diff --git a/website/public/favicon.svg b/website/public/favicon.svg deleted file mode 100644 index 6893eb1..0000000 --- a/website/public/favicon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/website/public/icons.svg b/website/public/icons.svg deleted file mode 100644 index e952219..0000000 --- a/website/public/icons.svg +++ /dev/null @@ -1,24 +0,0 @@ - diff --git a/website/public/yolo.jfif b/website/public/yolo.jfif new file mode 100644 index 0000000..6bf9693 Binary files /dev/null and b/website/public/yolo.jfif differ diff --git a/website/src/App.jsx b/website/src/App.jsx index 1f77a6c..f29971e 100644 --- a/website/src/App.jsx +++ b/website/src/App.jsx @@ -1,8 +1,5 @@ import { useState } from 'react' import { BrowserRouter as Router, Routes, Route, Navigate } from "react-router-dom"; -import reactLogo from './assets/react.svg' -import viteLogo from './assets/vite.svg' -import heroImg from './assets/hero.png' import './App.css' import Menu from './Menu' import Homepage from './Homepage'; diff --git a/website/src/Object_Detection.jsx b/website/src/Object_Detection.jsx index a151319..f4b85cd 100644 --- a/website/src/Object_Detection.jsx +++ b/website/src/Object_Detection.jsx @@ -97,7 +97,7 @@ function Object_Detection() { if (!ctx) return; const img = new Image(); - img.src = "/cherry_bird.jpeg"; + img.src = "/yolo.jfif"; const canvas = canvasRefBBox.current; @@ -139,8 +139,8 @@ function Object_Detection() { sendImage(); } socket.onmessage = (event) => { - drawBBox(); bboxes.current = JSON.parse(event.data).bboxes; + drawBBox(); sendImage(); } socket.onerror = console.error; @@ -166,11 +166,17 @@ function Object_Detection() { {running? "End Detection" : "Start Detection"} -
+ This Project is an implementation of the YOLO (You Only Look Once) algorithm. It was implemented with Pytorch and trained on a Dataset from Roboflow. +
+