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app.py

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+import torch
+import torch.nn as nn
+from torchvision import transforms
+from PIL import Image
+import gradio as gr
+import networkx as nx
+import os
+from transformers import AutoModel, AutoConfig
+from openai import OpenAI
+import json  # for black JSON
+import gdown
+
+# .....................................
+MODEL_PATH = "best.pt"
+if not os.path.exists(MODEL_PATH):
+    # Replace FILE_ID with Google Drive file ID
+    file_id = "1bGRLEC2_5GB53E-zEVH1Z4EQdKGA-YGI"
+    url = f"https://drive.google.com/uc?id={file_id}"
+    print("Downloading model from Google Drive...")
+    gdown.download(url, MODEL_PATH, quiet=False)
+
+
+# -------------------------------
+# Load Knowledge Graph + Symptom Map
+# -------------------------------
+# 1. Create Extended Knowledge Graph (KG)
+# -------------------------------
+G = nx.DiGraph()
+
+# -------------------------------
+# Symptoms → Diseases
+# -------------------------------
+# Apple
+G.add_edge("Olive-brown velvety spots on leaves/fruits", "Apple___Apple_scab")
+G.add_edge("Dark sunken lesions with concentric rings", "Apple___Black_rot")
+G.add_edge("Orange/yellow spots with black centers", "Apple___Cedar_apple_rust")
+G.add_edge("No visible disease", "Apple___healthy")
+
+# Blueberry
+G.add_edge("No visible disease", "Blueberry___healthy")
+
+# Cherry
+G.add_edge("White powdery coating on leaves", "Cherry_(including_sour)___Powdery_mildew")
+G.add_edge("No visible disease", "Cherry_(including_sour)___healthy")
+
+# Corn
+G.add_edge("Gray/tan lesions with dark borders", "Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot")
+G.add_edge("Small reddish-brown pustules on leaves", "Corn_(maize)___Common_rust_")
+G.add_edge("Cigar-shaped gray-green lesions on leaves", "Corn_(maize)___Northern_Leaf_Blight")
+G.add_edge("No visible disease", "Corn_(maize)___healthy")
+
+# Grape
+G.add_edge("Circular black spots on leaves/fruits", "Grape___Black_rot")
+G.add_edge("Interveinal chlorosis, necrosis (black measles)", "Grape___Esca_(Black_Measles)")
+G.add_edge("Irregular brown spots with yellow halo", "Grape___Leaf_blight_(Isariopsis_Leaf_Spot)")
+G.add_edge("No visible disease", "Grape___healthy")
+
+# Orange
+G.add_edge("Yellow shoots, mottled leaves, misshapen fruits", "Orange___Haunglongbing_(Citrus_greening)")
+
+# Peach 
+G.add_edge("Small dark water-soaked spots on leaves", "Peach___Bacterial_spot")
+G.add_edge("No visible disease", "Peach___healthy")
+
+# Pepper (typo fix: Pepper instead of 'pper,_bell')
+G.add_edge("Brown lesions with yellow halo", "Pepper,_bell___Bacterial_spot")
+G.add_edge("No visible disease", "Pepper,_bell___healthy")
+
+# Potato
+G.add_edge("Dark concentric spots on leaves", "Potato___Early_blight")
+G.add_edge("Large irregular brown/black lesions", "Potato___Late_blight")
+G.add_edge("No visible disease", "Potato___healthy")
+
+# Raspberry
+G.add_edge("No visible disease", "Raspberry___healthy")
+
+# Soybean
+G.add_edge("No visible disease", "Soybean___healthy")
+
+# Squash
+G.add_edge("White powdery patches on leaves", "Squash___Powdery_mildew")
+
+# Strawberry
+G.add_edge("Irregular brown leaf margins, scorching", "Strawberry___Leaf_scorch")
+G.add_edge("No visible disease", "Strawberry___healthy")
+
+# Tomato
+G.add_edge("Water-soaked brown spots on leaves", "Tomato___Bacterial_spot")
+G.add_edge("Concentric rings, target-like spots", "Tomato___Early_blight")
