Upload app.py

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+# Load kedua model
+spinach_model = tf.keras.models.load_model("exception.h5")  # Model klasifikasi bayam
+spad_model = tf.keras.models.load_model("spad_predictor.h5", compile=False)  # Model prediksi SPAD
+
+# Fungsi gabungan
+def analyze_leaf(image):
+    try:
+        # Preprocessing
+        image_resized = image.resize((299, 299))
+        img_array = np.array(image_resized) / 255.0
+        img_array = np.expand_dims(img_array, axis=0)
+
+        # Deteksi bayam
+        pred_spinach = spinach_model.predict(img_array)[0][0]
+        is_spinach = pred_spinach > 0.5
+
+        # Hasil klasifikasi
+        classification = "✅ Bayam" if is_spinach else "❌ Bukan Bayam"
+        confidence = pred_spinach if is_spinach else 1 - pred_spinach
+        confidence_pct = f"{confidence * 100:.2f}%"
+
+        # Prediksi SPAD jika Bayam
+        spad_value = "-"
+        recommendation = ""
+        if is_spinach:
+    
+            spad_value = round(float(spad_model.predict(img_array)[0][0]), 2)
+            
+            # Rekomendasi perawatan berdasarkan nilai SPAD
+            if spad_value < 20:
+                recommendation = "❗ Perawatan: Bayam kekurangan klorofil. Diperlukan peningkatan pencahayaan atau pemupukan."
+            elif 20 <= spad_value < 40:
+                recommendation = "✅ Perawatan: Bayam dalam kondisi normal. Pastikan perawatan rutin."
+            else:
+                recommendation = "🌱 Perawatan: Bayam sehat dan kaya klorofil. Pastikan kelembapan dan suhu stabil."
+
+        return spad_value, classification, recommendation, image_resized
+
+    except Exception as e:
+        return str(e), "❌ Terjadi kesalahan", "", image
+
+
+# Antarmuka Gradio
+interface = gr.Interface(
+    fn=analyze_leaf,
+    inputs=gr.Image(type="pil", label="Upload Gambar Daun"),
+    outputs=[
+        gr.Number(label="Nilai SPAD (jika Bayam)"),
+        gr.Label(label="Status Diagnosis Daun Bayam"),
+        gr.Textbox(label="Rekomendasi Perawatan"),
+    ],
+    title="🌿 Deteksi Daun Bayam + Prediksi Nilai SPAD",
+    description="Aplikasi ini mendeteksi apakah gambar adalah bayam, dan jika ya, akan memprediksi nilai SPAD serta memberikan rekomendasi perawatan.",
+    theme="soft"
+)
+
+# Jalankan secara lokal
+if __name__ == "__main__":
+    interface.launch()