### OpenCV Installation Stuck at Solving Environment When encountering the issue where the installation of OpenCV gets stuck at 'Solving environment', it is often due to conflicts or inefficiencies within the Conda package manager when resolving dependencies[^1]. The following factors may contribute: - Insufficient system resources, such as memory or CPU power. - Outdated versions of `conda` that struggle with complex dependency graphs. - Conflicting packages already present in your current conda environment. To address this problem effectively, consider implementing one or more of these strategies: #### Update Conda Ensure you are using an up-to-date version of Conda since newer releases include performance improvements and bug fixes related to dependency resolution. Use the command below to update Conda: ```bash conda update conda ``` #### Create a New Environment Creating a fresh environment minimizes interference from existing packages which might complicate the solver's task: ```bash conda create -n opencv_env python=3.9 conda activate opencv_env ``` #### Simplify Dependency Specifications Instead of allowing Conda to solve all possible combinations, specify exact versions for key libraries like Python itself during creation: ```bash conda install opencv ``` Alternatively, use pre-built binaries via pip after activating your new environment if direct Conda methods still fail: ```bash pip install opencv-python ``` #### Increase Verbosity for Debugging Insights If problems persist despite trying above solutions, increasing verbosity can provide deeper insights into what exactly causes delays: ```bash CONDA_VERBOSITY=3 conda install opencv ``` By combining these approaches tailored according to specific circumstances surrounding each unique case encountered while setting up environments containing OpenCV, users should be able resolve issues efficiently without getting stalled indefinitely on 'solving environment'. ```python import cv2 print(cv2.__version__) ```