+G.add_edge("Large dark blotches with fuzzy growth", "Tomato___Late_blight")
+G.add_edge("Yellow patches on upper leaf, fuzzy underside", "Tomato___Leaf_Mold")
+G.add_edge("Small circular dark spots with yellow halo", "Tomato___Septoria_leaf_spot")
+G.add_edge("White/yellow stippling + webbing", "Tomato___Spider_mites Two-spotted_spider_mite")
+G.add_edge("Brown/black target-like spots", "Tomato___Target_Spot")
+G.add_edge("Leaf curling + yellow mosaic", "Tomato___Tomato_Yellow_Leaf_Curl_Virus")
+G.add_edge("Mosaic mottling on leaves", "Tomato___Tomato_mosaic_virus")
+G.add_edge("No visible disease", "Tomato___healthy")
+
+# -------------------------------
+# Diseases → Treatments
+# -------------------------------
+# Apple
+G.add_edge("Apple___Apple_scab", "Fungicides (captan, myclobutanil), prune infected leaves")
+G.add_edge("Apple___Black_rot", "Remove mummified fruits, use fungicides")
+G.add_edge("Apple___Cedar_apple_rust", "Remove nearby junipers, apply fungicides")
+G.add_edge("Apple___healthy", "No treatment needed")
+
+# Blueberry
+G.add_edge("Blueberry___healthy", "No treatment needed")
+
+# Cherry
+G.add_edge("Cherry_(including_sour)___Powdery_mildew", "Fungicides: sulfur, myclobutanil")
+G.add_edge("Cherry_(including_sour)___healthy", "No treatment needed")
+
+# Corn
+G.add_edge("Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot", "Use resistant hybrids, fungicides")
+G.add_edge("Corn_(maize)___Common_rust_", "Resistant hybrids, fungicide if severe")
+G.add_edge("Corn_(maize)___Northern_Leaf_Blight", "Crop rotation, resistant varieties, fungicides")
+G.add_edge("Corn_(maize)___healthy", "No treatment needed")
+
+# Grape
+G.add_edge("Grape___Black_rot", "Fungicides (mancozeb, myclobutanil), prune infected vines")
+G.add_edge("Grape___Esca_(Black_Measles)", "Remove infected wood, fungicides not very effective")
+G.add_edge("Grape___Leaf_blight_(Isariopsis_Leaf_Spot)", "Remove infected leaves, fungicides")
+G.add_edge("Grape___healthy", "No treatment needed")
+
+# Orange
+G.add_edge("Orange___Haunglongbing_(Citrus_greening)", "No cure, control psyllid vector, use resistant rootstocks")
+
+# Peach
+G.add_edge("Peach___Bacterial_spot", "Copper fungicides, resistant varieties")
+G.add_edge("Peach___healthy", "No treatment needed")
+
+# Pepper
+G.add_edge("Pepper,_bell___Bacterial_spot", "Use copper-based bactericides, resistant cultivars")
+G.add_edge("Pepper,_bell___healthy", "No treatment needed")
+
+# Potato
+G.add_edge("Potato___Early_blight", "Use fungicides: Mancozeb, Chlorothalonil")
+G.add_edge("Potato___Late_blight", "Copper-based fungicides, resistant varieties")
+G.add_edge("Potato___healthy", "No treatment needed")
+
+# Raspberry
+G.add_edge("Raspberry___healthy", "No treatment needed")
+
+# Soybean
+G.add_edge("Soybean___healthy", "No treatment needed")
+
+# Squash
+G.add_edge("Squash___Powdery_mildew", "Sulfur-based fungicides, resistant varieties")
+
+# Strawberry
+G.add_edge("Strawberry___Leaf_scorch", "Remove infected leaves, apply fungicides")
+G.add_edge("Strawberry___healthy", "No treatment needed")
+
+# Tomato
+G.add_edge("Tomato___Bacterial_spot", "Copper sprays, avoid overhead irrigation")
+G.add_edge("Tomato___Early_blight", "Fungicides: Chlorothalonil, crop rotation")
+G.add_edge("Tomato___Late_blight", "Copper fungicides, remove infected plants")
+G.add_edge("Tomato___Leaf_Mold", "Fungicides: Chlorothalonil, improve ventilation")
+G.add_edge("Tomato___Septoria_leaf_spot", "Apply fungicides, remove infected leaves")
