# app.py (All modules now in same directory)

import streamlit as st
import cv2
from video_service import get_video_frame
from detection_service import detect_objects
from thermal_service import detect_thermal_anomalies
from shadow_detection import detect_shadow_coverage
from salesforce_dispatcher import send_to_salesforce
import os

st.set_page_config(page_title="Solar Surveillance", layout="wide")
st.title("🔭 Solar Panel Surveillance - Drone + AI + Salesforce")

video_option = st.selectbox("Choose a Simulation Feed", [
    "drone_day.mp4", "night_intrusion.mp4", "thermal_hotspot.mp4", "shadow_dust_issue.mp4"
])

if st.button("Start Monitoring"):
    frame_gen = get_video_frame(f"data/{video_option}")
    frame_placeholder = st.empty()

    for frame in frame_gen:
        temp_path = "temp.jpg"
        cv2.imwrite(temp_path, frame)

        detections = detect_objects(temp_path)
        thermal = detect_thermal_anomalies(temp_path)
        shadow_flag = detect_shadow_coverage(temp_path)

        alert_payload = {
            "detections": detections,
            "thermal": bool(thermal),
            "shadow_issue": shadow_flag,
        }

        send_to_salesforce(alert_payload)

        frame_placeholder.image(frame, channels="BGR")

# video_service.py

import cv2

def get_video_frame(video_path):
    cap = cv2.VideoCapture(video_path)
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        yield frame
    cap.release()

# detection_service.py

from transformers import pipeline
import cv2

object_detector = pipeline("object-detection", model="facebook/detr-resnet-50")

def detect_objects(image_path):
    image = cv2.imread(image_path)
    results = object_detector(image)
    return [r for r in results if r['score'] > 0.7]

# thermal_service.py

try:
    from ultralytics import YOLO
    thermal_model = YOLO("models/thermal_model.pt")
except Exception as e:
    thermal_model = None
    print("⚠️ Thermal model could not be loaded:", e)

def detect_thermal_anomalies(image_path):
    if not thermal_model:
        return []
    results = thermal_model(image_path)
    flagged = []
    for r in results:
        if hasattr(r, 'temperature') and r.temperature > 75:
            flagged.append(r)
    return flagged

# shadow_detection.py

import random

def detect_shadow_coverage(image_path):
    shadow_percent = random.randint(25, 40)
    return shadow_percent > 30

# salesforce_dispatcher.py

import requests
import json

SALESFORCE_WEBHOOK_URL = "https://your-salesforce-instance/services/web-to-case"

def send_to_salesforce(payload):
    alert_type = "Intrusion" if any(d["label"] == "person" for d in payload["detections"]) else "Anomaly"
    summary = {
        "Alert_Type__c": alert_type,
        "ThermalFlag__c": payload["thermal"],
        "ShadowFlag__c": payload["shadow_issue"],
        "Confidence_Score__c": max([d["score"] for d in payload["detections"]], default=0)
    }
    headers = {"Content-Type": "application/json"}
    try:
        response = requests.post(SALESFORCE_WEBHOOK_URL, json=summary, headers=headers)
        response.raise_for_status()
    except requests.exceptions.RequestException as e:
        print("❌ Error sending to Salesforce:", e)