_path: '/home/project/dataset/Hyperism/hyperism_ldr_albedo_ground_truth_256'
  im_channels : 1
  im_size : 256
  name: 'ldr_to_sh_flow'

albedo_params:
  im_path: '/home/project/dataset/Hyperism/hyperism_ldr_albedo_ground_truth_256'
  im_channels : 3
  im_size : 256
  name: 'ldr_to_sh_flow'

dataset_params_input:
  im_path: '/home/project/dataset/Hyperism/sh_al_hyperism_ldr_dequantize_linearize_256'
  im_channels :  3
  im_size : 256
  name: 'ldr_to_sh_flow'

autoencoder_params:
  z_channels: 8

train_params:
  im_size_lt : 32
  seed : 107
  task_name: 'ldr_to_sh_flow'
  ldm_batch_size: 32
  autoencoder_batch_size: 64
  disc_start: 31500
  disc_weight: 0.25
  perceptual_weight: 10
  kl_weight: 0.005
  gradient_weight: 0
  ldm_epochs : 1000
  autoencoder_epochs : 2000
  num_samples : 25
  ldm_lr: 0.0001
  albedo_weight : 1
  shading_weight : 1
  autoencoder_lr: 0.0001
  discriminator_lr: 0.00005
  autoencoder_acc_steps : 1
  autoencoder_img_save_steps : 6100
  save_latents : False
  vae_latent_dir_name : 'latent_output/latent_vectors.h5'
  ldm_ckpt_name: 'flow_model_ckpt.pth'
  ldm_ckpt_name_fine: 'best_flow_model_ckpt.pth'
  vae_autoencoder_ckpt_name: 'epoch_290_best_autoencoder_model_checkpoint.pth'
  vae_discriminator_ckpt_name: 'vae_discriminator_ckpt.pth'  
  encoder_ckpt_name: 'encoder_ckpt.pth'  
  ldm_optimizer_ckpt_name: 'ldm_optimizer_ckpt.pth'