HumanGaussian
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Render All Black During Training
Hello! Thanks for your inspiring work! I am a beginner in this field and want to learn from your work.
When training with the given instruction:
python launch.py --config configs/test.yaml --train --gpu 0 system.prompt_processor.prompt="A boy with a beanie wearing a hoodie and joggers"
I found that all the renders in "save" dir are mere black, no figure or colourful gaussians seems to appear.
I also noticed that I've got 0 total parametres, maybe that is the problem.
I doubt that there is something wrong with my configuration or paths to SMPL or Texture-structure-joint, but I can't figure it out. here is my config:
name: "bennie-boy"
tag: "${rmspace:${system.prompt_processor.prompt},_}"
exp_root_dir: "/home/zsj/lyf/HumanGaussian/experiments"
seed: 0
data_type: "random-camera-datamodule"
data:
batch_size: 8
eval_camera_distance: 2.0
camera_distance_range: [1.5, 2.0]
light_sample_strategy: "dreamfusion3dgs"
height: 1024
width: 1024
# resolution_milestones: [600]
eval_height: 1024
eval_width: 1024
elevation_range: [-30, 30]
enable_near_head_poses: true
head_offset: 0.65
head_camera_distance_range: [0.4, 0.6]
head_prob: 0.25
head_start_step: 1200
head_end_step: 3600
head_azimuth_range: [0, 180]
enable_near_back_poses: true
back_offset: 0.65
back_camera_distance_range: [0.6, 0.8]
back_prob: 0.20
back_start_step: 1200
back_end_step: 3600
back_azimuth_range: [-180, 0]
system_type: "gaussiandreamer-system"
system:
radius: ${data.eval_camera_distance}
texture_structure_joint: true
smplx_path: /data1/human_dataset/smplx #"/path/to/the/downloaded/smplx_models" # I gave the folder
disable_hand_densification: false
pts_num: 100000
densify_prune_start_step: 300
densify_prune_end_step: 2100
densify_prune_interval: 300
size_threshold: 20
max_grad: 0.0002
gender: 'neutral'
prune_only_start_step: 2400
prune_only_end_step: 3300
prune_only_interval: 300
prune_size_threshold: 0.008
apose: true
bg_white: false
prompt_processor_type: "texture-structure-prompt-processor"
prompt_processor:
use_perp_neg: false
pretrained_model_name_or_path: "stabilityai/stable-diffusion-2-base"
negative_prompt: "shadow, dark face, colorful hands, eyeglass, glasses, (deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck"
prompt: "???"
guidance_type: "dual-branch-guidance"
guidance:
pretrained_model_name_or_path: "stabilityai/stable-diffusion-2-base"
model_key: "/data1/human_dataset/texture_structure_joint/unet" #"/path/to/pretrained/texture-structure_joint_model"
vae_key: "stabilityai/sd-vae-ft-mse"
guidance_scale: 7.5
weighting_strategy: sds
min_step_percent: 0.02
max_step_percent: 0.98
grad_clip: [0,1.5,2.0,1000]
lw_depth: 0.5
guidance_rescale: 0.75
original_size: 1024
target_size: 1024
use_anpg: true
enable_memory_efficient_attention: true
grad_clip_pixel: true
grad_clip_threshold: 1.0
loggers:
wandb:
enable: false
project: 'threestudio'
name: None
loss:
lambda_sds: 1.
lambda_sparsity: 1.
lambda_opaque: 0.0
optimizer:
name: Adam
args:
lr: 0.001
betas: [0.9, 0.99]
eps: 1.e-15
trainer:
max_steps: 3600
log_every_n_steps: 1
num_sanity_val_steps: 0
val_check_interval: 100
enable_progress_bar: true
precision: 16-mixed
checkpoint:
save_last: true # save at each validation time
save_top_k: -1
every_n_train_steps: ${trainer.max_steps}
Would you be so kind to help me out? Thanks!