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3dc1bcf466
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 LABS\s478989
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3dc1bcf466 | |
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LABS\s478989
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d8ac8c32a5 |
205
index.html
205
index.html
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@ -2,69 +2,168 @@
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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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<title>TomAIto</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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display: flex;
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flex-direction: column;
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max-width: 300px; /* Ustaw maksymalną szerokość formularza */
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margin: auto; /* Centruj formularz na stronie */
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margin-top: 10px;
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}
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#weatherInfo {
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display: flex;
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flex-direction: column;
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max-width: 300px; /* Ustaw maksymalną szerokość formularza */
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margin: auto; /* Centruj formularz na stronie */
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margin-top: 10px;
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}
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form {
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display: flex;
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flex-direction: column;
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max-width: 300px; /* Ustaw maksymalną szerokość formularza */
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margin: auto; /* Centruj formularz na stronie */
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}
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label {
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margin-top: 10px;
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}
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button {
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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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<form id="uploadForm">
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<label for="cropType">Crop Type:</label>
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<select id="cropType" name="cropType">
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<option value="external">External</option>
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<option value="internal">Internal</option>
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<option value="greenhouse">Greenhouse</option>
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</select>
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<label for="location">Location:</label>
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<input type="text" id="location" name="location" required/>
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<label for="variety">Variety:</label>
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<input type="text" id="variety" name="variety" required/>
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<label for="uploadInput">Choose an image:</label>
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<input id="uploadInput" type="file" required/>
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<button type="Sprawdz">Sprawdz</button>
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</form>
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<canvas></canvas>
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<div id="weatherInfo"></div>
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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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const form = document.getElementById("uploadForm");
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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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form.addEventListener("submit", async (event) => {
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event.preventDefault();
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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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const fileInput = document.getElementById("uploadInput");
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const cropTypeInput = document.getElementById("cropType");
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const locationInput = document.getElementById("location");
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const varietyInput = document.getElementById("variety");
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const file = fileInput.files[0];
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const data = new FormData();
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data.append("image_file", file);
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data.append("cropType", cropTypeInput.value);
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data.append("location", locationInput.value);
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data.append("variety", varietyInput.value);
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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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const location = locationInput.value;
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if (cropTypeInput.value == "external") {
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getWeather(location);
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}
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else {
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const randomTips = [
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"water your tomatoes every day.",
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"keep the temperature between 20-25 degrees Celsius.",
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"place the tomatoes in sunlight."];
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const randomTip = randomTips[Math.floor(Math.random() * randomTips.length)];
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document.getElementById("weatherInfo").innerText = "TIP! To maximalize your yields " + randomTip;
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}
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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} ${prob.toFixed(2)}`;
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ctx.strokeRect(x1, y1, x2 - x1, y2 - y1);
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ctx.fillStyle = "#00ff00";
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const width = ctx.measureText(label).width;
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ctx.fillRect(x1, y1, width + 10, 25);
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ctx.fillStyle = "#000000";
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ctx.fillText(label, x1, y1 + 18);
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});
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}
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}
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async function getWeather(location) {
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const apiKey = "1fc6a52c96331d035a828cc0c1606241";
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const apiUrl = `https://api.openweathermap.org/data/2.5/weather?q=${location}&appid=${apiKey}`;
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try {
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const weatherResponse = await fetch(apiUrl);
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const weatherData = await weatherResponse.json();
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if (weatherData.main && weatherData.main.temp) {
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const temperatureKelvin = weatherData.main.temp;
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const temperatureCelsius = temperatureKelvin - 273.15;
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const tempRound = Math.round(temperatureCelsius);
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const weatherCondition = weatherData.weather[0].main;
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const isRaining = weatherCondition === 'Rain';
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let additionalInfo = `${isRaining ? 'Rain is expected in your town today, so you dont have to water your tomatoes' :
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'No rainfall is expected in the city today, so you need to water your tomatoes!'} Temperature in ${location} is ${tempRound} °C.`;
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if (tempRound < 15) {
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additionalInfo += ' So you need to cover your tomatoes!';
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}
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document.getElementById("weatherInfo").innerText = additionalInfo;
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} else {
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document.getElementById("weatherInfo").innerText = "Unable to fetch weather data.";
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}
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} catch (error) {
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console.error("Error fetching weather data:", error);
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document.getElementById("weatherInfo").innerText = "Error fetching weather data.";
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}
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}
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</script>
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</body>
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</html>
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@ -4,6 +4,7 @@ from waitress import serve
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from PIL import Image
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import onnxruntime as ort
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import numpy as np
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import requests
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#my changes
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import os
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@ -24,6 +25,7 @@ yolo_classes = ["b_fully_ripened",
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app = Flask(__name__)
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@app.route("/")
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def root():
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"""
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@ -33,22 +35,18 @@ def root():
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with open("index.html") as file:
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return file.read()
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@app.route("/detect", methods=["POST"])
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def detect():
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"""
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Handler of /detect POST endpoint
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Receives uploaded file with a name "image_file", passes it
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through YOLOv8 object detection network and returns and array
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of bounding boxes.
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:return: a JSON array of objects bounding boxes in format [[x1,y1,x2,y2,object_type,probability],..]
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"""
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buf = request.files["image_file"]
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crop_type = request.form.get("cropType")
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location = request.form.get("location")
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variety = request.form.get("variety")
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boxes, orientation = detect_objects_on_image(buf.stream)
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#print(boxes)
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#print(orientation)
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# Do something with crop_type, location, and variety here (e.g., store in database)
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return jsonify(boxes)
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def detect_objects_on_image(buf):
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input, img_width, img_height = prepare_input(buf)
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output = run_model(input)
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