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.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Main_py/banana_cnn_model.keras filter=lfs diff=lfs merge=lfs -text
+Main_py/banana_vit_model.keras filter=lfs diff=lfs merge=lfs -text

.streamlit/config.toml

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+[server]
+headless = true
+port = 8501
+enableCORS = false
+
+[theme]
+base = "light"
+primaryColor = "#00B86B"
+backgroundColor = "#F0F2F6"
+secondaryBackgroundColor = "#FFFFFF"
+textColor = "#000000"
+font = "sans serif"

Main_py/X_test_combined.npy

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+size 962688

Main_py/X_train_combined.npy

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Main_py/banana_cnn_model.keras

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+oid sha256:db4edf6484881ee6e5a779d29f1c419295ae13f5eb4ca188278606dac5729b68
+size 11599896

Main_py/banana_disease_knowledge_base.json

@@ -0,0 +1,71 @@
+[
+  {
+    "Crop": "Banana",
+    "Disease": "Sigatoka Leaf Spot",
+    "Local_Name": {
+      "mr": "सिगाटोका पाने डाग",
+      "hi": "सिगाटोका पत्ती धब्बा",
+      "en": "Sigatoka Leaf Spot"
+    },
+    "Symptoms": "Small dark streaks on leaves that expand into yellow or brown patches, reducing photosynthesis.",
+    "Symptoms_HI": "पत्तियों पर छोटे काले धब्बे जो पीले या भूरे रंग के धब्बों में बदल जाते हैं और प्रकाश संश्लेषण को कम करते हैं।",
+    "Symptoms_MR": "पानांवर लहान काळे ठिपके जे नंतर पिवळसर किंवा तपकिरी डागात रूपांतरित होतात आणि प्रकाशसंश्लेषण कमी करतात.",
+    "Cause": "Caused by the fungus Mycosphaerella musicola in warm, humid environments.",
+    "Cause_HI": "गर्म और नम वातावरण में Mycosphaerella musicola नामक कवक के कारण होता है।",
+    "Cause_MR": "Mycosphaerella musicola या बुरशीमुळे उष्ण व दमट हवामानात रोग होतो.",
+    "Pesticide_Recommendation": "Use Mancozeb fungicide weekly during the early stages.",
+    "Pesticide_Recommendation_HI": "प्रारंभिक चरण में साप्ताहिक रूप से Mancozeb फफूंदनाशी का उपयोग करें।",
+    "Pesticide_Recommendation_MR": "प्रारंभिक अवस्थेत दर आठवड्याला Mancozeb फंगिसाइड वापरा.",
+    "Pesticide": "Mancozeb",
+    "Pathogen": "Mycosphaerella musicola",
+    "Management_Practices": "Ensure plant spacing, remove infected leaves, and improve airflow in plantations.",
+    "Management_HI": "पौधों की उचित दूरी बनाए रखें, संक्रमित पत्तियों को हटा दें और खेत में वायु प्रवाह बढ़ाएं।",
+    "Management_MR": "झाडांमधील योग्य अंतर ठेवा, बाधित पाने काढा आणि हवा खेळती राहील याची खात्री करा."
+  },
+  {
+    "Crop": "Banana",
+    "Disease": "Cordana Leaf Spot",
+    "Local_Name": {
+      "mr": "कॉर्डाना पाने डाग",
+      "hi": "कॉर्डाना पत्ती धब्बा",
