TrashDetection_Dev.js

import SimulatorPlugins from "./reusable/SimulatorPlugins.js"
import StatusTable from "./reusable/StatusTable.js"
import MobileNotifications from "./reusable/MobileNotifications.js"
import { PLUGINS_APIKEY } from "./reusable/apikey.js"
import GoogleMapsLocation from "./reusable/GoogleMapsLocation.js"

async function fetchRowsFromSpreadsheet(spreadsheetId, apiKey) {
    // Set the range to A1:Z1000
    const range = "A1:Z1000";

    // Fetch the rows from the Google Spreadsheet API
    const response = await fetch(
        `https://sheets.googleapis.com/v4/spreadsheets/${spreadsheetId}/values/${range}?key=${encodeURIComponent(apiKey)}`
    );
    const json = await response.json();
    // Get the headers from the first row
    const headers = json.values[0];
    // Convert the remaining rows to an array of objects
    const rows = json.values.slice(1).map(row => {
        const rowObject = {};
        for (let i = 0; i < row.length; i++) {
            rowObject[headers[i]] = row[i];
        }
        return rowObject;
    });

    return rows;
}

const plugin = ({widgets, simulator, vehicle}) => {

    let simInterval = null

    const loadSpreadSheet = async () => {
        let sheetID = "1KopET4hpEUQqswqvBP1Nx2xljYE7Ws-6kRqH1rxGJv4";
        fetchRowsFromSpreadsheet(sheetID, PLUGINS_APIKEY)
        .then((rows) => {
            SimulatorPlugins(rows, simulator)
        })
    }

    widgets.register("Table",
    StatusTable({
        apis:["Vehicle.Connectivity.IsConnectivityAvailable","Vehicle.IsMoving", "Vehicle.Cabin.Seat.Row1.Pos1.IsOccupied", "Vehicle.CurrentLocation.Latitude", "Vehicle.CurrentLocation.Longitude"],
        vehicle: vehicle,
        refresh: 800         
    }))

    let setLocationGlobal = null;
	widgets.register("Map", (box) => {
		const initialLocation = {
            "lat": 46.477127,
            "lng": 10.367829
		}
        GoogleMapsLocation(PLUGINS_APIKEY, box, initialLocation).then(({setLocation}) => {
			setLocationGlobal = setLocation
		})
	})

//   let container = null

//   let resultImgDiv = null
//   let resultRecDiv = null

//   let imgWidth = 0;
 //  let imgHeight = 0;

//widgets.register("Result", (box) => {
 //  const container = document.createElement('div');
 //  container.innerHTML = `
 //       <div style="width: 50%; height: 50%; position: relative;">
  //          <div id="resultRec" style="position: absolute; border: 2px solid red; top: 0; left: 0; width: 0; height: 0; z-index: 2;"></div>
  //          <img id="resultImg" style="position: absolute; top: 50%; left: 50%; transform: translate(-50%, -50%); max-width: 100%; max-height: 100%; z-index: 1;"
  //              src="https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2FLanding_AI_Logo_RGB_600.png?alt=media&token=9f6e445d-cf6d-4556-9240-4645a804b240"/> 
  //      </div>
  //  `;
 //   const resultImgDiv = container.querySelector("#resultImg");
  //  const resultRecDiv = container.querySelector("#resultRec");
 //   box.injectNode(container);
//});

let container = null

    let resultImgDiv = null
    let resultRecDiv = null

    let landingAiLogo = `https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2FAIOT_LAB_Logo_RGB_RZ.jpg?alt=media&token=f12df497-6f0b-4549-ac8b-c006de5d06d1`

    let imgWidth = 0;
    let imgHeight = 0;

    widgets.register("Resultnew", (box) => {
        const container = document.createElement('div');
        container.innerHTML = `
            <div style="width:100%;height:100%; position: relative;">
                <div id="resultRec" 
                    style="position:absolute;border: 2px solid red; top: 0; left: 0; width: 0; height: 0; z-index: 2;">
                </div>
                <img id="resultImg" 
                    style="display:block;position:absolute;top:0%;left:0%;width:100%;height:100%; z-index: 1;"
                    src="https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2F2023-05-18_17h11_11.png?alt=media&token=81335e79-b793-4c81-ad40-1e6dc4d93f54"/> 
                <img id="logoImg" 
                    style="position:absolute;top:5%;right:5%;width:30%;padding:6px; z-index: 3;object-fit:contain;background:white;"
                    src="${landingAiLogo}"/> 
            </div>
        `;
        resultImgDiv = container.querySelector("#resultImg");
        resultRecDiv = container.querySelector("#resultRec");
        box.injectNode(container);
    });		