+G.add_edge("Tomato___Spider_mites Two-spotted_spider_mite", "Insecticidal soap, neem oil, predatory mites")
+G.add_edge("Tomato___Target_Spot", "Fungicides: Chlorothalonil, Mancozeb")
+G.add_edge("Tomato___Tomato_Yellow_Leaf_Curl_Virus", "No cure: use resistant varieties, control whiteflies")
+G.add_edge("Tomato___Tomato_mosaic_virus", "Remove infected plants, disinfect tools")
+G.add_edge("Tomato___healthy", "No treatment needed")
+
+# -------------------------------
+# 2. Map Model Predictions → Symptoms
+# -------------------------------
+symptom_map = {
+    "Apple___Apple_scab": "Olive-brown velvety spots on leaves/fruits",
+    "Apple___Black_rot": "Dark sunken lesions with concentric rings",
+    "Apple___Cedar_apple_rust": "Orange/yellow spots with black centers",
+    "Apple___healthy": "No visible disease",
+
+    "Blueberry___healthy": "No visible disease",
+
+    "Cherry_(including_sour)___Powdery_mildew": "White powdery coating on leaves",
+    "Cherry_(including_sour)___healthy": "No visible disease",
+
+    "Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot": "Gray/tan lesions with dark borders",
+    "Corn_(maize)___Common_rust_": "Small reddish-brown pustules on leaves",
+    "Corn_(maize)___Northern_Leaf_Blight": "Cigar-shaped gray-green lesions on leaves",
+    "Corn_(maize)___healthy": "No visible disease",
+
+    "Grape___Black_rot": "Circular black spots on leaves/fruits",
+    "Grape___Esca_(Black_Measles)": "Interveinal chlorosis, necrosis (black measles)",
+    "Grape___Leaf_blight_(Isariopsis_Leaf_Spot)": "Irregular brown spots with yellow halo",
+    "Grape___healthy": "No visible disease",
+
+    "Orange___Haunglongbing_(Citrus_greening)": "Yellow shoots, mottled leaves, misshapen fruits",
+
+    "Peach___Bacterial_spot": "Small dark water-soaked spots on leaves",
+    "Peach___healthy": "No visible disease",
+
+    "Pepper,_bell___Bacterial_spot": "Brown lesions with yellow halo",
+    "Pepper,_bell___healthy": "No visible disease",
+
+    "Potato___Early_blight": "Dark concentric spots on leaves",
+    "Potato___Late_blight": "Large irregular brown/black lesions",
+    "Potato___healthy": "No visible disease",
+
+    "Raspberry___healthy": "No visible disease",
+    "Soybean___healthy": "No visible disease",
+
+    "Squash___Powdery_mildew": "White powdery patches on leaves",
+
+    "Strawberry___Leaf_scorch": "Irregular brown leaf margins, scorching",
+    "Strawberry___healthy": "No visible disease",
+
+    "Tomato___Bacterial_spot": "Water-soaked brown spots on leaves",
+    "Tomato___Early_blight": "Concentric rings, target-like spots",
+    "Tomato___Late_blight": "Large dark blotches with fuzzy growth",
+    "Tomato___Leaf_Mold": "Yellow patches on upper leaf, fuzzy underside",
+    "Tomato___Septoria_leaf_spot": "Small circular dark spots with yellow halo",
+    "Tomato___Spider_mites Two-spotted_spider_mite": "White/yellow stippling + webbing",
+    "Tomato___Target_Spot": "Brown/black target-like spots",
+    "Tomato___Tomato_Yellow_Leaf_Curl_Virus": "Leaf curling + yellow mosaic",
+    "Tomato___Tomato_mosaic_virus": "Mosaic mottling on leaves",
+    "Tomato___healthy": "No visible disease"
+}
+
+# -------------------------------
+# Model Setup
+# -------------------------------
+class DinoClassifier(nn.Module):
+    def __init__(self, base_model, num_classes, hidden_size):
+        super().__init__()
+        self.base = base_model
+        self.classifier = nn.Linear(hidden_size, num_classes)
+
+    def forward(self, x):
+        outputs = self.base(x)