+      "en": "Cordana Leaf Spot"
+    },
+    "Symptoms": "Oval gray-white spots on older leaves that enlarge into necrotic patches.",
+    "Symptoms_HI": "पुरानी पत्तियों पर अंडाकार भूरे-सफेद धब्बे जो बाद में सड़न में बदल जाते हैं।",
+    "Symptoms_MR": "जुन्या पानांवर अंडाकृती करड्या-पांढऱ्या डागांचे निर्माण होते जे नंतर सडतात.",
+    "Cause": "Fungal disease favored by prolonged leaf wetness and poor drainage.",
+    "Cause_HI": "लंबे समय तक पत्तियों की नमी और खराब जल निकासी के कारण होने वाला फंगल रोग।",
+    "Cause_MR": "पानांवर जास्त वेळ ओलावा राहणे आणि निकृष्ट निचरा यामुळे होणारा बुरशीजन्य रोग.",
+    "Pesticide_Recommendation": "Apply fungicide on lower leaf surfaces every 10–14 days in humid weather.",
+    "Pesticide_Recommendation_HI": "नमी वाले मौसम में हर 10–14 दिन में निचली पत्तियों पर फफूंदनाशी छिड़कें।",
+    "Pesticide_Recommendation_MR": "दमट हवामानात दर 10–14 दिवसांनी खालच्या पानांवर फंगिसाइड फवारणी करा.",
+    "Pesticide": "Mancozeb",
+    "Pathogen": "Cordana musae",
+    "Management_Practices": "Improve drainage, apply mulching, and remove infected leaves.",
+    "Management_HI": "जल निकासी सुधारें, मल्चिंग करें और संक्रमित पत्तियों को हटा दें।",
+    "Management_MR": "निचरा सुधारावा, मल्चिंग करावी आणि बाधित पाने काढावीत."
+  },
+  {
+    "Crop": "Banana",
+    "Disease": "Pestalotiopsis Leaf Spot",
+    "Local_Name": {
+      "mr": "पेस्टालोटिओप्सिस पाने डाग",
+      "hi": "पेस्टालोटिओप्सिस पत्ती धब्बा",
+      "en": "Pestalotiopsis Leaf Spot"
+    },
+    "Symptoms": "Irregular brown to black leaf spots with yellow halos on leaf edges.",
+    "Symptoms_HI": "पत्तियों के किनारों पर पीले घेरे वाले अनियमित भूरे से काले रंग के धब्बे।",
+    "Symptoms_MR": "पानांच्या कडांवर पिवळ्या वलयांसह अनियमित तपकिरी ते काळे ठिपके.",
+    "Cause": "Spread by water splash in high humidity; Pestalotiopsis fungal infection.",
+    "Cause_HI": "उच्च आर्द्रता में पानी के छींटों से फैलने वाला पेस्टालोटिओप्सिस फंगल संक्रमण।",
+    "Cause_MR": "उच्च आर्द्रतेत पाण्याचे शिंपडल्यामुळे पसरणारा पेस्टालोटिओप्सिस बुरशी संसर्ग.",
+    "Pesticide_Recommendation": "Spray appropriate fungicide during early symptoms to control spread.",
+    "Pesticide_Recommendation_HI": "प्रारंभिक लक्षणों पर उपयुक्त फफूंदनाशी का छिड़काव करें।",
+    "Pesticide_Recommendation_MR": "लक्षणे दिसताच योग्य फंगिसाइड फवारणी करा.",
+    "Pesticide": "Propiconazole",
+    "Pathogen": "Pestalotiopsis species",
+    "Management_Practices": "Avoid overhead irrigation, prune old leaves, maintain field hygiene.",
+    "Management_HI": "ऊपरी सिंचाई से बचें, पुरानी पत्तियों को काटें और खेत की स्वच्छता बनाए रखें।",
+    "Management_MR": "वरून पाणी देणे टाळा, जुनी पाने छाटावीत आणि शेत स्वच्छ ठेवावे."
+  }
+]