widgets.register("InputImage", (box) => {
        container = document.createElement('div')
        container.innerHTML = 
        `
        <div id="image" style="display:block;z-index:1;">
            <img id="output" width="100%" height="100%" 
                src="https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2F0000.JPG?alt=media&token=4e2bb785-846f-4ee1-8774-0a101b473bca"/>
        </div>
        <div class="btn btn-color" 
            style="display:flex;z-index:2; position:absolute; width: 100%; bottom: 10px; opacity:85%; align-items:center; align-content:center; flex-direction:row; justify-content:center">
            <button id="upload-btn" 
                style="background-color: rgb(104 130 158);padding: 10px 24px;cursor: pointer;float: left;margin:2px;border-radius:5px;font-size:1em;font-family:Lato;color: rgb(255, 255, 227);border:0px">
                Upload
            </button>
            <button id="submit-btn" 
                style="background-color: rgb(104 130 158);padding: 10px 24px;cursor: pointer;float: left;margin:2px;border-radius:5px;font-size:1em;font-family:Lato;color: rgb(255, 255, 227);border:0px">
                Submit
            </button>
            <input id="upload" type="file" accept="image/*" style="display:none">
        </div>
        `
        const upload_btn = container.querySelector("#upload-btn")
        const upload = container.querySelector("#upload")
        upload_btn.onclick = () => {
            if(upload) upload.click()
        }

        let imageEncoded = null
        let file = null
        const img_output = container.querySelector('#output');
        const img = container.querySelector("#image")
        upload.onchange = (event) => {
            file = event.target.files[0]
            img_output.src = URL.createObjectURL(event.target.files[0]);
            img.style = "display: block"

            const canvas = document.createElement('canvas');
            const ctx = canvas.getContext('2d');
        
            var base_image = new Image();
            base_image.src = img_output.src;
            base_image.onload = function() {
                canvas.width = base_image.width;
                canvas.height = base_image.height;

                imgWidth = base_image.width;
                imgHeight = base_image.height;
        
                ctx.drawImage(base_image, 0, 0);
                imageEncoded = canvas.toDataURL('image/jpeg')
                canvas.remove();
            }
        }

        const imageUpload = async (image) => {
            if(!file) return
            const data = new FormData()
            data.append('file', file)
            const res = await fetch(
                `https://predict.app.landing.ai/inference/v1/predict?endpoint_id=582a8a02-0357-412f-a31d-865549855e43`, {
                    method:'POST',
                    mode: 'cors',
                    headers: {
                        'apikey':'2a7uwh0n7kojn34iov5wo4epnt6qcum',
                        'apisecret':'klprn1tfzninfffpdsb7jqwt09zvbtvbughnljq6wq8pa2gavc2ku15ybysykp'
                    },
                    body: data
            });
            if (!res.ok) {
                const message = `An error has occured: ${res.status}`;
                throw new Error(message);
            }
            const response = await res.json()
            return response
        }

        const submit_btn = container.querySelector("#submit-btn")
        submit_btn.onclick = async () => {
            const resData = await imageUpload(imageEncoded)
            if(resultImgDiv) {
                resultImgDiv.src = imageEncoded;
                resultImgDiv.style.display='block'
            }
            if(resData) {
                if(resData.backbonepredictions) {
                    for(let key in resData.backbonepredictions) {
                        let coordinates = resData.backbonepredictions[key].coordinates
                        if(resultImgDiv) {
                            resultImgDiv.src = imageEncoded;
                            let imgWidthDiv =  resultImgDiv.width
                            let imgHeightDiv =  resultImgDiv.height
                            let xmax = coordinates.xmax
                            let xmin = coordinates.xmin
                            let ymax = coordinates.ymax
                            let ymin = coordinates.ymin

                            let leftPercent = (1.0*xmin)/(imgWidth*1.0)
                            let topPercent = (1.0*ymin)/(imgHeight*1.0)

