index.html

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Tulsi Analytics — DETR & YOLO12</title>
    <style>
        :root {
            --primary-orange: #EA782D;
            --accent-orange: #FF7A5A;
            --dark-bg: #121212;
            --surface: #1E1E2E;
            --text: #E0E0E0;
            --border: rgba(255, 255, 255, 0.1);
        }

        body {
            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
            background: var(--dark-bg);
            color: var(--text);
            margin: 0;
            padding: 20px;
        }

        .container {
            max-width: 1400px;
            margin: 0 auto;
            background: var(--surface);
            border-radius: 12px;
            border: 1px solid var(--border);
            overflow: hidden;
        }

        header {
            padding: 25px;
            text-align: center;
            border-bottom: 1px solid var(--border);
            background: rgba(0,0,0,0.2);
        }

        h1 { color: var(--primary-orange); margin: 0; font-weight: 500; }

        .layout {
            display: grid;
            grid-template-columns: 1fr 1fr;
            gap: 20px;
            padding: 20px;
        }

        @media (max-width: 1000px) {
            .layout { grid-template-columns: 1fr; }
        }

        .panel {
            background: rgba(0,0,0,0.15);
            padding: 20px;
            border-radius: 10px;
        }

        .image-view {
            width: 100%;
            height: 450px;
            background: #000;
            border-radius: 8px;
            display: flex;
            align-items: center;
            justify-content: center;
            margin-bottom: 15px;
            border: 1px solid var(--border);
            overflow: hidden;
        }

        img { max-width: 100%; max-height: 100%; object-fit: contain; }

        .controls {
            display: flex;
            flex-direction: column;
            gap: 15px;
        }

        .control-row {
            display: flex;
            align-items: center;
            justify-content: space-between;
            padding: 10px;
            background: rgba(255,255,255,0.03);
            border-radius: 6px;
        }

        .slider-group { padding: 10px; }
        input[type="range"] { width: 100%; accent-color: var(--primary-orange); }

        /* Toggle Switch */
        .switch {
            position: relative;
            display: inline-block;
            width: 44px;
            height: 22px;
        }
        .switch input { opacity: 0; width: 0; height: 0; }
        .slider {
            position: absolute;
            cursor: pointer;
            top: 0; left: 0; right: 0; bottom: 0;
            background-color: #444;
            transition: .4s;
            border-radius: 34px;
        }
        .slider:before {
            position: absolute;
            content: "";
            height: 16px; width: 16px;
            left: 3px; bottom: 3px;
            background-color: white;
            transition: .4s;
            border-radius: 50%;
        }
        input:checked + .slider { background-color: var(--primary-orange); }
        input:checked + .slider:before { transform: translateX(22px); }

        .predict-btn {
            background: var(--primary-orange);
            color: white;
            border: none;
            padding: 15px;
            border-radius: 8px;
            font-weight: 600;
            cursor: pointer;
            transition: 0.2s;
            width: 100%;
        }
        .predict-btn:hover { background: var(--accent-orange); }
        .predict-btn:disabled { opacity: 0.5; cursor: not-allowed; }

        .upload-box {
            border: 2px dashed var(--border);
            padding: 20px;
            text-align: center;
            cursor: pointer;
            margin-bottom: 15px;
        }
    </style>
</head>
<body>

<div class="container">
    <header>
        <h1>Tulsi Disease Analysis</h1>
    </header>

    <div class="layout">
        <div class="panel">
            <div class="upload-box" id="drop-zone">Click/Drop Image</div>
            <input type="file" id="file-input" hidden accept="image/*">
            
            <div class="image-view">
                <img id="input-preview" src="" style="display:none;">
            </div>

            <div class="controls">
                <div class="control-row">
                    <span>Enable Segmentation</span>
                    <label class="switch"><input type="checkbox" id="seg-enable" checked><span class="slider"></span></label>
                </div>
                <div class="slider-group">
                    <label>Seg. Confidence: <span id="seg-val">0.25</span></label>
                    <input type="range" id="seg-conf" min="5" max="95" value="25">
                </div>
                <div class="control-row">
                    <span>Show Seg. Confidence</span>
                    <label class="switch"><input type="checkbox" id="seg-show-conf"><span class="slider"></span></label>
                </div>

                <div class="control-row">
                    <span>Enable Classification</span>
                    <label class="switch"><input type="checkbox" id="cls-enable" checked><span class="slider"></span></label>
                </div>
                <div class="control-row">
                    <span>Show Label</span>
                    <label class="switch"><input type="checkbox" id="cls-show-label" checked><span class="slider"></span></label>
                </div>
                <div class="control-row">
                    <span>Show Cls. Confidence</span>
                    <label class="switch"><input type="checkbox" id="cls-show-conf" checked><span class="slider"></span></label>
                </div>

                <button id="predict-btn" class="predict-btn" disabled>Run Analysis</button>
            </div>
        </div>

        <div class="panel">
            <h3 style="margin-top:0;">Overlay Result</h3>
            <div class="image-view">
                <img id="output-preview" src="">
            </div>
            <div id="status">Status: Waiting for input</div>
        </div>
    </div>
</div>

<script>
    const fileInput = document.getElementById('file-input');
    const dropZone = document.getElementById('drop-zone');
    const inputImg = document.getElementById('input-preview');
    const outputImg = document.getElementById('output-preview');
    const predictBtn = document.getElementById('predict-btn');
    const segConf = document.getElementById('seg-conf');
    const segVal = document.getElementById('seg-val');

    segConf.oninput = () => segVal.innerText = (segConf.value / 100).toFixed(2);

    dropZone.onclick = () => fileInput.click();
    fileInput.onchange = (e) => handleFile(e.target.files[0]);

    function handleFile(file) {
        if (!file) return;
        const reader = new FileReader();
        reader.onload = (e) => {
            inputImg.src = e.target.result;
            inputImg.style.display = 'block';
            predictBtn.disabled = false;
        };
        reader.readAsDataURL(file);
    }

    predictBtn.onclick = async () => {
        predictBtn.disabled = true;
        predictBtn.innerText = "Processing...";
        
        const payload = {
            image: inputImg.src,
            seg_enabled: document.getElementById('seg-enable').checked,
            seg_conf: segConf.value / 100,
            seg_show_conf: document.getElementById('seg-show-conf').checked,
            cls_enabled: document.getElementById('cls-enable').checked,
            cls_show_conf: document.getElementById('cls-show-conf').checked,
            cls_show_label: document.getElementById('cls-show-label').checked
        };

        try {
            const resp = await fetch('/predict', {
                method: 'POST',
                headers: {'Content-Type': 'application/json'},
                body: JSON.stringify(payload)
            });
            const data = await resp.json();
            outputImg.src = data.annotated;
            document.getElementById('status').innerText = `Status: Detected ${data.count} leaves`;
        } catch (e) {
            alert("Error running inference");
        } finally {
            predictBtn.disabled = false;
            predictBtn.innerText = "Run Analysis";
        }
    };
</script>
</body>
</html>