70 lines
2.3 KiB
HTML
70 lines
2.3 KiB
HTML
<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>YOLOv8 Object Detection</title>
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<style>
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canvas {
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display:block;
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border: 1px solid black;
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margin-top:10px;
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}
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</style>
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</head>
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<body>
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<input id="uploadInput" type="file"/>
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<canvas></canvas>
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<script>
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/**
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* "Upload" button onClick handler: uploads selected
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* image file to backend, receives an array of
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* detected objects and draws them on top of image
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*/
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const input = document.getElementById("uploadInput");
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input.addEventListener("change",async(event) => {
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const file = event.target.files[0];
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const data = new FormData();
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data.append("image_file",file,"image_file");
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const response = await fetch("/detect",{
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method:"post",
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body:data
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});
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const boxes = await response.json();
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draw_image_and_boxes(file,boxes);
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})
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/**
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* Function draws the image from provided file
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* and bounding boxes of detected objects on
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* top of the image
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* @param file Uploaded file object
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* @param boxes Array of bounding boxes in format
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[[x1,y1,x2,y2,object_type,probability],...]
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*/
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function draw_image_and_boxes(file,boxes) {
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const img = new Image()
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img.src = URL.createObjectURL(file);
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img.onload = () => {
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const canvas = document.querySelector("canvas");
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canvas.width = img.width;
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canvas.height = img.height;
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const ctx = canvas.getContext("2d");
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ctx.drawImage(img,0,0);
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ctx.strokeStyle = "#00FF00";
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ctx.lineWidth = 5;
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ctx.font = "20px serif";
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boxes.forEach(([x1,y1,x2,y2,object_type, prob]) => {
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const label = `${object_type} ${prob.toFixed(2)}`;
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ctx.strokeRect(x1,y1,x2-x1,y2-y1);
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ctx.fillStyle = "#00ff00";
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const width = ctx.measureText(label).width;
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ctx.fillRect(x1,y1,width+10,25);
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ctx.fillStyle = "#000000";
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ctx.fillText(label,x1,y1+18);
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});
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}
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}
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</script>
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</body>
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</html> |