Main_py/banana_disease_knowledge_base_DL.json

@@ -0,0 +1,62 @@
+[
+  {
+    "Crop": "Banana",
+    "Disease": "Sigatoka Leaf Spot",
+    "Local_Name": {
+      "mr": "सिगाटोका पाने डाग",
+      "hi": "सिगाटोका पत्ती धब्बा",
+      "en": "Sigatoka Leaf Spot"
+    },
+    "Symptoms_MR": "पानांवर लहान काळे ठिपके जे नंतर पिवळसर किंवा तपकिरी डागात रूपांतरित होतात आणि प्रकाशसंश्लेषण कमी करतात.",
+    "Cause_MR": "Mycosphaerella musicola या बुरशीमुळे उष्ण व दमट हवामानात रोग होतो.",
+    "Pesticide_Recommendation_MR": "प्रारंभिक अवस्थेत दर आठवड्याला Mancozeb फंगिसाइड वापरा.",
+    "Pesticide": "Mancozeb",
+    "Pathogen": "Mycosphaerella musicola",
+    "Management_Practices_MR": "झाडांमधील योग्य अंतर ठेवा, बाधित पाने काढा आणि हवा खेळती राहील याची खात्री करा."
+  },
+  {
+    "Crop": "Banana",
+    "Disease": "Cordana Leaf Spot",
+    "Local_Name": {
+      "mr": "कॉर्डाना पाने डाग",
+      "hi": "कॉर्डाना पत्ती धब्बा",
+      "en": "Cordana Leaf Spot"
+    },
+    "Symptoms_MR": "जुन्या पानांवर अंडाकृती करड्या-पांढऱ्या डागांचे निर्माण होते जे नंतर सडतात.",
+    "Cause_MR": "पानांवर जास्त वेळ ओलावा राहणे आणि निकृष्ट निचरा यामुळे होणारा बुरशीजन्य रोग.",
+    "Pesticide_Recommendation_MR": "दमट हवामानात दर 10–14 दिवसांनी खालच्या पानांवर फंगिसाइड फवारणी करा.",
+    "Pesticide": "Mancozeb",
+    "Pathogen": "Cordana musae",
+    "Management_Practices_MR": "निचरा सुधारावा, मल्चिंग करावी आणि बाधित पाने काढावीत."
+  },
+  {
+    "Crop": "Banana",
+    "Disease": "Pestalotiopsis Leaf Spot",
+    "Local_Name": {
+      "mr": "पेस्टालोटिओप्सिस पाने डाग",
+      "hi": "पेस्टालोटिओप्सिस पत्ती धब्बा",
+      "en": "Pestalotiopsis Leaf Spot"
+    },
+    "Symptoms_MR": "पानांच्या कडांवर पिवळ्या वलयांसह अनियमित तपकिरी ते काळे ठिपके.",
+    "Cause_MR": "उच्च आर्द्रतेत पाण्याचे शिंपडल्यामुळे पसरणारा पेस्टालोटिओप्सिस बुरशी संसर्ग.",
+    "Pesticide_Recommendation_MR": "लक्षणे दिसताच योग्य फंगिसाइड फवारणी करा.",
+    "Pesticide": "Propiconazole",
+    "Pathogen": "Pestalotiopsis species",
+    "Management_Practices_MR": "वरून पाणी देणे टाळा, जुनी पाने छाटावीत आणि शेत स्वच्छ ठेवावे."
+  },
+  {
+    "Crop": "Banana",
+    "Disease": "Healthy",
+    "Local_Name": {
+      "mr": "निरोगी",
+      "hi": "स्वस्थ",
+      "en": "Healthy"
+    },
+    "Symptoms_MR": "पाने हिरवी, स्वच्छ आणि कोणतेही डाग किंवा पिवळेपणा नसलेली.",
+    "Cause_MR": "कोणताही रोग किंवा संसर्ग नाही.",
+    "Pesticide_Recommendation_MR": "फवारणीची आवश्यकता नाही; नियमित देखभाल करा.",
+    "Pesticide": "None",
+    "Pathogen": "None",
+    "Management_Practices_MR": "नियमित पाणी देणे, खतांचा वापर आणि शेत स्वच्छता राखणे."
+  }
+]

