import gradio as gr
import cv2
import numpy as np
import tensorflow as tf
from tensorflow.keras.applications.resnet_v2 import preprocess_input

# 1. Load Model ResNet50V2 yang udah di-training
model = tf.keras.models.load_model("model_cctv.h5")

# Urutan kategori WAJIB SAMA persis dengan output Colab (sesuai urutan alfabet folder)
CATEGORIES = ['kebakaran', 'normal'] # Disarankan alfabetis: K baru N, pastikan sesuai training!
IMG_SIZE = (224, 224)
FRAMES_PER_VIDEO = 20

def predict_video(video_path):
    if video_path is None:
        return "Upload video dulu, Bro!"
        
    cap = cv2.VideoCapture(video_path)
    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    
    if total_frames == 0:
        return "Video rusak atau tidak terbaca."
        
    interval = max(1, total_frames // FRAMES_PER_VIDEO)
    frames = []
    count = 0
    extracted = 0
    
    # 2. Ekstraksi Frame
    while cap.isOpened() and extracted < FRAMES_PER_VIDEO:
        ret, frame = cap.read()
        if not ret:
            break
        if count % interval == 0:
            # Convert BGR (OpenCV) ke RGB (Keras/Gradio)
            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            frame_res = cv2.resize(frame, IMG_SIZE)
            frames.append(frame_res)
            extracted += 1
        count += 1
    cap.release()
    
    if len(frames) == 0:
        return "Gagal mengekstrak frame dari video."
        
    # 3. Preprocessing
    frames_array = np.array(frames)
    frames_array = preprocess_input(frames_array)
    
    # 4. Prediksi dengan Model
    predictions = model.predict(frames_array)
    predicted_classes = np.argmax(predictions, axis=1)
    
   # 5. Majority Voting (Ambil Suara Terbanyak)
    counts = np.bincount(predicted_classes, minlength=len(CATEGORIES))
    majority_class_idx = np.argmax(counts)
    majority_class = CATEGORIES[majority_class_idx]
    confidence = counts[majority_class_idx] / len(predicted_classes)
    
    return f"🚨 Hasil Deteksi: {majority_class.upper()} \n📊 Tingkat Keyakinan (Majority Vote): {confidence*100:.1f}%"

# 6. Bikin Tampilan (UI) Pakai Gradio (KODE INI HARUS DI LUAR FUNGSI / TIDAK MENJOROK)
interface = gr.Interface(
    fn=predict_video,
    inputs=gr.Video(label="Upload Video CCTV (Max 30s)"),
    outputs=gr.Textbox(label="Kesimpulan Sistem"),
    title="Sistem Deteksi Anomali CCTV Pintar (Kebakaran)",
    description="Upload video CCTV mentah. Sistem akan memecahnya menjadi 20 frame, menganalisis dengan ResNet50V2, dan mengambil keputusan berdasarkan Majority Voting."
)

if __name__ == "__main__":
    interface.launch()