Update app.py

app.py

@@ -3,8 +3,8 @@ import json
 import gradio as gr
 import requests
 import logging
+import base64
 from PIL import Image
-import numpy as np
 from io import BytesIO
 from dotenv import load_dotenv
 
@@ -23,18 +23,18 @@ logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(
 # Plant.id API URL
 PLANT_ID_URL = "https://api.plant.id/v2/health_assessment"
 
-# Function to get disease and treatment information from Plant.id
+# Function to analyze plant health using Plant.id API
 def analyze_plant_health(image):
     try:
-        # Convert image to bytes
+        # Convert image to bytes & encode in Base64
         buffered = BytesIO()
         image.save(buffered, format="JPEG")
-        img_bytes = buffered.getvalue()
+        img_base64 = base64.b64encode(buffered.getvalue()).decode()
 
         # Send request to Plant.id API
         headers = {"Content-Type": "application/json"}
         payload = {
-            "images": [f"data:image/jpeg;base64,{img_bytes.decode()}"],
+            "images": [f"data:image/jpeg;base64,{img_base64}"],
             "organs": ["leaf"],
             "api_key": PLANT_ID_API_KEY
         }
@@ -45,29 +45,39 @@ def analyze_plant_health(image):
             return f"❌ API Error: {response.text}"
 
         data = response.json()
-        
-        if "health_assessment" not in data:
-            return "⚠️ No disease detected or insufficient data."
+
+        if "health_assessment" not in data or not data["health_assessment"].get("diseases"):
+            return "✅ No disease detected! Your plant looks healthy. 🌿"
 
         assessment = data["health_assessment"]
-        predicted_disease = assessment.get("diseases", [{}])[0].get("name", "Unknown Disease")
-        treatment = assessment.get("diseases", [{}])[0].get("treatment", "No treatment suggestions available.")
+        disease_info = assessment["diseases"][0]
+        predicted_disease = disease_info.get("name", "Unknown Disease")
+        treatment = disease_info.get("treatment", "No treatment suggestions available.")
 
-        return f"🌱 **Predicted Disease:** {predicted_disease}\n💊 **Treatment:** {treatment}"
+        return f"""
+        🌱 **Predicted Disease:** {predicted_disease}  
+        💊 **Treatment:** {treatment}  
+        """
 
     except Exception as e:
         logging.error(f"Prediction failed: {str(e)}")
         return f"❌ Error: {str(e)}"
 
-# Gradio Interface
+# Gradio Interface with Improved UI
 iface = gr.Interface(
     fn=analyze_plant_health,
-    inputs=gr.Image(type="pil", label="📸 Upload or capture a plant image"),
+    inputs=gr.Image(type="pil", label="📸 Upload or Capture a Plant Image"),
     outputs=gr.Textbox(label="🔍 Diagnosis & Treatment"),
     title="🌿 AI-Powered Plant Disease Detector",
-    description="📷 Upload a leaf image to detect plant diseases and get treatment suggestions from Plant.id API.",
+    description="""
+    📷 Upload an image of a plant leaf to detect diseases and get treatment suggestions from Plant.id API.  
+    ✅ Supports **multiple plant species**  
+    ✅ Instant **AI-powered analysis**  
+    ✅ Get **organic & chemical treatment suggestions**  
+    """,
+    theme="compact",
     allow_flagging="never",
-    theme="default",
+    examples=["example_leaf.jpg"],  # Add a sample leaf image
 )
 
 # Launch Gradio App