style: change language to Indonesian

src/streamlit_app.py

@@ -4,33 +4,37 @@ from PIL import Image
 import numpy as np
 import os
 
-# --- CONFIGURATION ---
 SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
 MODEL_PATH = os.path.join(SCRIPT_DIR, "best.pt")
 
-# --- KNOWLEDGE BASE ---
 SYMPTOM_QUESTIONS = {
     "G1": "Daun berwana putih kecoklatan memanjang seperti mengering pada bagian tepi daun?",
-    "G2": "Pada pagi hari, ditemukan cairan bakteri (seperti butiran air) pada bagian terinfeksi?",
-    "G3": "Luka terlihat seperti anak panah di antara urat daun?",
-    "G4": "Luka berwarna kuning kecoklatan?",
-    "G5": "Pada daun terlihat transparan bila dihadapkan cahaya matahari?",
-    "G6": "Bercak berbentuk belah ketupat (Diamond shape)?",
-    "G7": "Bagian tengah bercak abu-abu/putih, tepi berwarna kecoklatan?",
+    "G2": "Pada pagi hari, dapat ditemukan cairan bakteri terlihat seperti butiran air pada bagian terinfeksi",
+    "G3": "Gejala terlihat seperti anak panah terdapat di antara urat daun?",
+    "G4": "Daun Berwarna kuning kecoklatan?",
+    "G5": "Luka pada daun terlihat transparan bila dihadapkan cahaya matahari?",
+    "G6": "Daun berbentuk belah ketupat?",
+    "G7": "Pada daun bagian tengah berwarna abu-abu atau berwarna putih dengan bagian tepi berwarna kecoklatan?",
     "G8": "Infeksi pada malai/leher berwarna abu-abu?",
-    "G13": "Tanaman kerdil dan daun berubah warna (hijau -> jingga/kemerahan)?",
-    "G025": "Daun menguning, menggulung, mengering dan menjadi layu?",
-    "G026": "Bibit menjadi layu (kresek) tapi sulit dicabut?",
-    "G027": "Warna luka bercak jingga kekuningan dari ujung ke pangkal?",
-    "G028": "Ada bulatan kecil berwarna kuning pada pelepah daun?"
+    "G9": "Tanaman kerdil dan Gejala pada daun terjadi perubahan warna dari hijau menjadi jingga atau kemerahan?",
+    "G10": "Daun menguning, menggulung, mengering dan menjadi layu?",
+    "G11": "Bibit menjadi layu (kresek) tapi sulit dicabut?",
+    "G12": "Warna luka bercak menjadi jingga kekuningan dari ujung daun ke pangkal daun?",
+    "G13": "Ada bulatan kecil berwarna kuning pada pelepah daun?",
+    "G14": "Bercak cokelat pada daun, pelepah, dan bulir gabah?",
+    "G15": "Bercak daun sering menutupi permukaan daun, menyebabkan daun menjadi layu?",
+    "G16": "Bercak cokelat pada batang/leher malai?",
+    "G17": "Terdapat bercak berbentuk oval berwarna abu-abu kehijauan pada pelepah (tulang daun)?",
+    "G18": "Batang tanaman padi menjadi rapuh dan mudah rebah/jatuh?",
+    "G19": "Bibit yang sakit menjadi layu dan akhirnya mati?"
 }
 
 YOLO_PROMPTS = {
-    "bacterial_leaf_blight": ["G1", "G2"], 
-    "bacterial_leaf_streak": ["G3", "G4", "G5"],
+    "bacterial_leaf_blight": ["G1", "G2", "G3"], 
+    "bacterial_leaf_streak": ["G4", "G5"],
     "blast": ["G6", "G7", "G8"], 
-    "tungro": ["G13"],
-    "brown_spot": [], 
+    "tungro": ["G9"],
+    "brown_spot": ["G14", "G15", "G16"], 
     "downy_mildew": [],
     "dead_heart": [],
     "hispa": [],
@@ -38,15 +42,17 @@ YOLO_PROMPTS = {
 }
 
