Update validate_onnx_parity.py

update code & comment

Machine_Learning/validate_onnx_parity.py

@@ -10,10 +10,10 @@ import onnxruntime as ort
 import tensorflow as tf
 from PIL import Image, UnidentifiedImageError
 
-
+# Definisi label kelas sesuai urutan output model klasifikasi
 LABELS = ["Bercak Daun", "Daun Sehat", "Karat Daun", "Hawar Daun"]
 
-
+# Kelas eksepsi kustom untuk menangani ketidaksesuaian akurasi prediksi
 class ParityError(RuntimeError):
     """Raised when Keras and ONNX predictions do not match."""
     pass
@@ -33,16 +33,19 @@ def preprocess_image(image_path, input_size):
     Raises:
         ParityError: If image cannot be loaded or processed.
     """
+    # Penanganan error secara aman saat memuat gambar ke format RGB
     try:
         img = Image.open(image_path).convert("RGB")
     except (FileNotFoundError, UnidentifiedImageError, OSError) as e:
         raise ParityError(f"Failed to load image {image_path}: {e}")
 
+    # Penyesuaian resolusi gambar menggunakan metode interpolasi Bilinear
     try:
         img = img.resize((input_size, input_size), Image.Resampling.BILINEAR)
     except Exception as e:
         raise ParityError(f"Failed to resize image {image_path}: {e}")
 
+    # Konversi ke matriks float32 dan penambahan dimensi batch (1, H, W, C)
     img_array = np.array(img, dtype=np.float32)
     img_batch = np.expand_dims(img_array, axis=0)
 
@@ -60,6 +63,7 @@ def predict_keras(model, image_batch):
     Returns:
         Predictions array (1, num_classes).
     """
+    # Eksekusi inferensi pada model TensorFlow/Keras tanpa log proses
     predictions = model.predict(image_batch, verbose=0)
     return predictions
 
@@ -75,6 +79,7 @@ def predict_onnx(session, image_batch):
     Returns:
         Predictions array (1, num_classes).
     """
+    # Eksekusi inferensi secara dinamis pada model ONNX menggunakan sesi runtime
     input_name = session.get_inputs()[0].name
     predictions = session.run(None, {input_name: image_batch})
     return predictions[0]
@@ -94,14 +99,18 @@ def validate_image(image_path, keras_model, onnx_session, input_size, atol):
     Raises:
         ParityError: If predictions do not match or image cannot be processed.
     """
+    # Menyiapkan tensor gambar untuk pengujian
     img_batch = preprocess_image(image_path, input_size)
 
+    # Mengekstrak matriks probabilitas dari kedua format model
     keras_pred = predict_keras(keras_model, img_batch)
     onnx_pred = predict_onnx(onnx_session, img_batch)
 
+    # Mendapatkan indeks kelas dengan probabilitas tertinggi (Top-1)
     keras_label_idx = np.argmax(keras_pred[0])
     onnx_label_idx = np.argmax(onnx_pred[0])
 
+    # Validasi keselarasan keputusan klasifikasi utama
     if keras_label_idx != onnx_label_idx:
         keras_label = LABELS[keras_label_idx]
         onnx_label = LABELS[onnx_label_idx]
@@ -110,6 +119,7 @@ def validate_image(image_path, keras_model, onnx_session, input_size, atol):
             f"Keras={keras_label}, ONNX={onnx_label}"
         )
 
+    # Validasi selisih nilai desimal probabilitas menggunakan toleransi absolut
     if not np.allclose(keras_pred, onnx_pred, atol=atol):
         max_diff = np.max(np.abs(keras_pred - onnx_pred))
         raise ParityError(
@@ -117,6 +127,7 @@ def validate_image(image_path, keras_model, onnx_session, input_size, atol):
             f"max difference={max_diff:.6e} (atol={atol})"
         )
 
+    # Pencatatan log sistem jika kedua model presisi 100%
     label = LABELS[keras_label_idx]
     logging.info(f"PASS: {image_path} -> {label}")
 
@@ -125,6 +136,7 @@ def main():
     """Validate parity between Keras and ONNX models."""
     logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
 
+    # Inisialisasi parser argumen untuk antarmuka CLI (Command Line Interface)
     parser = argparse.ArgumentParser(
         description="Validate parity between Keras and ONNX models"
     )
@@ -161,6 +173,7 @@ def main():
 
     args = parser.parse_args()
 
+    # Pengecekan eksistensi berkas model sebelum memuat memori
     if not args.keras_model.exists():
         msg = f"Keras model not found at {args.keras_model}"
         logging.error(msg)
@@ -171,15 +184,18 @@ def main():
         logging.error(msg)
         raise FileNotFoundError(msg)
 