+        pooled = outputs.last_hidden_state.mean(dim=1)
+        return self.classifier(pooled)
+
+model_name = "facebook/dinov3-vits16-pretrain-lvd1689m"
+hf_token = os.environ.get("HF_TOKEN")  # Token from environment variable
+
+config = AutoConfig.from_pretrained(model_name, use_auth_token=hf_token)
+base_model = AutoModel.from_pretrained(model_name, config=config, use_auth_token=hf_token)
+
+
+num_classes = 38
+model = DinoClassifier(base_model, num_classes, config.hidden_size)
+checkpoint = torch.load(MODEL_PATH, map_location="cpu")
+model.load_state_dict(checkpoint["model_state_dict"])
+class_names = checkpoint["classes"]
+model.eval()
+
+# -------------------------------
+# Image Preprocessing
+# -------------------------------
+val_test_tfms = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=(0.5, 0.5, 0.5),
+                         std=(0.5, 0.5, 0.5)),
+])
+
+# -------------------------------
+# OpenAI API Setup
+# -------------------------------
+client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
+
+# -------------------------------
+# Prediction Pipeline (fast)
+# -------------------------------
+def predict_pipeline(image: Image.Image, get_explanation: bool = True):
+    # Preprocess
+    x = val_test_tfms(image).unsqueeze(0)
+
+    # Prediction
+    with torch.no_grad():
+        logits = model(x)
+        pred_idx = logits.argmax(1).item()
+        pred_class = class_names[pred_idx]
+
+    # KG Lookup
+    symptom = symptom_map.get(pred_class, "Unknown")
+    treatment = list(G.neighbors(pred_class)) if pred_class in G else ["No treatment found"]
+
+    # JSON summary (black text)
+    result_json = {
+        "Predicted Disease": pred_class,
+        "Symptom": symptom,
+        "Treatment": ", ".join(treatment),
+    }
+
+    # GPT explanation (optional, can be skipped to speed up)
+    if get_explanation:
+        prompt = f"""
+        You are an agriculture expert.
+        Disease: {pred_class}
+        Symptom: {symptom}
+        Treatment: {', '.join(treatment)}
+
+        Provide a **detailed explanation** in Markdown with sections:
+        1. What causes it  
+        2. How to control it  
+        3. Prevention methods
+        """
+        try:
+            response = client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[{"role": "user", "content": prompt}],
+                temperature=0.7
+            )
+            llm_text = response.choices[0].message.content
+        except Exception as e:
+            llm_text = f"**LLM Error:** {str(e)}"
+    else:
+        llm_text = "GPT explanation skipped for speed."
+
+    return json.dumps(result_json, indent=2), llm_text
+
+# -------------------------------
+# Gradio App (fast, black JSON)
+# -------------------------------
+demo = gr.Interface(
+    fn=predict_pipeline,
+    inputs=[gr.Image(type="pil")],
+    outputs=[
+        gr.Textbox(label="📊 Prediction Summary", lines=10, interactive=False),
+        gr.Markdown(label="📖 Detailed Explanation")
+    ],
+    title="🌱 Plant Disease Detection with KG + GPT-4o-mini",
+    description="Upload a plant leaf image to detect disease, get symptoms, treatment, and optionally an expert explanation."
+)
+
+if __name__ == "__main__":
+    demo.launch()
+

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed0ce22248f5f197a0b9b69a17b912a60dae47322003f017abb0386c4a4faf85
+size 259545297

requirements.txt

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+torch
+torchvision
+transformers
+timm
+gradio
+networkx
+Pillow
+openai
+gdown