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Based on our record, OpenCV should be more popular than Liberapay. 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.
Reminder that librapay exists, and their developers are only paid from user donations, just like anyone else on the platform. https://liberapay.com/ (I only wish their CC costs could be reduced a bit to make micropayments viable). - Source: Hacker News / 2 months ago
I don't think they want your money, not unless you are an enterprise costumer. But feel free to donate to another open source project: https://liberapay.com/. - Source: Hacker News / over 1 year ago
I often see links to Liberapay and Open Collective (Liberapay even has an official Mastodon account). Source: over 1 year ago
It seems a little suspicious that the person sharing those posts isn't building an open platform himself -- why not make it more open /u/paydevs ? I think Liberapay is a great way to spontaneously pay OSS developers. I'm not opposed to paydevs.com (as far as they're showing), but I encourage increasing transparency and openness, as is I don't feel confident supporting the platform. I think individuals, governments... Source: over 1 year ago
This doesn't seem to mention liberapay (and patreon which funds developers directly. Source: over 1 year 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 / 23 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / about 2 months 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
Patreon - Patreon enables fans to give ongoing support to their favorite creators.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Ko-fi - Ko-fi offers a friendly way for content creators to get paid for their work.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Buy Me A Coffee - A free, fast and friendly way to accept donations 💰
NumPy - NumPy is the fundamental package for scientific computing with Python