Error occurred when executing MeshGraphormer-DepthMapPreprocessor:

No module named 'scipy.sparse._csc'

File "/kaggle/temp/ComfyUI/execution.py", line 151, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "/kaggle/temp/ComfyUI/execution.py", line 81, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "/kaggle/temp/ComfyUI/execution.py", line 74, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/node_wrappers/mesh_graphormer.py", line 68, in execute
else MeshGraphormerDetector.from_pretrained(detect_thr=detect_thr, presence_thr=presence_thr).to(model_management.get_torch_device())
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/src/controlnet_aux/mesh_graphormer/__init__.py", line 23, in from_pretrained
pipeline = MeshGraphormerMediapipe(args, detect_thr=detect_thr, presence_thr=presence_thr)
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/src/controlnet_aux/mesh_graphormer/pipeline.py", line 77, in __init__
mano_model = MANO().to(args.device)
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/src/custom_mesh_graphormer/modeling/_mano.py", line 31, in __init__
self.layer = self.get_layer()
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/src/custom_mesh_graphormer/modeling/_mano.py", line 54, in get_layer
return ManoLayer(mano_root=osp.join(self.mano_dir), flat_hand_mean=False, use_pca=False) # load right hand MANO model
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/src/custom_manopth/manolayer.py", line 65, in __init__
smpl_data = ready_arguments(self.mano_path)
File "/kaggle/temp/ComfyUI/custom_nodes/comfyui_controlnet_aux/src/custom_manopth/smpl_handpca_wrapper_HAND_only.py", line 36, in ready_arguments
dd = pickle.load(open(fname_or_dict, 'rb'), encoding='latin1')

-----------

try:
    import scipy.sparse._csc
    print("scipy.sparse._csc is available.")
except ImportError as e:
    print("An import error occurred:", e)

Результат выполнения этого кода:

An import error occurred: cannot import name 'np_long' from 'scipy._lib._util' (/opt/conda/lib/python3.10/site-packages/scipy/_lib/_util.py)

#Код1#:

import subprocess
import sys

# Обновление pip и scipy до последней версии
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--upgrade', 'pip'])
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--upgrade', 'scipy'])

# Проверка корректности установки и наличие нужных подмодулей
try:
    import scipy
    import scipy.sparse
    from scipy.sparse import csc_matrix
    print("scipy version:", scipy.version)
    print("scipy.sparse and scipy.sparse.csc_matrix are available.")
except ImportError as e:
    print(f"An import error occurred: {e}")

# Дополнительная проверка специфичных элементов
try:
    from scipy.sparse import _csc
    print("scipy.sparse._csc is available.")
except ImportError as e:
    print(f"An import error occurred while importing scipy.sparse._csc: {e}")

print("Проверка завершена")

Результат выполнения кода #Код1#:

