1. Create a python virtual environment
First select the file to configure the environment
as follows:
Enter cmd here and press Enter
Here I create an environment named hands3dtext, the environment version is the initial environment of 3.7.2
conda create -n hands3dtext python==3.7.2
The creation is successful as follows:
2. Configure the just created virtual environment
First activate the just created virtual environment
conda activate hands3dtext
As shown above, the parentheses in front of it indicate successful activation, and you are in the virtual environment at this time.
You can then install all the required packages and libraries
Be sure to confirm whether to install the cpu or gpu version before installation.
Here I need to install mediapipe
Note: To install mediapipe, first install opencv, and execute the terminal
conda install opencv-contrib-python
The previous article may be wrong, you can use the following domestic Tsinghua mirror source
pip install opencv-python -i https://pypi.tuna.tsinghua.edu.cn/simple
Then Install mediapipe, execute the terminal
conda install mediapipe
I also need to install the tqdm module (according to personal needs)
conda install tqdm
If you feel that the installation is too slow, you can switch to the domestic mirror source for installation and execute the following command
conda config --remove-key channels conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/main/ conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/ conda config --add channels https://mirrors.bfsu.edu.cn/anaconda/cloud/pytorch/ conda config --set show_channel_urls yes pip config set global.index-url https://mirrors.ustc.edu.cn/pypi/web/simple
pytorch installation (gpu version and cpu version installation)
For specific steps of GPU version installation, please refer to this article: Installing the GPU version of Tensorflow and Pytorch under Windows in 2021_dejahu's blog-CSDN blog
You need to pay attention to the following points:
1. Be sure to update your graphics card driver before installation. Go to the official website to download the driver installation of the corresponding model.
2. 30 series graphics cards can only be used. cuda11 version
3. Be sure to create a virtual environment so that there is no conflict between the deep learning frameworks
conda install pytorch==1.8.0 torchvision torchaudio cudatoolkit=10.2 # 注意这条命令指定Pytorch的版本和cuda的版本 conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cpuonly # CPU的小伙伴直接执行这条命令即可
Installation of pycocotools
pip install pycocotools-windows
Installation of other packages
pip install -r requirements.txt pip install pyqt5 pip install labelme
3. Configure the virtual environment to the corresponding project
First open the corresponding project and follow the icon guidance to find the newly created virtual environment
Click OK. Wait for the configuration to be completed
The above is the detailed content of How to configure python virtual environment with conda. For more information, please follow other related articles on the PHP Chinese website!
Python's Execution Model: Compiled, Interpreted, or Both?May 10, 2025 am 12:04 AMPythonisbothcompiledandinterpreted.WhenyourunaPythonscript,itisfirstcompiledintobytecode,whichisthenexecutedbythePythonVirtualMachine(PVM).Thishybridapproachallowsforplatform-independentcodebutcanbeslowerthannativemachinecodeexecution.
Is Python executed line by line?May 10, 2025 am 12:03 AMPython is not strictly line-by-line execution, but is optimized and conditional execution based on the interpreter mechanism. The interpreter converts the code to bytecode, executed by the PVM, and may precompile constant expressions or optimize loops. Understanding these mechanisms helps optimize code and improve efficiency.
What are the alternatives to concatenate two lists in Python?May 09, 2025 am 12:16 AMThere are many methods to connect two lists in Python: 1. Use operators, which are simple but inefficient in large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use the = operator, which is both efficient and readable; 4. Use itertools.chain function, which is memory efficient but requires additional import; 5. Use list parsing, which is elegant but may be too complex. The selection method should be based on the code context and requirements.
Python: Efficient Ways to Merge Two ListsMay 09, 2025 am 12:15 AMThere are many ways to merge Python lists: 1. Use operators, which are simple but not memory efficient for large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use itertools.chain, which is suitable for large data sets; 4. Use * operator, merge small to medium-sized lists in one line of code; 5. Use numpy.concatenate, which is suitable for large data sets and scenarios with high performance requirements; 6. Use append method, which is suitable for small lists but is inefficient. When selecting a method, you need to consider the list size and application scenarios.
Compiled vs Interpreted Languages: pros and consMay 09, 2025 am 12:06 AMCompiledlanguagesofferspeedandsecurity,whileinterpretedlanguagesprovideeaseofuseandportability.1)CompiledlanguageslikeC arefasterandsecurebuthavelongerdevelopmentcyclesandplatformdependency.2)InterpretedlanguageslikePythonareeasiertouseandmoreportab
Python: For and While Loops, the most complete guideMay 09, 2025 am 12:05 AMIn Python, a for loop is used to traverse iterable objects, and a while loop is used to perform operations repeatedly when the condition is satisfied. 1) For loop example: traverse the list and print the elements. 2) While loop example: guess the number game until you guess it right. Mastering cycle principles and optimization techniques can improve code efficiency and reliability.
Python concatenate lists into a stringMay 09, 2025 am 12:02 AMTo concatenate a list into a string, using the join() method in Python is the best choice. 1) Use the join() method to concatenate the list elements into a string, such as ''.join(my_list). 2) For a list containing numbers, convert map(str, numbers) into a string before concatenating. 3) You can use generator expressions for complex formatting, such as ','.join(f'({fruit})'forfruitinfruits). 4) When processing mixed data types, use map(str, mixed_list) to ensure that all elements can be converted into strings. 5) For large lists, use ''.join(large_li
Python's Hybrid Approach: Compilation and Interpretation CombinedMay 08, 2025 am 12:16 AMPythonusesahybridapproach,combiningcompilationtobytecodeandinterpretation.1)Codeiscompiledtoplatform-independentbytecode.2)BytecodeisinterpretedbythePythonVirtualMachine,enhancingefficiencyandportability.
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.
Atom editor mac version download
The most popular open source editor