+    # Memuat model Keras (tanpa kompilasi agar lebih hemat beban komputasi)
     logging.info(f"Loading Keras model from {args.keras_model}...")
     keras_model = tf.keras.models.load_model(args.keras_model, compile=False)
 
+    # Memuat sesi ONNX dengan penyedia eksekusi CPU murni
     logging.info(f"Loading ONNX model from {args.onnx_model}...")
     onnx_session = ort.InferenceSession(
         str(args.onnx_model),
         providers=["CPUExecutionProvider"],
     )
 
+    # Iterasi pengujian paritas (kesetaraan performa) untuk setiap gambar
     logging.info(f"Validating {len(args.images)} image(s)...")
     for image_path in args.images:
         try:

Makefile

@@ -2,7 +2,7 @@
 # ZeaVis Edu — Root Makefile
 #
 # Orchestrates the application stack (web, api, ml) and the telemetry
-# metric pipeline (Prometheus → Ingester → Vector → ClickHouse).
+# metric pipeline (Prometheus → Grafana).
 #
 # Telemetry commands operate on the submodule at telemetry/.
 # =============================================================================

README.md

@@ -66,7 +66,10 @@ ZeaVis Edu menggunakan **Computer Vision** sebagai asisten edukasi interaktif:
 |---|---|
 | Arsitektur Model | **EfficientNetV2B0** — keseimbangan optimal antara akurasi dan efisiensi parameter |
 | Metode Pelatihan | **Transfer Learning** pada Google Colab (GPU T4) |
-| Sumber Dataset | Kaggle — [Corn Leaf Disease](https://www.kaggle.com/datasets/ndisan/corn-leaf-disease) |
+| Sumber Dataset 1 | Kaggle — [Corn Leaf Disease](https://www.kaggle.com/datasets/ndisan/corn-leaf-disease) |
+| Sumber Dataset 2 | Kaggle — [Corn or Maize Leaf Disease Dataset](https://www.kaggle.com/datasets/smaranjitghose/corn-or-maize-leaf-disease-dataset) |
+| Sumber Dataset 3 | scidb — [Dataset of Corn Leaf Diseases based on Manual Annotation and Contrast Generation Model](https://www.scidb.cn/en/detail?dataSetId=19536c73f6d74946a212719a94f53ab3) |
+
 | Deployment | VPS dengan Docker, ONNX Runtime untuk inferensi real-time |
 
 ---

apps/web/index.html

@@ -4,6 +4,11 @@
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>ZeaVis Edu</title>
+    <link
+      rel="icon"
+      type="image/svg+xml"
+      href="data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='none' stroke='%2322C55E' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'%3E%3Cpath d='M11 20A7 7 0 0 1 9.8 6.1C15.5 5 17 4.48 19 2c1 2 2 4.18 2 8 0 5.5-4.78 10-10 10Z'/%3E%3Cpath d='M2 22l10-10'/%3E%3C/svg%3E"
+    />
   </head>
   <body>
     <div id="root"></div>

apps/web/src/components/auth-form.tsx

@@ -1,25 +1,42 @@
-import { FormEvent, useState, useCallback } from 'react';
-import { Eye, EyeOff } from 'lucide-react';
-import { Button } from '@/components/ui/button';
-import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card';
-import { Input } from '@/components/ui/input';
-import { Label } from '@/components/ui/label';
-import { apiBaseUrl } from '@/lib/api-client';
-import { isTauri, openUrl } from '@/lib/tauri';
+import { FormEvent, useState, useCallback } from "react";
+import { Eye, EyeOff } from "lucide-react";
+import { Button } from "@/components/ui/button";
+import {
+  Card,
+  CardContent,
+  CardDescription,
+  CardHeader,
+  CardTitle,
+} from "@/components/ui/card";
+import { Input } from "@/components/ui/input";
+import { Label } from "@/components/ui/label";
+import { apiBaseUrl } from "@/lib/api-client";
+import { isTauri, openUrl } from "@/lib/tauri";
 
 type AuthFormProps = {
-  mode: 'login' | 'register';
+  mode: "login" | "register";
   isSubmitting: boolean;
   error: string | null;
   googleOAuthEnabled: boolean;
-  onSubmit: (payload: { name?: string; email: string; password: string }) => Promise<unknown>;
+  onSubmit: (payload: {
+    name?: string;
+    email: string;
+    password: string;
+  }) => Promise<unknown>;
   onFieldChange?: () => void;
 };
 