 PRODUCTION_RULES = [
-    {"disease": "Bacterial Leaf Blight (Hawar Daun Bakteri)", "symptoms": ["G1", "G2"], "source": "Literatur 1"},
-    {"disease": "Bacterial Leaf Streak (Bakteri Daun Bergaris)", "symptoms": ["G3", "G4", "G5"], "source": "Literatur 1"},
-    {"disease": "Blast (Blas)", "symptoms": ["G6", "G7"], "source": "Literatur 1"},
-    {"disease": "Neck Blast (Blas Leher)", "symptoms": ["G8"], "source": "Literatur 1"},
-    {"disease": "Tungro", "symptoms": ["G13"], "source": "Literatur 1"},
-    {"disease": "Bacterial Leaf Blight (Alt. Definition)", "symptoms": ["G025", "G026", "G027", "G028"], "source": "Literatur 2"}
+    {"disease": "Bacterial Leaf Blight (Hawar Daun Bakteri)", "symptoms": ["G1", "G2", "G3"], "source": "Literatur 1"},
+    {"disease": "Bakteri Daun Bergaris (Bacterial Leaf Streak)", "symptoms": ["G4", "G5"], "source": "Literatur 1"},
+    {"disease": "Blas (Blast)", "symptoms": ["G6", "G7", "G8"], "source": "Literatur 1"},
+    {"disease": "Tungro", "symptoms": ["G9"], "source": "Literatur 1"},
+
+    {"disease": "Hawar Daun Bakteri (Bacterial Leaf Blight)", "symptoms": ["G10", "G11", "G12", "G13"], "source": "Literatur 2"},
+    
+    {"disease": "Bercak Daun Coklat (Brown Spot)", "symptoms": ["G14", "G15", "G16"], "source": "Literatur 3"},
+    {"disease": "Hawar Pelepah (Sheath Blight)", "symptoms": ["G17", "G18", "G19"], "source": "Literatur 3"},
 ]
 
-# --- MODEL LOADING (Cached so it doesn't reload every click) ---
 @st.cache_resource
 def load_model():
     try:
@@ -57,14 +63,12 @@ def load_model():
 
 model = load_model()
 
-# --- APP LAYOUT ---
-st.title("🌾 Rice Doctor: Hybrid AI System")
+st.title("🌾 Rice Doctor: Sistem Pakar Penyakit Padi")
 st.markdown("""
-1. **AI Inference**: Detects disease from image.
-2. **Expert System**: Verifies diagnosis using Forward Chaining logic.
+1. **Inferensi AI**: Mendeteksi penyakit dari gambar.
+2. **Sistem Pakar**: Memverifikasi diagnosis menggunakan logika Forward Chaining.
 """)
 
-# Initialize Session State to keep data across re-runs
 if 'prediction' not in st.session_state:
     st.session_state['prediction'] = None
 if 'priority_codes' not in st.session_state:
@@ -72,77 +76,66 @@ if 'priority_codes' not in st.session_state:
 if 'analyzed' not in st.session_state:
     st.session_state['analyzed'] = False
 
-# --- STEP 1: UPLOAD AND ANALYZE ---
-uploaded_file = st.file_uploader("Step 1: Upload Leaf Image", type=["jpg", "png", "jpeg"])
+uploaded_file = st.file_uploader("Langkah 1: Unggah Gambar Daun", type=["jpg", "png", "jpeg"])
 
 if uploaded_file is not None:
-    # Display image
     image = Image.open(uploaded_file)
-    st.image(image, caption="Uploaded Image", use_container_width=True)
+    st.image(image, caption="Gambar yang Diunggah", use_container_width=True)
     
-    if st.button("Analyze & Generate Questions", type="primary"):
+    if st.button("Analisis Penyakit", type="primary"):
         if model:
-            with st.spinner("Analyzing..."):
-                # Run Inference
+            with st.spinner("Menganalisis..."):
                 results = model.predict(image, imgsz=640)
                 raw_name = results[0].names[results[0].probs.top1]
                 top_class_name = raw_name.lower().strip()
                 
