ValueError: COLMAP data not found. Traceback (most recent call last):

[mmxuan18]

run on linux server when run throw ValueError: COLMAP data not found. Traceback (most recent call last): error , can close colmap?

[SuLvXiangXin]

@mmxuan18 You may do not have your data in the correct place.

[SvenPaterson]

I have this same error, where would the correct place be to put the data? I have the example lego data in a folder located at ./data/lego and this same error pops for me:

$ accelerate launch train.py     --gin_configs=configs/360.gin     --gin_bindings="Config.data_dir = '${DATA_DIR}'"     --gin_bindings="Config.exp_name = '${EXP_NAME}'"     --gin_bindings="Config.factor = 4"
The following values were not passed to `accelerate launch` and had defaults used instead:
        `--num_cpu_threads_per_process` was set to `6` to improve out-of-box performance when training on CPUs
To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
2023-06-30 11:40:11: Config(dataset_loader='llff', batching='all_images', batch_size=65536, patch_size=1, factor=4, multiscale=False, multiscale_levels=4, forward_facing=False, render_path=False, llffhold=8, llff_use_all_images_for_training=False, llff_use_all_images_for_testing=False, use_tiffs=False, compute_disp_metrics=False, compute_normal_metrics=False, disable_multiscale_loss=False, randomized=True, near=0.2, far=1000000.0, exp_name='lego', data_dir='data\\lego', vocab_tree_path=None, render_chunk_size=65536, num_showcase_images=5, deterministic_showcase=True, vis_num_rays=16, vis_decimate=0, max_steps=25000, early_exit_steps=None, checkpoint_every=5000, resume_from_checkpoint=True, checkpoints_total_limit=1, gradient_scaling=False, print_every=100, train_render_every=500, data_loss_type='charb', charb_padding=0.001, data_loss_mult=1.0, data_coarse_loss_mult=0.0, interlevel_loss_mult=0.0, anti_interlevel_loss_mult=0.01, orientation_loss_mult=0.0, orientation_coarse_loss_mult=0.0, orientation_loss_target='normals_pred', predicted_normal_loss_mult=0.0, predicted_normal_coarse_loss_mult=0.0, hash_decay_mults=0.1, lr_init=0.01, lr_final=0.001, lr_delay_steps=5000, lr_delay_mult=1e-08, adam_beta1=0.9, adam_beta2=0.99, adam_eps=1e-15, grad_max_norm=0.0, grad_max_val=0.0, distortion_loss_mult=0.005, opacity_loss_mult=0.0, eval_only_once=True, eval_save_output=True, eval_save_ray_data=False, eval_render_interval=1, eval_dataset_limit=2147483647, eval_quantize_metrics=True, eval_crop_borders=0, render_video_fps=60, render_video_crf=18, render_path_frames=120, z_variation=0.0, z_phase=0.0, render_dist_percentile=0.5, render_dist_curve_fn=<ufunc 'log'>, render_path_file=None, render_resolution=None, render_focal=None, render_camtype=None, render_spherical=False, render_save_async=True, render_spline_keyframes=None, render_spline_n_interp=30, render_spline_degree=5, render_spline_smoothness=0.03, render_spline_interpolate_exposure=False, rawnerf_mode=False, exposure_percentile=97.0, num_border_pixels_to_mask=0, apply_bayer_mask=False, autoexpose_renders=False, eval_raw_affine_cc=False, zero_glo=False, valid_weight_thresh=0.05, isosurface_threshold=20, mesh_voxels=134217728, visibility_resolution=512, mesh_radius=1.0, mesh_max_radius=10.0, std_value=0.0, compute_visibility=False, extract_visibility=True, decimate_target=-1, vertex_color=True, vertex_projection=True, tsdf_radius=2.0, tsdf_resolution=512, truncation_margin=5.0, tsdf_max_radius=10.0)
2023-06-30 11:40:11: Distributed environment: NO
Num processes: 1
Process index: 0
Local process index: 0
Device: cpu

Mixed precision type: fp16

2023-06-30 11:40:11: Error!
Traceback (most recent call last):
  File "C:\Users\stephen\zipnerf-pytorch\train.py", line 387, in <module>
    app.run(main)
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\site-packages\absl\app.py", line 308, in run
    _run_main(main, args)
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\site-packages\absl\app.py", line 254, in _run_main
    sys.exit(main(argv))
  File "C:\Users\stephen\zipnerf-pytorch\train.py", line 73, in main
    dataset = datasets.load_dataset('train', config.data_dir, config)
  File "C:\Users\stephen\zipnerf-pytorch\internal\datasets.py", line 39, in load_dataset      
    return dataset_dict[config.dataset_loader](split, train_dir, config)
  File "C:\Users\stephen\zipnerf-pytorch\internal\datasets.py", line 278, in __init__
    self._load_renderings(config)
  File "C:\Users\stephen\zipnerf-pytorch\internal\datasets.py", line 547, in _load_renderings 
    raise ValueError('COLMAP data not found.')
ValueError: COLMAP data not found.
Traceback (most recent call last):
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\runpy.py", line 197, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\stephen\miniconda3\envs\zipnerf\Scripts\accelerate.exe\__main__.py", line 7, in <module>
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\site-packages\accelerate\commands\accelerate_cli.py", line 45, in main
    args.func(args)
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\site-packages\accelerate\commands\launch.py", line 941, in launch_command
    simple_launcher(args)
  File "C:\Users\stephen\miniconda3\envs\zipnerf\lib\site-packages\accelerate\commands\launch.py", line 603, in simple_launcher
    raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['C:\\Users\\stephen\\miniconda3\\envs\\zipnerf\\python.exe', 'train.py', '--gin_configs=configs/360.gin', "--gin_bindings=Config.data_dir = 'data\\lego'", "--gin_bindings=Config.exp_name = 'lego'", '--gin_bindings=Config.factor = 4']' returned non-zero exit status 1.

[SuLvXiangXin]

@SvenPaterson You should use blender.gin instead of 360.gin as in https://github.com/SuLvXiangXin/zipnerf-pytorch/blob/main/scripts/train_blender.sh

[SvenPaterson]

thanks, progress made. Now I get RuntimeError: Windows not yet supported for torch.compile. I'm running cuda=118 based on reply to this issue: https://github.com/SuLvXiangXin/zipnerf-pytorch/issues/44

[SuLvXiangXin]

Just comment out torch.complie