Pytorch-Yolo-V3

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pytorch-yolo-v3 is an Open Source & Models tool that provides a PyTorch implementation of the YOLO v3 object detection algorithm. It enables real-time object detection in images and videos.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is pytorch-yolo-v3?

pytorch-yolo-v3 offers a PyTorch implementation of the YOLO v3 object detection algorithm, designed for efficient and real-time object recognition. This repository aims to improve upon existing ports by streamlining the code, removing redundant components, and providing clear documentation. It currently supports detection in single images, multiple images, and video streams, with options to adjust resolution and utilize half-precision floats for faster inference. The project serves as a driver code for research, with plans to include a training module in the future. It requires Python 3.5, OpenCV, and PyTorch 0.4.

Best used for

Ideal for AI researchers and developers who need to implement and experiment with the YOLO v3 object detection algorithm, detect objects in images and videos, and integrate real-time object recognition into their projects. Especially valuable for those seeking a streamlined and well-documented PyTorch-based solution.

Common actions

implement object detection

detect objects in images

detect objects in videos

experiment with YOLO

open-sourceworkflows"AI Agents"deepfakeautomated workflowgithub copilotface swappinglow-code/no-codecollaboration

Capabilities

Key features

YOLO v3 implementation
Object detection
Image processing
Video processing
Adjustable resolution
Half-precision inference

Target Audience

professordeveloperresearcher

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the system requirements for pytorch-yolo-v3?

To run pytorch-yolo-v3, you will need Python 3.5, OpenCV, and PyTorch 0.4. Using PyTorch 0.3 will cause the detector to break. Ensure these dependencies are met for proper functionality.

Can pytorch-yolo-v3 detect objects in videos?

Yes, pytorch-yolo-v3 supports object detection in video files. You can use the `video_demo.py` script with the `--video` flag, specifying an .avi format video file. There's also `video_demo_half.py` for faster inference with 16-bit half-precision floats.

How can I adjust the input image resolution for detection?

You can change the resolution of the input image using the `--reso` flag when running `detect.py`. The chosen value must be a multiple of 32 and greater than 32 to avoid unexpected behavior. The default resolution is 416.

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Research & Education › Academic Research Data & Analytics › Data Labeling & Annotation

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