-                # Save to session state
                 st.session_state['prediction'] = top_class_name
                 st.session_state['priority_codes'] = YOLO_PROMPTS.get(top_class_name, [])
                 st.session_state['analyzed'] = True
                 
-                # Force rerun to show step 2
                 st.rerun()
 
-# --- STEP 2: DYNAMIC QUESTIONS ---
 if st.session_state['analyzed']:
     st.divider()
-    st.subheader("Step 2: Symptom Verification")
+    st.subheader("Langkah 2: Verifikasi Gejala")
     
     pred = st.session_state['prediction']
     codes = st.session_state['priority_codes']
     
-    st.info(f"🔍 **AI Prediction:** `{pred}`")
+    st.info(f"🔍 **Prediksi AI:** `{pred}`")
     
     if not codes:
-        st.warning("⚠️ No specific verification questions defined for this disease. Please check the **Full Knowledge Base** below.")
+        st.warning("Tidak ada pertanyaan verifikasi khusus untuk penyakit ini. Silakan periksa **Basis Pengetahuan Lengkap** di bawah ini.")
     else:
-        st.write("Please verify this diagnosis by answering the specific symptoms below:")
+        st.write("Silakan verifikasi diagnosis ini dengan menjawab gejala spesifik di bawah ini:")
     
-    # Dynamic Yes/No Questions
     user_answers = {}
     for code in codes:
         question = SYMPTOM_QUESTIONS.get(code, "Unknown")
-        # Unique key is important in Streamlit
         ans = st.radio(
             f"**({code})** {question}", 
-            options=["No", "Yes"], 
-            index=0, # Default to No
+            options=["Tidak", "Ya"], 
+            index=0,
             key=f"q_{code}"
         )
-        if ans == "Yes":
+        if ans == "Ya":
             user_answers[code] = True
 
     st.divider()
-    st.markdown("**Are there other symptoms?** (If the AI missed something, check it here)")
+    st.markdown("**Apakah ada gejala lain?**")
     
-    # Full Checklist
     all_symptoms_list = [f"{k}: {v}" for k,v in SYMPTOM_QUESTIONS.items()]
-    other_checks = st.multiselect("Full Knowledge Base", all_symptoms_list)
+    other_checks = st.multiselect("Basis Pengetahuan Lengkap", all_symptoms_list)
     
-    # Process "Other" inputs
     for item in other_checks:
         code = item.split(":")[0].strip()
         user_answers[code] = True
 
-    # --- STEP 3: FORWARD CHAINING ---
-    if st.button("Step 3: Run Forward Chaining", type="primary"):
+    if st.button("Langkah 3: Jalankan Forward Chaining", type="primary"):
         user_facts = set(user_answers.keys())
         
         if not user_facts:
-            st.error("⚠️ **Inconclusive:** You selected 'No' for everything.")
+            st.error("**Tidak Meyakinkan:** Anda memilih 'Tidak' untuk semuanya.")
         else:
             matches = []
             for rule in PRODUCTION_RULES:
@@ -151,7 +144,7 @@ if st.session_state['analyzed']:
                     matches.append(rule)
             
             if matches:
-                st.success("✅ **Disease Confirmed!**")
+                st.success("**Penyakit Terkonfirmasi!**")
                 for m in matches:
                     st.markdown(f"""
                     ### {m['disease']}
@@ -159,5 +152,5 @@ if st.session_state['analyzed']:
                     - **Logic:** Found all required symptoms {m['symptoms']}
                     """)
             else:
-                st.error("❌ **No Exact Match Found**")
-                st.write("The symptoms you selected do not perfectly fit any strict rule in the knowledge base.")
+                st.error("**Tidak Ditemukan Kecocokan Pasti**")
+                st.write("Gejala yang Anda pilih tidak sepenuhnya sesuai dengan aturan ketat mana pun dalam basis pengetahuan.")