umigv/UMARV-CV-ScenePerception

Write Benchmarking Script for YOLOv8 Model

Open

#1 opened on Oct 8, 2024

View on GitHub
 (0 comments) (0 reactions) (0 assignees)Jupyter Notebook (0 forks)auto 404
good first issue

Repository metrics

Stars
 (3 stars)
PR merge metrics
 (PR metrics pending)

Description

YOLOv8 model is still CV's best performing model on drivable area and potholes. So in order to be able to compare the YOLOv8 model and our custom PyTorch we need to measure the performance of our YOLO model on the same metrics we use for PyTorch performance.

Check out the segmentation-compare.py in the yolo_stack repo for a starting point.

Contributor guide

Research direction
Look at segmentation compare.py in the yolo stack repo and write a similar script to benchmark YOLOv8 using the same metrics as for PyTorch.
Tech stack
pythonpytorch
Domain
machine learningai
Issue type
Test
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
PythonPyTorch
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
60