OpenCV Reviews

gRPC 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 / 18 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

gRPC mentions (92)

• Performance and Scalability for Database-Backed Applications

  We can take the previously mentioned idea of partitioning the database further by breaking up an application into multiple applications, each with its own database. In this case each application will communicate with the others via something like REST, RPC (e.g. gRPC), or a message queue (e.g. Redis, Kafka, or RabbitMQ). - Source: dev.to / 23 days ago

• Text-based language processing enhanced with AI/ML

  Aside from the obvious differences in client library nomenclature and use of different credentials, API usage is fairly similar. Not visually obvious is that the older platform client library calls the REST versions of the GCP APIs whereas the newer product client libraries call the gRPC versions which generally perform better... Yet another reason why the product client libraries are always recommended. - Source: dev.to / 8 days ago

• Fastly and the Linux kernel

  The open source projects Fastly uses and the foundations we partner with are vital to Fastly’s mission and success. Here's an unscientific list of projects and organizations supported by the Linux Foundation that we use and love include: The Linux Kernel, Kubernetes, containerd, eBPF, Falco, OpenAPI Initiative, ESLint, Express, Fastify, Lodash, Mocha, Node.js, Prometheus, Jenkins, OpenTelemetry, Envoy, etcd, Helm,... - Source: dev.to / 13 days ago

• Best Practices for Building Microservices with NestJS

  Choose a consistent communication protocol for inter-service communication. Common protocols include HTTP, gRPC, and message brokers like RabbitMQ or Kafka. NestJS supports various communication strategies, allowing you to choose the one that best fits your needs. - Source: dev.to / 26 days ago

• Why Did Google Choose To Implement gRPC Using HTTP/2?

  gRPC is an open-source high-performance RPC framework developed by Google. The design goal of gRPC is to run in any environment, supporting pluggable load balancing, tracing, health checking, and authentication. It not only supports service calls within and across data centers but is also suitable for the last mile of distributed computing, connecting devices, mobile applications, and browsers to backend services.... - Source: dev.to / about 1 month ago