-export function AuthForm({ mode, isSubmitting, error, googleOAuthEnabled, onSubmit, onFieldChange }: AuthFormProps) {
-  const [name, setName] = useState('');
-  const [email, setEmail] = useState('');
-  const [password, setPassword] = useState('');
+export function AuthForm({
+  mode,
+  isSubmitting,
+  error,
+  googleOAuthEnabled,
+  onSubmit,
+  onFieldChange,
+}: AuthFormProps) {
+  const [name, setName] = useState("");
+  const [email, setEmail] = useState("");
+  const [password, setPassword] = useState("");
   const [showPassword, setShowPassword] = useState(false);
 
   async function handleSubmit(event: FormEvent<HTMLFormElement>) {
@@ -29,7 +46,7 @@ export function AuthForm({ mode, isSubmitting, error, googleOAuthEnabled, onSubm
 
   const handleGoogleLogin = useCallback(async (e: React.MouseEvent) => {
     e.preventDefault();
-    const platform = isTauri() ? 'tauri' : 'web';
+    const platform = isTauri() ? "tauri" : "web";
     const googleUrl = `${apiBaseUrl}/api/v1/auth/google?platform=${platform}`;
     await openUrl(googleUrl);
   }, []);
@@ -37,59 +54,111 @@ export function AuthForm({ mode, isSubmitting, error, googleOAuthEnabled, onSubm
   return (
     <Card className="mx-auto w-full max-w-md bg-transparent border-none shadow-none">
       <CardHeader className="text-center space-y-2">
-        <CardTitle className="text-2xl font-bold text-emerald-900">{mode === 'login' ? 'Masuk Akun ZeaVis Edu' : 'Buat akun ZeaVis Edu'}</CardTitle>
+        <CardTitle className="text-2xl font-bold text-emerald-900">
+          {mode === "login" ? "Masuk Akun ZeaVis Edu" : "Buat akun ZeaVis Edu"}
+        </CardTitle>
         <CardDescription className="text-sm text-emerald-800/80">
-          {mode === 'login'
-            ? 'Masuk untuk menyimpan diagnosis dan mengikuti review pakar.'
-            : 'Daftar untuk menyimpan diagnosis dan mengikuti review pakar.'}
+          {mode === "login"
+            ? "Masuk untuk menyimpan diagnosis dan mengikuti review pakar."
+            : "Daftar untuk menyimpan diagnosis dan mengikuti review pakar."}
         </CardDescription>
       </CardHeader>
       <CardContent>
         <form className="space-y-4" onSubmit={handleSubmit}>
-          {mode === 'register' && (
+          {mode === "register" && (
             <div className="space-y-2">
               <Label htmlFor="name">Nama</Label>
-              <Input id="name" value={name} onChange={(event) => {
-                setName(event.target.value);
-                onFieldChange?.();
-              }} required />
+              <Input
+                id="name"
+                placeholder="Masukkan nama Anda"
+                value={name}
+                onChange={(event) => {
+                  setName(event.target.value);
+                  onFieldChange?.();
+                }}
+                required
+              />
             </div>
           )}
           <div className="space-y-2">
             <Label htmlFor="email">Email</Label>
-            <Input id="email" type="email" value={email} onChange={(event) => {
-              setEmail(event.target.value);
-              onFieldChange?.();
-            }} required />
+            <Input
+              id="email"
+              type="email"
+              placeholder="Masukkan email Anda"
+              value={email}
+              onChange={(event) => {
+                setEmail(event.target.value);
+                onFieldChange?.();
+              }}
+              required
+            />
           </div>
           <div className="space-y-2">
             <Label htmlFor="password">Password</Label>
             <div className="relative">
-              <Input id="password" type={showPassword ? "text" : "password"} minLength={8} value={password} onChange={(event) => {
-                setPassword(event.target.value);
-                onFieldChange?.();
-              }} required />
+              <Input
+                id="password"
+                type={showPassword ? "text" : "password"}
+                placeholder="Password minimal 8 karakter"
+                minLength={8}
+                value={password}
+                onChange={(event) => {
+                  setPassword(event.target.value);
+                  onFieldChange?.();
+                }}
+                required
+              />
               <button
                 type="button"
                 className="absolute right-3 top-1/2 -translate-y-1/2 text-muted-foreground focus:outline-none"
                 onClick={() => setShowPassword(!showPassword)}
               >
-                {showPassword ? <EyeOff className="h-4 w-4" /> : <Eye className="h-4 w-4" />}
+                {showPassword ? (
+                  <EyeOff className="h-4 w-4" />
+                ) : (
+                  <Eye className="h-4 w-4" />
+                )}
               </button>
             </div>
           </div>
-          {error && <p className="text-sm text-red-600" role="alert">{error}</p>}
+          {error && (
+            <p className="text-sm text-red-600" role="alert">
+              {error}
+            </p>
+          )}
           <Button className="w-full" type="submit" disabled={isSubmitting}>
-            {isSubmitting ? 'Memproses...' : mode === 'login' ? 'Masuk' : 'Daftar'}
+            {isSubmitting
+              ? "Memproses..."
+              : mode === "login"
+                ? "Masuk"
+                : "Daftar"}
           </Button>
         </form>
         {googleOAuthEnabled && (
-          <Button className="mt-3 w-full flex items-center justify-center gap-2.5" variant="outline" onClick={handleGoogleLogin} type="button">
+          <Button
+            className="mt-3 w-full flex items-center justify-center gap-2.5"
+            variant="outline"
+            onClick={handleGoogleLogin}
+            type="button"
+          >
             <svg viewBox="0 0 24 24" className="h-5 w-5" aria-hidden="true">
-              <path fill="#4285F4" d="M22.56 12.25c0-.78-.07-1.53-.2-2.25H12v4.26h5.92a5.06 5.06 0 0 1-2.2 3.32v2.77h3.57c2.08-1.92 3.28-4.74 3.28-8.1z" />
-              <path fill="#34A853" d="M12 23c2.97 0 5.46-.98 7.28-2.66l-3.57-2.77c-.98.66-2.23 1.06-3.71 1.06-2.86 0-5.29-1.93-6.16-4.53H2.18v2.84C3.99 20.53 7.7 23 12 23z" />
-              <path fill="#FBBC05" d="M5.84 14.09c-.22-.66-.35-1.36-.35-2.09s.13-1.43.35-2.09V7.07H2.18C1.43 8.55 1 10.22 1 12s.43 3.45 1.18 4.93l2.85-2.22.81-.62z" />
-              <path fill="#EA4335" d="M12 5.38c1.62 0 3.06.56 4.21 1.64l3.15-3.15C17.45 2.09 14.97 1 12 1 7.7 1 3.99 3.47 2.18 7.07l3.66 2.84c.87-2.6 3.3-4.53 6.16-4.53z" />
+              <path
+                fill="#4285F4"
+                d="M22.56 12.25c0-.78-.07-1.53-.2-2.25H12v4.26h5.92a5.06 5.06 0 0 1-2.2 3.32v2.77h3.57c2.08-1.92 3.28-4.74 3.28-8.1z"
+              />
+              <path
+                fill="#34A853"
+                d="M12 23c2.97 0 5.46-.98 7.28-2.66l-3.57-2.77c-.98.66-2.23 1.06-3.71 1.06-2.86 0-5.29-1.93-6.16-4.53H2.18v2.84C3.99 20.53 7.7 23 12 23z"
+              />
+              <path
+                fill="#FBBC05"
+                d="M5.84 14.09c-.22-.66-.35-1.36-.35-2.09s.13-1.43.35-2.09V7.07H2.18C1.43 8.55 1 10.22 1 12s.43 3.45 1.18 4.93l2.85-2.22.81-.62z"
+              />
+              <path
+                fill="#EA4335"
+                d="M12 5.38c1.62 0 3.06.56 4.21 1.64l3.15-3.15C17.45 2.09 14.97 1 12 1 7.7 1 3.99 3.47 2.18 7.07l3.66 2.84c.87-2.6 3.3-4.53 6.16-4.53z"
+              />
               <path fill="none" d="M1 1h22v22H1z" />
             </svg>
             Masuk dengan Google

