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Based on our record, OpenCV should be more popular than CloudShell. It has been mentiond 52 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Gcloud/command-line - Finally, for those more inclined to using the command-line, you can enable APIs with a single command in the Cloud Shell or locally on your computer if you installed the Cloud SDK (which includes the gcloud command-line tool [CLI]) and initialized its use. If this is you, issue the following command to enable all three APIs: gcloud services enable geocoding-backend.googleapis.com... - Source: dev.to / about 1 month ago
While you might find that using the Google Cloud online console or Cloud Shell environment meets your occasional needs, for maximum developer efficiency you will want to install the Google Cloud CLI (gcloud) on your own system where you already have your favorite editor or IDE and git set up. - Source: dev.to / over 1 year ago
Here is the product https://cloud.google.com/shell It has a quick start guide and docs. - Source: Hacker News / over 1 year ago
If you are worried about creating other accounts etc - you can just use your gmail account with https://cloud.google.com/shell and that gives you a very small vm and a coding environment (replit or colab are way better than this though). Source: over 2 years ago
One workaround...launch a Google cloud shell from a personal google account and try the ssh toy from there. It's free. https://cloud.google.com/shell. - Source: Hacker News / over 2 years ago
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 13 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / about 1 month ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 7 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 7 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago
GitHub Codespaces - GItHub Codespaces is a hosted remote coding environment by GitHub based on Visual Studio Codespaces integrated directly for GitHub.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Dirigible - Dirigible is a cloud development toolkit providing both development tools and runtime environment.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
CodeTasty - CodeTasty is a programming platform for developers in the cloud.
NumPy - NumPy is the fundamental package for scientific computing with Python