                            let widthPercent = (xmax-xmin)/(imgWidth*1.0)
                            let heightPercent = (ymax-ymin)/(imgHeight*1.0)

                            resultRecDiv.style.left = `${imgWidthDiv * leftPercent}px`
                            resultRecDiv.style.top = `${imgHeightDiv * topPercent}px`

                            resultRecDiv.style.width = `${imgWidthDiv * widthPercent}px`
                            resultRecDiv.style.height = `${imgHeightDiv * heightPercent}px`
                        }
                        break;
                    }
                }
            }
        }
        box.injectNode(container)
        return () => { }
    })


    widgets.register("Video Panel", (box) => {
        container = document.createElement('div')
        container.innerHTML = 
        `
        <div id="image" style="display:block;z-index:1;">
            <img id="output" width="100%" height="100%" 
                src="https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2F0000.JPG?alt=media&token=4e2bb785-846f-4ee1-8774-0a101b473bca"/>
        </div>
        <!-- <div id="video" style="display:block; width:100%; height:100%"> -->
            <!-- <video id="raw-video" width="100%" height="100%" style="object-fit:fill">
                <source src="https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2Fwallet-detection%2Fwallet-detection-default.mp4?alt=media&token=e7a9ed4e-a463-4bd8-be45-af1a3e498f51" type="video/mp4"></source>
            </video> -->
            <!-- <div style="width:3em;cursor: pointer;position:absolute;bottom:45%;left:45%"" id="play-btn">
				<img src="https://firebasestorage.googleapis.com/v0/b/digital-auto.appspot.com/o/media%2Fplay.svg?alt=media&token=4f68e20d-5c11-4e2c-9ae3-7f44ebdd0416" alt="play" style="filter: invert(100%);">
			</div> -->
        <!-- </div> -->
        <div class="btn btn-color" style="display:flex;z-index:2; position:absolute; width: 100%; bottom: 10px; opacity:85%; align-items:center; align-content:center; flex-direction:row; justify-content:center">
            <button id="upload-btn" style="background-color: rgb(104 130 158);padding: 10px 24px;cursor: pointer;float: left;margin:2px;border-radius:5px;font-size:1em;font-family:Lato;color: rgb(255, 255, 227);border:0px">
                Upload
            </button>
            <button id="submit-btn" style="background-color: rgb(104 130 158);padding: 10px 24px;cursor: pointer;float: left;margin:2px;border-radius:5px;font-size:1em;font-family:Lato;color: rgb(255, 255, 227);border:0px">
                Submit
            </button>
            <input id="upload" type="file" accept="image/*" style="display:none">
        </div>
        `
        const upload_btn = container.querySelector("#upload-btn")
        const upload = container.querySelector("#upload")
        upload_btn.onclick = () => {
            // container.querySelector("#upload").click()
            if(upload) upload.click()
        }

        let imageEncoded = null
        const img_output = container.querySelector('#output');
        const img = container.querySelector("#image")
        upload.onchange = (event) => {
            img_output.src = URL.createObjectURL(event.target.files[0]);
            img.style = "display: block"

            const canvas = document.createElement('canvas');
            const ctx = canvas.getContext('2d');
        
            var base_image = new Image();
            base_image.src = img_output.src;
            base_image.onload = function() {
                canvas.width = base_image.width;
                canvas.height = base_image.height;

                imgWidth = base_image.width;
                imgHeight = base_image.height;
        
                ctx.drawImage(base_image, 0, 0);
                imageEncoded = canvas.toDataURL('image/jpeg')
                canvas.remove();
            }

            // const video = container.querySelector("#raw-video");
            // container.querySelector("#video").style = "display: none"
            // video.innerHTML = `<source src=${URL.createObjectURL(event.target.files[0])} type="video/mp4"></source>`
            // video.load()
            // container.querySelector("#video").style = "display: block"
        }