apps/web/src/pages/scan-page.tsx

@@ -33,6 +33,7 @@ export function ScanPage() {
   const imageRef = useRef<HTMLImageElement | null>(null);
   const navigate = useNavigate();
   const queryClient = useQueryClient();
+  const [isDragging, setIsDragging] = useState(false);
 
   // Camera mode state
   const [useCamera, setUseCamera] = useState(false);
@@ -164,8 +165,25 @@ export function ScanPage() {
                   ) : (
                     <>
                       <div
-                        className="w-full border-2 border-dashed border-green-300 rounded-md p-10 h-60 text-center cursor-pointer"
+                        className={`w-full border-2 border-dashed rounded-md p-10 h-60 text-center cursor-pointer transition-colors duration-200 ${
+                          isDragging
+                            ? "border-blue-500 bg-blue-100"
+                            : "border-green-300"
+                        }`}
                         onClick={() => inputRef.current?.click()}
+                        onDragOver={(e) => {
+                          e.preventDefault();
+                          setIsDragging(true);
+                        }}
+                        onDragLeave={() => setIsDragging(false)}
+                        onDrop={(e) => {
+                          e.preventDefault();
+                          setIsDragging(false);
+                          const droppedFile = e.dataTransfer.files?.[0];
+                          if (droppedFile) {
+                            handleFile(droppedFile);
+                          }
+                        }}
                       >
                         <Upload
                           className="mx-auto text-green-500 mb-3"