Cvlib

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cvlib is an open-source Computer Vision library for Python, offering a simple, high-level interface for tasks like face, gender, and object detection. It's easy to use and install, requiring dependencies like OpenCV and TensorFlow.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is cvlib?

cvlib is a simple, high-level, and easy-to-use open-source Computer Vision library designed for Python developers. It provides straightforward functions for common computer vision tasks, including face detection, gender detection, and object detection using models like YOLOv4. The library is pip installable, with optional GPU support for enhanced performance, requiring pre-installed dependencies such as OpenCV and TensorFlow. cvlib also includes utility functions for video processing, such as extracting frames and creating GIFs. Its focus on ease of use makes complex computer vision tasks accessible with minimal code.

Best used for

Ideal for developers and machine learning engineers who need to quickly implement computer vision functionalities like face, gender, and object detection in Python applications. Especially valuable for those looking for an easy-to-use, high-level library with optional GPU acceleration for performance-critical tasks.

Common actions

detect faces

detect gender

detect objects

process video

create animations

automated workflowcollaborationopen-sourcelow-code/no-codedeepfake"AI Agents"face swappinggithub copilotworkflows

Capabilities

Key features

Face detection
Gender detection
Object detection
Video to frames
Create GIFs
GPU acceleration

Target Audience

developersdata scientistsstudentsresearchers

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the primary dependencies for cvlib?

cvlib primarily depends on OpenCV and TensorFlow. These packages need to be installed separately, either via pip or by compiling from source for specific hardware optimizations, especially for GPU usage.

Does cvlib support GPU acceleration?

Yes, cvlib supports GPU acceleration for tasks like face, gender, and object detection. To enable it, you need to install the tensorflow-gpu package and ensure you have the necessary Nvidia drivers (CUDA Toolkit, CuDNN) properly set up.

Can I use custom YOLO weights with cvlib?

Yes, cvlib allows you to run inference with custom trained YOLOv3/v4 weights. You can initialize a YOLO object with your custom weights, config, and labels, then use it to detect objects in your images.

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