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app.py

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+import streamlit as st
+import cv2
+import numpy as np
+import os
+import json
+import joblib
+import pickle
+from typing import Dict, Any
+from sentence_transformers import SentenceTransformer, CrossEncoder
+from langdetect import detect
+from tensorflow.keras.models import Model, load_model
+from tensorflow.keras.applications.mobilenet_v2 import preprocess_input as mobilenet_preprocess
+from vit_keras.layers import ClassToken, AddPositionEmbs, TransformerBlock
+
+# ================== CACHING ==================
+@st.cache_resource
+def load_all_models():
+    cnn_model = load_model("Main_py/banana_cnn_model.keras", compile=False)
+    vit_model = load_model(
+        "Main_py/banana_vit_model.keras", compile=False,
+        custom_objects={
+            'ClassToken': ClassToken,
+            'AddPositionEmbs': AddPositionEmbs,
+            'TransformerBlock': TransformerBlock
+        }
+    )
+    cnn_feat_ext = Model(inputs=cnn_model.input, outputs=cnn_model.get_layer(index=-4).output)
+    vit_feat_ext = Model(inputs=vit_model.input, outputs=vit_model.get_layer(index=-4).output)
+    return cnn_model, vit_model, cnn_feat_ext, vit_feat_ext
+
+@st.cache_resource
+def load_all_assets():
+    scaler = joblib.load("Main_py/feature_scaler.pkl")
+    mlp_model = joblib.load("Main_py/lightgbm_model.pkl")
+    outlier_detector = joblib.load("Main_py/isolation_forest.pkl")
+    with open("Main_py/label_encoder.pkl", "rb") as f:
+        le = pickle.load(f)
+    with open("Main_py/banana_disease_knowledge_base_DL.json", "r", encoding="utf-8") as f:
+        kb_data_image = {entry["Disease"]: entry for entry in json.load(f)}
+    with open("Main_py/banana_disease_knowledge_base.json", "r", encoding="utf-8") as f:
+        kb_data_text = json.load(f)
+    return scaler, mlp_model, le, kb_data_image, kb_data_text, outlier_detector
+
+@st.cache_resource
+def load_nlp_models():
+    embedder = SentenceTransformer('sentence-transformers/paraphrase-xlm-r-multilingual-v1')
+    cross_encoder = CrossEncoder('cross-encoder/mmarco-mMiniLMv2-L12-H384-v1')
+    return embedder, cross_encoder
+
+# ================== IMAGE DIAGNOSIS ==================
+def identify_disease_from_image(image_path):
+    try:
+        img = cv2.imread(image_path)
+        if img is None:
+            raise ValueError("Image not loaded.")
+        img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        img_resized = cv2.resize(img_rgb, (224, 224))
+
+        cnn_input = np.expand_dims(img_resized / 255.0, axis=0)
+        vit_input = np.expand_dims(mobilenet_preprocess(img_resized), axis=0)
+
+        cnn_feat = cnn_feature_extractor.predict(cnn_input, verbose=0)
+        vit_feat = vit_feature_extractor.predict(vit_input, verbose=0)
+        combined_feat = np.concatenate([cnn_feat, vit_feat], axis=1)
+        combined_scaled = scaler.transform(combined_feat)
+
+        y_pred = mlp_model.predict(combined_scaled)
+        predicted_label = le.inverse_transform(y_pred)[0]
+
+        confidence = None
+        try:
+            probs = mlp_model.predict_proba(combined_scaled)
+            confidence = np.max(probs)
+        except:
+            probs = None
+
+        st.image(img_rgb, caption="Uploaded Image", use_column_width=True)
+        st.write(f"**Predicted Disease**: {predicted_label} ({confidence:.2f} confidence)" if confidence else predicted_label)
+
+        result = {
+            "predicted_disease": predicted_label,
+            "confidence": confidence,
+            "info_available": False,
+            "all_probabilities": probs[0].tolist() if probs is not None else None
+        }
+
+        normalized_pred = predicted_label.lower().replace(" ", "")
+        for disease in kb_data_image:
+            if normalized_pred in disease.lower().replace(" ", ""):
+                matched = kb_data_image[disease]
+                result["info_available"] = True
+                st.subheader("Image-Based Prediction (Marathi)")
+                st.write(f"**रोग**: {matched['Local_Name']['mr']}")
+                st.write(f"**लक्षणे**: {matched['Symptoms_MR']}")
+                st.write(f"**कारण**: {matched['Cause_MR']}")
+                st.write(f"**कीटकनाशक शिफारस**: {matched['Pesticide_Recommendation_MR']}")
