OpenCV Reviews

Artifactory Reviews

OpenCV mentions (52)

• Essential Deep Learning Checklist: Best Practices Unveiled

  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

• FridgeBot — GPT-4o shopping list automation

  Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / about 1 month ago

• Exploring Open-Source Alternatives to Landing AI for Robust MLOps

  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

• Looking for a Windows auto-clicker with conditions

  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

• Looking to recreate a cool AI assistant project with free tools

  - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago

Artifactory mentions (20)

• Where to store executables shared by a team/project

  I kind of hate it, but Artifactory seems popular at companies: https://jfrog.com/artifactory/. Source: 12 months ago

• Adding Virtual Environments to Git Repo

  When not providing all dependencies yourself, you might suffer from people deleting the packages you depend on (IMHO a very rare scenario). If it is really that critical (hint: usually it isn't), create a local mirror of Pypi (full or only the packages you need). Devpi, Artifactory, etc. Can do that or you just dump the necessary files into Cloud storage, so you have a backup. Source: about 1 year ago

• Authenticated Docker Hub image pulls in Kubernetes

  Operate a pull-through cache registry, like Artifactory or the open source reference Docker registry. This will allow you to pull images from Docker Hub less frequently, improving your chances of staying under the anonymous usage limit. - Source: dev.to / about 1 year ago

• Concretely, how do you trust the experts? That is, how do you a) identify experts relevant to something and b) determine if they have a consensus (and if so, what it is) on a given topic?

  Like suppose for a second that . . . Idk . . . a product team wants our ci workflows to start using Artifactory. Okay great, I don't know Artifactory integration but I'm going to tell them "Sure, I'll get right on that.". Source: over 1 year ago

• What do I do with large "asset" files?

  If these "assets" have an independent release schedule I would treat them separately (especially if they are externally provided). If they are not built from source then treat them as artefacts, they don't belong in git. You can store the in an artefact repository (like Artifactory of Nexus) or (as u/nekokattt points out) in something like S3. Source: over 1 year ago