metadata

title: S15
emoji: 🐨
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 4.28.0
app_file: app.py
pinned: false
license: mit

Inference of Vehicle detection using Yolov9

This application showcases the inference capabilities of a Yolo v9 trained on the vehicle dataset from kaggle. Vehicle Dataset Repo Link
The model is trained on 6 classes:
- car
- threewheel
- bus
- truck
- motorbike
- van
The architecture is based on Yolo v9 papar https://arxiv.org/abs/2402.13616 and model is trained using https://github.com/WongKinYiu/yolov9.git
detect.py file used for inference.
From gradio applicaiton call is made to detect.py using command line shell with unique folder name passed as argument
After processing, image/video is picked from same location.

Mentioned below is the link for Training Repository Training Repo Link

Post training process, the model is saved locally and then uploaded to Gradio Spaces.
Attached below is the link to download model file
This app has two features :
Video Prediction: " - This feature will allow detection of moving vehicles in the the video
Image Prediction:
- This feature will allow detection of vehicle in the the image

Usage:

Video Prediction: " - Upload video file and detect vehicles present in the video.
- Inferencing is done using CPU therefore it takes more time.
Image Prediction:
- Upload image file and detect vehicles present in the image.

Thank you