Object Detection

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YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset

Overview

What is YOLOv4-Tiny

YOLOv4-tiny is the compressed version of YOLOv4 designed to train on machines that have less computing power. Its model weights are around 16 megabytes large, allowing it to train on 350 images in 1 hour when using a Tesla P100 GPU. YOLOv4-tiny has an inference speed of 3 ms on the Tesla P100, making it one of the fastest object detection models to exist.

YOLOv4-Tiny Architecture

YOLOv4-Tiny utilizes a couple of different changes from the original YOLOv4 network to help it achieve these fast speeds. First and foremost, The number of convolutional layers in the CSP backbone are compressed with a total of 29 pretrained convolutional layers. Additionally, the number of YOLO layers has been reduced to two instead of three and there are fewer anchor boxes for prediction.

YOLOv4 Results

YOLOv4-Tiny has comparatively competitive results with YOLOv4 given the size reduction. It achieves 40 mAP @.5 on the MS COCO dataset.

YOLOv4-Tiny Results

Further Reading over YOLOv4-Tiny

Training YOLOv4-tiny on Custom Data for Lightning Fast Object Detection: https://blog.roboflow.com/train-yolov4-tiny-on-custom-data-lighting-fast-detection/

Performance

Use This Model

Label Data Automatically with YOLOv4 Tiny

You can automatically label a dataset using YOLOv4 Tiny with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use YOLOv4 Tiny to train a computer vision model.

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Popular YOLOv4 Tiny Use Cases

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YOLOv4 Tiny Integrations

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Explore This Model on Roboflow

How to Train a YOLOv4 Tiny model and Use TensorFlow Lite

How to Train a YOLOv4 Tiny model and Use TensorFlow Lite

Using the state of the art YOLOv4 tiny Darknet model converted to TensorFlow Lite for on-device inference.

How to Train a YOLOv4 Tiny model and Use TensorFlow Lite

How to Train a YOLOv4 Tiny model and Use TensorFlow Lite

Using the state of the art YOLOv4 tiny Darknet model converted to TensorFlow Lite for on-device inference.

Train YOLOv4-tiny on Custom Data - Lightning Fast Object Detection

Train YOLOv4-tiny on Custom Data - Lightning Fast Object Detection

Train YOLOv4-tiny on Custom Data - Lightning Fast Object Detection

Train YOLOv4-tiny on Custom Data - Lightning Fast Object Detection

Data Augmentation in YOLOv4

Data Augmentation in YOLOv4

How to Train Scaled-YOLOv4 to Detect Custom Objects

How to Train Scaled-YOLOv4 to Detect Custom Objects

This blog is written to help you apply Scaled-YOLOv4 to your custom object detection task, to detect any object in the world, given the right training data.

A New Video Tutorial: YOLOv4 in PyTorch

A New Video Tutorial: YOLOv4 in PyTorch

YOLOv4 - Ten Tactics to Build a Better Model

YOLOv4 - Ten Tactics to Build a Better Model

The YOLO v4 repository is currently one of the best places to train a custom object detector, and the capabilities of the Darknet repository are vast. In this post, we discuss and implement ten advanced tactics in YOLO v4 so you can build the best object detection model from your custom dataset.

YOLOv4 - An explanation of how it works

YOLOv4 - An explanation of how it works

YOLOv4 outperforms other object detection models by a significant margin. Learn how it works.

How to Train YOLOv4 on a Custom Dataset

How to Train YOLOv4 on a Custom Dataset

In this tutorial, we walkthrough how to train YOLOv4 Darknet for state-of-the-art object detection on your own dataset.

PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques

PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques

Baidu publishes PP-YOLO and pushes the state of the art in object detection research by building on top of the PaddlePaddle deep learning framework.

Scaled-YOLOv4 is Now the Best Model for Object Detection

Scaled-YOLOv4 is Now the Best Model for Object Detection