Requirement already satisfied: pip in /opt/conda/lib/python3.10/site-packages (24.1.2)
Requirement already satisfied: scipy in /opt/conda/lib/python3.10/site-packages (1.7.3)
Collecting scipy
  Downloading scipy-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (60 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 60.8/60.8 kB 3.1 MB/s eta 0:00:00
Collecting numpy<2.3,>=1.23.5 (from scipy)
  Downloading numpy-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (60 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 60.9/60.9 kB 2.5 MB/s eta 0:00:00
Downloading scipy-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.1 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 41.1/41.1 MB 41.9 MB/s eta 0:00:00:00:0100:01
Downloading numpy-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (19.3 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.3/19.3 MB 77.1 MB/s eta 0:00:00:00:0100:01
Installing collected packages: numpy, scipy
  Attempting uninstall: numpy
    Found existing installation: numpy 1.22.4
    Uninstalling numpy-1.22.4:
      Successfully uninstalled numpy-1.22.4
  Attempting uninstall: scipy
    Found existing installation: scipy 1.7.3
    Uninstalling scipy-1.7.3:
      Successfully uninstalled scipy-1.7.3
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
cudf 23.8.0 requires cupy-cuda11x>=12.0.0, which is not installed.
cuml 23.8.0 requires cupy-cuda11x>=12.0.0, which is not installed.
dask-cudf 23.8.0 requires cupy-cuda11x>=12.0.0, which is not installed.
apache-beam 2.46.0 requires dill<0.3.2,>=0.3.1.1, but you have dill 0.3.7 which is incompatible.
apache-beam 2.46.0 requires numpy<1.25.0,>=1.14.3, but you have numpy 2.0.0 which is incompatible.
apache-beam 2.46.0 requires protobuf<4,>3.12.2, but you have protobuf 4.25.3 which is incompatible.
apache-beam 2.46.0 requires pyarrow<10.0.0,>=3.0.0, but you have pyarrow 11.0.0 which is incompatible.
astropy 5.3.4 requires numpy<2,>=1.21, but you have numpy 2.0.0 which is incompatible.
cudf 23.8.0 requires pandas<1.6.0dev0,>=1.3, but you have pandas 2.0.3 which is incompatible.
cuml 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
cuml 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
cupy 12.2.0 requires numpy<1.27,>=1.20, but you have numpy 2.0.0 which is incompatible.
dask-cuda 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
dask-cuda 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
dask-cuda 23.8.0 requires pandas<1.6.0dev0,>=1.3, but you have pandas 2.0.3 which is incompatible.
dask-cudf 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
dask-cudf 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
dask-cudf 23.8.0 requires pandas<1.6.0dev0,>=1.3, but you have pandas 2.0.3 which is incompatible.
fastai 2.7.13 requires torch<2.2,>=1.10, but you have torch 2.3.1 which is incompatible.
gradio 4.37.2 requires urllib3~=2.0, but you have urllib3 1.26.16 which is incompatible.
libpysal 4.9.2 requires packaging>=22, but you have packaging 21.3 which is incompatible.
libpysal 4.9.2 requires shapely>=2.0.1, but you have shapely 1.8.5.post1 which is incompatible.
matplotlib 3.7.3 requires numpy<2,>=1.20, but you have numpy 2.0.0 which is incompatible.
momepy 0.6.0 requires shapely>=2, but you have shapely 1.8.5.post1 which is incompatible.
numba 0.57.1 requires numpy<1.25,>=1.21, but you have numpy 2.0.0 which is incompatible.
pymc3 3.11.5 requires numpy<1.22.2,>=1.15.0, but you have numpy 2.0.0 which is incompatible.
pymc3 3.11.5 requires scipy<1.8.0,>=1.7.3, but you have scipy 1.14.0 which is incompatible.
raft-dask 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
raft-dask 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
spacy 3.7.2 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.
tensorflow 2.13.0 requires numpy<=1.24.3,>=1.22, but you have numpy 2.0.0 which is incompatible.
tensorflow 2.13.0 requires typing-extensions<4.6.0,>=3.6.6, but you have typing-extensions 4.12.2 which is incompatible.
tensorflow-probability 0.21.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.12.2 which is incompatible.
tensorflow-transform 0.14.0 requires numpy<2,>=1.16, but you have numpy 2.0.0 which is incompatible.
tensorflow-transform 0.14.0 requires protobuf<4,>=3.7, but you have protobuf 4.25.3 which is incompatible.
tensorflowjs 4.13.0 requires packaging~=23.1, but you have packaging 21.3 which is incompatible.
transformers 4.42.4 requires numpy<2.0,>=1.17, but you have numpy 2.0.0 which is incompatible.
ultralytics 8.2.54 requires numpy<2.0.0,>=1.23.0, but you have numpy 2.0.0 which is incompatible.
woodwork 0.26.0 requires numpy<1.25.0,>=1.22.0, but you have numpy 2.0.0 which is incompatible.
ydata-profiling 4.5.1 requires numpy<1.24,>=1.16.0, but you have numpy 2.0.0 which is incompatible.
ydata-profiling 4.5.1 requires pydantic<2,>=1.8.1, but you have pydantic 2.4.2 which is incompatible.
ydata-profiling 4.5.1 requires scipy<1.12,>=1.4.1, but you have scipy 1.14.0 which is incompatible.
Successfully installed numpy-2.0.0 scipy-1.14.0
scipy version: <module 'scipy.version' from '/opt/conda/lib/python3.10/site-packages/scipy/version.py'>
scipy.sparse and scipy.sparse.csc_matrix are available.
An import error occurred while importing scipy.sparse._csc: cannot import name 'np_long' from 'scipy._lib._util' (/opt/conda/lib/python3.10/site-packages/scipy/_lib/_util.py)
Проверка завершена

#Код2#:

import subprocess
import sys

# Обновление scipy до версии 1.7.3
subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'scipy==1.7.3'])

# Проверка корректности установки и наличие нужных подмодулей
try:
    import scipy
    import scipy.sparse
    from scipy.sparse import csc_matrix
    print("scipy version:", scipy.version)
    print("scipy.sparse and scipy.sparse.csc_matrix are available.")
except ImportError as e:
    print(f"An import error occurred: {e}")

# Дополнительная проверка специфичных элементов
try:
    from scipy.sparse import _csc
    print("scipy.sparse._csc is available.")
except ImportError as e:
    print(f"An import error occurred while importing scipy.sparse._csc: {e}")

print("Проверка завершена")

Результат выполнения кода #Код2#:

Collecting scipy==1.7.3
  Downloading scipy-1.7.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.2 kB)
Collecting numpy<1.23.0,>=1.16.5 (from scipy==1.7.3)
  Downloading numpy-1.22.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.0 kB)
Downloading scipy-1.7.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.9 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 39.9/39.9 MB 44.6 MB/s eta 0:00:00:00:0100:01
Downloading numpy-1.22.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.8 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 16.8/16.8 MB 85.4 MB/s eta 0:00:00:00:0100:01
Installing collected packages: numpy, scipy
  Attempting uninstall: numpy
    Found existing installation: numpy 1.26.4
    Uninstalling numpy-1.26.4:
      Successfully uninstalled numpy-1.26.4
  Attempting uninstall: scipy
    Found existing installation: scipy 1.14.0
    Uninstalling scipy-1.14.0:
      Successfully uninstalled scipy-1.14.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
cudf 23.8.0 requires cupy-cuda11x>=12.0.0, which is not installed.
cuml 23.8.0 requires cupy-cuda11x>=12.0.0, which is not installed.
dask-cudf 23.8.0 requires cupy-cuda11x>=12.0.0, which is not installed.
apache-beam 2.46.0 requires dill<0.3.2,>=0.3.1.1, but you have dill 0.3.7 which is incompatible.
apache-beam 2.46.0 requires protobuf<4,>3.12.2, but you have protobuf 4.25.3 which is incompatible.
apache-beam 2.46.0 requires pyarrow<10.0.0,>=3.0.0, but you have pyarrow 11.0.0 which is incompatible.
chex 0.1.84 requires numpy>=1.24.1, but you have numpy 1.22.4 which is incompatible.
cudf 23.8.0 requires pandas<1.6.0dev0,>=1.3, but you have pandas 2.0.3 which is incompatible.
cuml 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
cuml 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
cuml 23.8.0 requires scipy>=1.8.0, but you have scipy 1.7.3 which is incompatible.
dask-cuda 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
dask-cuda 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
dask-cuda 23.8.0 requires pandas<1.6.0dev0,>=1.3, but you have pandas 2.0.3 which is incompatible.
dask-cudf 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
dask-cudf 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
dask-cudf 23.8.0 requires pandas<1.6.0dev0,>=1.3, but you have pandas 2.0.3 which is incompatible.
esda 2.5.1 requires scipy>=1.9, but you have scipy 1.7.3 which is incompatible.
fastai 2.7.13 requires torch<2.2,>=1.10, but you have torch 2.3.1 which is incompatible.
featuretools 1.28.0 requires scipy>=1.10.0, but you have scipy 1.7.3 which is incompatible.
gradio 4.37.2 requires urllib3~=2.0, but you have urllib3 1.26.16 which is incompatible.
inequality 1.0.1 requires numpy>=1.23, but you have numpy 1.22.4 which is incompatible.
inequality 1.0.1 requires scipy>=1.8, but you have scipy 1.7.3 which is incompatible.
jax 0.4.20 requires scipy>=1.9, but you have scipy 1.7.3 which is incompatible.
jaxlib 0.4.20+cuda11.cudnn86 requires scipy>=1.9, but you have scipy 1.7.3 which is incompatible.
libpysal 4.9.2 requires packaging>=22, but you have packaging 21.3 which is incompatible.
libpysal 4.9.2 requires scipy>=1.8, but you have scipy 1.7.3 which is incompatible.
libpysal 4.9.2 requires shapely>=2.0.1, but you have shapely 1.8.5.post1 which is incompatible.
momepy 0.6.0 requires shapely>=2, but you have shapely 1.8.5.post1 which is incompatible.
pointpats 2.4.0 requires scipy>=1.8, but you have scipy 1.7.3 which is incompatible.
pymc3 3.11.5 requires numpy<1.22.2,>=1.15.0, but you have numpy 1.22.4 which is incompatible.
raft-dask 23.8.0 requires dask==2023.7.1, but you have dask 2023.11.0 which is incompatible.
raft-dask 23.8.0 requires distributed==2023.7.1, but you have distributed 2023.11.0 which is incompatible.
scikit-image 0.21.0 requires scipy>=1.8, but you have scipy 1.7.3 which is incompatible.
spacy 3.7.2 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.
spglm 1.1.0 requires numpy>=1.23, but you have numpy 1.22.4 which is incompatible.
spglm 1.1.0 requires scipy>=1.8, but you have scipy 1.7.3 which is incompatible.
spreg 1.4.2 requires numpy>=1.23, but you have numpy 1.22.4 which is incompatible.
tensorflow 2.13.0 requires typing-extensions<4.6.0,>=3.6.6, but you have typing-extensions 4.12.2 which is incompatible.
tensorflow-probability 0.21.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.12.2 which is incompatible.
tensorflow-transform 0.14.0 requires protobuf<4,>=3.7, but you have protobuf 4.25.3 which is incompatible.
tensorflowjs 4.13.0 requires packaging~=23.1, but you have packaging 21.3 which is incompatible.
ultralytics 8.2.54 requires numpy<2.0.0,>=1.23.0, but you have numpy 1.22.4 which is incompatible.
woodwork 0.26.0 requires scipy>=1.10.0, but you have scipy 1.7.3 which is incompatible.
ydata-profiling 4.5.1 requires pydantic<2,>=1.8.1, but you have pydantic 2.4.2 which is incompatible.
Successfully installed numpy-1.22.4 scipy-1.7.3
scipy version: <module 'scipy.version' from '/opt/conda/lib/python3.10/site-packages/scipy/version.py'>
scipy.sparse and scipy.sparse.csc_matrix are available.
An import error occurred while importing scipy.sparse._csc: cannot import name '_csc' from 'scipy.sparse' (/opt/conda/lib/python3.10/site-packages/scipy/sparse/__init__.py)
Проверка завершена

На основе всех предыдущих сообщений из этого чата напишите пожалуйста полный исправленный код этой программы