+                st.write(f"**कीटकनाशक**: {matched['Pesticide']}")
+                st.write(f"**परजीवी**: {matched['Pathogen']}")
+                st.write(f"**व्यवस्थापन उपाय**: {matched['Management_Practices_MR']}")
+                break
+        else:
+            st.warning("❌ Disease not found in knowledge base.")
+        return result
+
+    except Exception as e:
+        st.error(f"Error: {e}")
+        return {"error": str(e), "predicted_disease": None}
+
+# ================== TEXT DIAGNOSIS ==================
+def detect_language(query: str) -> str:
+    try:
+        lang = detect(query)
+        return lang if lang in ["mr", "hi"] else "en"
+    except:
+        return "en"
+
+def predict_disease(query: str) -> Dict[str, Any]:
+    lang = detect_language(query)
+    query_emb = embedder.encode([query], normalize_embeddings=True)
+    symptom_key = f"Symptoms_{lang.upper()}" if lang != "en" else "Symptoms"
+    pairs = [[query, entry[symptom_key]] for entry in kb_data_text]
+    scores = cross_encoder.predict(pairs)
+    best_idx = np.argmax(scores)
+
+    if scores[best_idx] < 0.2:
+        return {
+            "message": {
+                "mr": "हा रोग आमच्या डेटाबेसमध्ये नाही.",
+                "hi": "यह रोग हमारे डेटाबेस में नहीं है।",
+                "en": "This disease is not in our database."
+            }[lang]
+        }
+
+    entry = kb_data_text[best_idx]
+    return {
+        "Crop": entry["Crop"],
+        "Disease": entry["Local_Name"][lang],
+        "Symptoms": entry[symptom_key],
+        "Cause": entry.get(f"Cause_{lang.upper()}", entry["Cause"]),
+        "Pesticide_Recommendation": entry.get(f"Pesticide_Recommendation_{lang.upper()}", entry["Pesticide_Recommendation"]),
+        "Pesticide": entry["Pesticide"],
+        "Pathogen": entry["Pathogen"],
+        "Management_Practices": entry.get(f"Management_{lang.upper()}", entry["Management_Practices"])
+    }
+
+# ================== UI ==================
+st.set_page_config(page_title="Banana Disease Detection", layout="centered")
+
+st.title("🍌 Banana Disease Detection App")
+st.write("Detect banana crop diseases using image or symptom query in Marathi, Hindi, or English.")
+
+option = st.radio("Choose input method:", ("Image Only", "Text Only", "Both"))
+
+# Load all models & assets once
+cnn_model, vit_model, cnn_feature_extractor, vit_feature_extractor = load_all_models()
+scaler, mlp_model, le, kb_data_image, kb_data_text, outlier_detector = load_all_assets()
+embedder, cross_encoder = load_nlp_models()
+
+# Image input
+if option in ["Image Only", "Both"]:
+    st.subheader("📷 Upload Banana Leaf Image")
+    uploaded_image = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])
+    if uploaded_image:
+        temp_path = "temp_image.jpg"
+        with open(temp_path, "wb") as f:
+            f.write(uploaded_image.getbuffer())
+        identify_disease_from_image(temp_path)
+        os.remove(temp_path)
+
+# Text input
+if option in ["Text Only", "Both"]:
+    st.subheader("📝 Enter Symptoms")
+    symptoms = st.text_area("Describe the symptoms (Marathi, Hindi, or English):")
+    if symptoms and st.button("Predict Disease from Text"):
+        result = predict_disease(symptoms)
+        if "message" in result:
+            st.warning(result["message"])
+        else:
+            st.subheader("Text-Based Prediction")
+            st.write(f"**Crop**: {result['Crop']}")
+            st.write(f"**Disease**: {result['Disease']}")
+            st.write(f"**Symptoms**: {result['Symptoms']}")
+            st.write(f"**Cause**: {result['Cause']}")
+            st.write(f"**Pesticide Recommendation**: {result['Pesticide_Recommendation']}")
+            st.write(f"**Pesticide**: {result['Pesticide']}")
+            st.write(f"**Pathogen**: {result['Pathogen']}")
+            st.write(f"**Management Practices**: {result['Management_Practices']}")

requirements.txt

@@ -0,0 +1,14 @@
+streamlit==1.35.0
+tensorflow==2.11.0        # ⚠️ Use this version instead of 2.12.0
+opencv-python==4.11.0.86
+numpy==1.23.5
+pandas==2.3.0
+matplotlib==3.10.3
+scikit-learn==1.7.0
+xgboost==3.0.2
+seaborn==0.13.2
+vit-keras==0.1.2
+transformers==4.52.4
+sentence-transformers==4.1.0
+langdetect==1.0.9
+joblib==1.5.1

runtime.txt

@@ -0,0 +1 @@
+python-3.10