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app.py

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+
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+import json
+from PIL import Image
+
+# Load model and class mapping
+model = tf.keras.models.load_model("cropguard_model.h5")
+
+with open("class_indices.json", "r") as f:
+    class_indices = json.load(f)
+
+idx_to_class = {v: k for k, v in class_indices.items()}
+
+# Human-readable labels and treatment tips
+disease_info = {
+    "Pepper__bell___Bacterial_spot": {
+        "name": "Bell Pepper — Bacterial Spot",
+        "tip": "Remove infected leaves, avoid overhead watering, apply copper-based bactericide."
+    },
+    "Pepper__bell___healthy": {
+        "name": "Bell Pepper — Healthy",
+        "tip": "No action needed. Maintain good watering and spacing practices."
+    },
+    "Potato___Early_blight": {
+        "name": "Potato — Early Blight",
+        "tip": "Remove affected foliage, rotate crops yearly, apply fungicide if severe."
+    },
+    "Potato___Late_blight": {
+        "name": "Potato — Late Blight",
+        "tip": "Highly destructive — remove infected plants immediately, apply fungicide, avoid wet foliage."
+    },
+    "Potato___healthy": {
+        "name": "Potato — Healthy",
+        "tip": "No action needed. Continue regular monitoring."
+    },
+    "Tomato_Bacterial_spot": {
+        "name": "Tomato — Bacterial Spot",
+        "tip": "Avoid overhead watering, remove infected leaves, apply copper-based spray."
+    },
+    "Tomato_Early_blight": {
+        "name": "Tomato — Early Blight",
+        "tip": "Remove lower infected leaves, mulch soil, apply fungicide preventatively."
+    },
+    "Tomato_Late_blight": {
+        "name": "Tomato — Late Blight",
+        "tip": "Act fast — highly contagious. Remove and destroy infected plants, apply fungicide."
+    },
+    "Tomato_Leaf_Mold": {
+        "name": "Tomato — Leaf Mold",
+        "tip": "Improve air circulation, reduce humidity, apply fungicide if persistent."
+    },
+    "Tomato_Septoria_leaf_spot": {
+        "name": "Tomato — Septoria Leaf Spot",
+        "tip": "Remove infected lower leaves, avoid wetting foliage, rotate crops."
+    },
+    "Tomato_Spider_mites_Two_spotted_spider_mite": {
+        "name": "Tomato — Spider Mites",
+        "tip": "Spray with insecticidal soap or neem oil, increase humidity around plants."
+    },
+    "Tomato__Target_Spot": {
+        "name": "Tomato — Target Spot",
+        "tip": "Remove infected debris, apply fungicide, improve air circulation."
+    },
+    "Tomato__Tomato_YellowLeaf__Curl_Virus": {
+        "name": "Tomato — Yellow Leaf Curl Virus",
+        "tip": "No cure — remove infected plants to prevent spread, control whiteflies (the vector)."
+    },
+    "Tomato__Tomato_mosaic_virus": {
+        "name": "Tomato — Mosaic Virus",
+        "tip": "No cure — remove and destroy infected plants, disinfect tools between use."
+    },
+    "Tomato_healthy": {
+        "name": "Tomato — Healthy",
+        "tip": "No action needed. Continue regular care and monitoring."
+    },
+}
+
+def predict_disease(img):
+    if img is None:
+        return "Please upload a leaf image.", ""
+
+    img = img.resize((224, 224))
+    img_array = np.array(img) / 255.0
+    img_array = np.expand_dims(img_array, axis=0)
+
+    preds = model.predict(img_array, verbose=0)[0]
+    pred_idx = np.argmax(preds)
+    confidence = round(float(preds[pred_idx]) * 100, 1)
+
+    raw_label = idx_to_class[pred_idx]
+    info = disease_info.get(raw_label, {"name": raw_label, "tip": "No info available."})
+
+    result = f"{info['name']}  ({confidence}% confidence)"
+    tip = f"💡 Recommendation: {info['tip']}"
+
+    # Top 3 predictions
+    top3_idx = np.argsort(preds)[::-1][:3]
+    breakdown = "Top 3 predictions:\n"
+    for idx in top3_idx:
+        lbl = disease_info.get(idx_to_class[idx], {"name": idx_to_class[idx]})["name"]
+        pct = round(float(preds[idx]) * 100, 1)
+        breakdown += f"  • {lbl}: {pct}%\n"
+
+    return result, tip, breakdown
+
+with gr.Blocks(title="CropGuard") as demo:
+    gr.Markdown("""
+    # 🌱 CropGuard — Crop Disease Detector
+    ### Upload a photo of a Tomato, Potato, or Bell Pepper leaf to detect disease
+    *Built by Samuel Yaula Dutse | MobileNetV2 Transfer Learning | 93% Accuracy*
+    """)
+
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="pil", label="Upload Leaf Image")
+            submit_btn = gr.Button("Diagnose", variant="primary")
+
+        with gr.Column():
+            result_output = gr.Textbox(label="Diagnosis", interactive=False)
+            tip_output = gr.Textbox(label="Recommendation", interactive=False)
+            breakdown_output = gr.Textbox(label="Confidence Breakdown", lines=5, interactive=False)
+
+    submit_btn.click(
+        fn=predict_disease,
+        inputs=[image_input],
+        outputs=[result_output, tip_output, breakdown_output]
+    )
+
+demo.launch()