        const imageUpload = async (image) => {
            image = image.replace('data:image/jpeg;base64,', '')
            const apikey = 'h644blf0bp1g3k4d8ffkazchyfb412e'
            const apisecret = 'yswm5qiyg0lhf45fo3pn1epsv5m01li03094wgwf7hgactxlq76kdd55whymfx'
            const endpoint_id = '582a8a02-0357-412f-a31d-865549855e43'
            const res = await fetch(
                `https://aiotapp.net/walletdetection/image-upload`, {
                    method:'POST',
                    mode: 'cors',
                    cache: 'no-cache',
                    headers: {
                        'Content-Type': 'application/json'
                    },
                    body: JSON.stringify({
                        image,
                        apikey,
                        apisecret,
                        endpoint_id
                    })
                });
            // waits until the request completes...
            if (!res.ok) {
                const message = `An error has occured: ${res.status}`;
                throw new Error(message);
            }
            //conver response to json
            const response = await res.json()
            let op = response["output"]
            op = op.replaceAll('\"', "'").replaceAll('"{', '{').replaceAll('"}','}').replaceAll("'", '"')
            return op
        }

        const videoUpload = async () => {
            const data = new FormData()
            data.append('file', upload.files[0])
            console.log(data)

            const res = await fetch(
                `https://predict.app.landing.ai/inference/v1/predict?endpoint_id=582a8a02-0357-412f-a31d-865549855e43`, {
                    method:'POST',
                    mode: 'cors',
                    headers: {
                        'Content-Type': 'multipart/form-data',
                        'apikey':'h644blf0bp1g3k4d8ffkazchyfb412e',
                        'apisecret':'yswm5qiyg0lhf45fo3pn1epsv5m01li03094wgwf7hgactxlq76kdd55whymfx'
                    },
                    body: data
                });
            // waits until the request completes...
            if (!res.ok) {
                const message = `An error has occured: ${res.status}`;
                throw new Error(message);
            }
            //convert response to json
            const response = await res.json()
            return response
        }

        const submit_btn = container.querySelector("#submit-btn")
        submit_btn.onclick = async () => {
            // console.log(setLocationGlobal)
            const res = await imageUpload(imageEncoded)
            // console.log(resultImgDiv)
            // console.log(imageEncoded)
            if(res) {
                let resData = JSON.parse(res)
                // console.log(resData)
                if(resData && resData.backbonepredictions) {
                    for(let key in resData.backbonepredictions) {
                        let coordinates = resData.backbonepredictions[key].coordinates
                        // console.log("res.backbonepredictions.coordinates", coordinates)
                        if(resultImgDiv) {
                            resultImgDiv.src = imageEncoded;
                            let imgWidthDiv =  resultImgDiv.width
                            let imgHeightDiv =  resultImgDiv.height
                            let xmax = coordinates.xmax
                            let xmin = coordinates.xmin
                            let ymax = coordinates.ymax
                            let ymin = coordinates.ymin

                            let leftPercent = (1.0*xmin)/(imgWidth*1.0)
                            let topPercent = (1.0*ymin)/(imgHeight*1.0)

                            let widthPercent = (xmax-xmin)/(imgWidth*1.0)
                            let heightPercent = (ymax-ymin)/(imgHeight*1.0)

                            resultRecDiv.style.left = `${imgWidthDiv * leftPercent}px`
                            resultRecDiv.style.top = `${imgHeightDiv * topPercent}px`

                            resultRecDiv.style.width = `${imgWidthDiv * widthPercent}px`
                            resultRecDiv.style.height = `${imgHeightDiv * heightPercent}px`

                        }

                        break;
                    }
                }
            }
        }

        /* const play_btn = container.querySelector("#play-btn")
        play_btn.onclick = () => {
            container.querySelector("#raw-video").play();            
        } */

        box.injectNode(container)

        return () => {
            clearInterval(simInterval)
        }

    })

    let mobileNotificationsGlobal = null;
    widgets.register("Mobile",
    (box) => {
        const {printNotification} = MobileNotifications(
            {
                box:box,
                backgroundColor: "rgb(0 80 114)"
            }
        )
        mobileNotificationsGlobal = printNotification
    })

    let count = 0;

    return {
        load_data: async () => {
            loadSpreadSheet()
        },
        mobile_notification: (message) => {
            mobileNotificationsGlobal(message)
        },
        start_simulation: (time) => {
            simInterval = setInterval(async () => {
                const lat = parseFloat(await vehicle.CurrentLocation.Latitude.get())
                const lng = parseFloat(await vehicle.CurrentLocation.Longitude.get())

                setLocationGlobal({lat, lng})
                if(count === 0) {
                    container.querySelector("#raw-video").play()
                    count++
                }
                await vehicle.Next.get()
            }, time)
        }
    }

}

export default plugin;