Model-Demo / configs /stage2-v2-snr_train.yaml
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config:
# others
seed: 1234
num_frames: 6
mode: pixel
offset_noise: true
gd_type: xyz
# model related
models:
config: imagedream/configs/sd_v2_base_ipmv_chin8_zero_snr.yaml
resume: release_models/ImageDream/sd-v2.1-base-4view-ipmv.pt
resume_unet: null
# eval related
sampler:
target: libs.sample.ImageDreamDiffusionStage2
params:
mode: pixel
num_frames: 6
camera_views: [1, 2, 3, 4, 5, 0]
ref_position: null
random_background: false
offset_noise: true
resize_rate: 1.0
# config datasets
train_data:
target: libs.data.DataHQCRelative
params:
xyz_base: train_examples
base_dir: train_examples
caption_csv: train_examples/caption.csv
image_size: 256
repeat: 1
camera_views: [1, 2, 3, 4, 5, 0]
ref_indexs: [0, 1, 3, 4]
ref_position: null
split: train
num_frames: 6
random_background: true
resize_rate: 0.95
eval_data:
target: libs.data.DataHQCRelative
params:
xyz_base: train_examples
base_dir: train_examples
caption_csv: train_examples/caption.csv
image_size: 256
repeat: 1
camera_views: [1, 2, 3, 4, 5, 0] # when pixel mode, last image will be coverd by ref image
ref_indexs: [0, 1, 3, 4]
ref_position: null
split: eval
num_frames: 6
random_background: true
resize_rate: 0.95
# optimizer related
optimizer:
lr: 5e-5
gradient_accumulation_steps: 12
# wandb related parameters
project: CRM
wandb_run_name: CRM-xyz
wandb_mode: offline
# training hyperparmeters
batch_size: 16
dataloader:
num_workers: 10
shuffle: true
drop_last: true
save_interval: 400000
log_interval: 5000
eval_interval: 50000
max_step: 100000000