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TCLResearchEurope/
yolov8n_pruned_43

Name: yolov8n_pruned_43
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Model Card for yolov8n_pruned_43

This is a prunned version of the YOLOv8n model in a toch-dag format.

This model has rougly 43% of the original model FLOPs with small metrics drop.

Model	KMAPPs*	M Parameters	mAP50-95 (640x640)
YOLOv8n (baseline)	21.5	3.16	37.3
yolov8n_pruned_43 (ours)	9.2 (43%)	1.2 (38%)	29.9 (↓ 7.4)

*KMAPPs thousands of FLOPs per input pixel

KMAPPs(model) = FLOPs(model) / (H * W * 1000), where (H, W) is the input resolution.

The accuracy was calculated on the COCO val2017 dataset. For details about image pre-processing, please refer to the original repository.

Model Details

Model Description

Developed by: TCL Research Europe
Model type: Object detection
License: Apache 2.0
Finetuned from model: YOLOv8n

Model Sources

Repository: YOLOv8n

How to Get Started with the Model

To load the model, You have to install torch-dag library, which can be done using pip by

pip install torch-dag

then, clone this repository

# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co/TCLResearchEurope/yolov8n_pruned_43

and now You are ready to load the model:

import torch_dag
import torch

model = torch_dag.io.load_dag_from_path('./yolov8n_pruned_43')

model.eval()
out = model(torch.ones(1, 3, 224, 224))
print(out.shape)