Lors de la création de l'image docker de l'environnement d'apprentissage automatique, j'ai installé paddlehub et la dépendance de paddlehub est opencv-python. Lors de son utilisation, l'erreur est signalée comme suit :
Traceback (most recent call last):
File "woodpecker/etl_main.py", line 2, in <module>
from etl import etl_paper_html, tl_paper_paragraph_label, tl_model_inputs
File "/ws/woodpecker/etl/tl_paper_paragraph_label.py", line 13, in <module>
from bai.project_common.woodpecker.preprocess import (
File "<frozen zipimport>", line 259, in load_module
File "/usr/local/lib/python3.8/site-packages/bai-0.3.0-py3.8.egg/bai/project_common/woodpecker/preprocess.py", line 4, in <module>
File "<frozen zipimport>", line 259, in load_module
File "/usr/local/lib/python3.8/site-packages/bai-0.3.0-py3.8.egg/bai/feature_extraction/text/__init__.py", line 4, in <module>
File "/usr/local/lib/python3.8/site-packages/paddlehub/__init__.py", line 31, in <module>
from paddlehub import datasets
File "/usr/local/lib/python3.8/site-packages/paddlehub/datasets/__init__.py", line 15, in <module>
from paddlehub.datasets.canvas import Canvas
File "/usr/local/lib/python3.8/site-packages/paddlehub/datasets/canvas.py", line 23, in <module>
from paddlehub.vision.utils import get_img_file
File "/usr/local/lib/python3.8/site-packages/paddlehub/vision/utils.py", line 18, in <module>
import cv2
File "/usr/local/lib/python3.8/site-packages/cv2/__init__.py", line 8, in <module>
from .cv2 import *
ImportError: libGL.so.1: cannot open shared object file: No such file or directory
Il s'agit d'une erreur lors de l'importation d'opencv. Après recherche, j'ai trouvé que le document opencv-python fournit 4 packages d'installation. Ma compréhension est la suivante :
| Noms des packages | Environnement applicable | illustrer |
|---|---|---|
| opencv-python | Environnements de bureau tels que Windows, macOS, GNU/Linux | Contient des modules de base |
| opencv-contrib-python | Environnements de bureau tels que Windows, macOS, GNU/Linux | contient tous les modules |
| opencv-python-sans tête | Environnement serveur, pas de dépendances à la bibliothèque GUI, comme Docker, environnement cloud | Contient des modules de base |
| opencv-contrib-python-sans tête | Environnement serveur, pas de dépendances à la bibliothèque GUI, comme Docker, environnement cloud | contient tous les modules |
Un seul de ces quatre packages peut être sélectionné pour l'installation. paddlehub dépend d'opencv-python. Lors de la création d'une image docker, remplacez-la simplement par opencv-python-headless.
Le texte original d'opencv-python est le suivant :
Select the correct package for your environment:
There are four different packages (see options 1, 2, 3 and 4 below) and you should SELECT ONLY ONE OF THEM. Do not install multiple different packages in the same environment. There is no plugin architecture: all the packages use the same namespace (cv2). If you installed multiple different packages in the same environment, uninstall them all with pip uninstall and reinstall only one package.
a. Packages for standard desktop environments (Windows, macOS, almost any GNU/Linux distribution)
Option 1 - Main modules package: pip install opencv-python
Option 2 - Full package (contains both main modules and contrib/extra modules): pip install opencv-contrib-python (check contrib/extra modules listing from OpenCV documentation)
b. Packages for server (headless) environments (such as Docker, cloud environments etc.), no GUI library dependencies
These packages are smaller than the two other packages above because they do not contain any GUI functionality (not compiled with Qt / other GUI components). This means that the packages avoid a heavy dependency chain to X11 libraries and you will have for example smaller Docker images as a result. You should always use these packages if you do not use cv2.imshow et al. or you are using some other package (such as PyQt) than OpenCV to create your GUI.
Option 3 - Headless main modules package: pip install opencv-python-headless
Option 4 - Headless full package (contains both main modules and contrib/extra modules): pip install opencv-contrib-python-headless (check contrib/extra modules listing from OpenCV documentation)