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| import math | |
| import requests | |
| from app.model import model | |
| # Must match data.yaml: ['Accident', 'Non-accident', 'Fire'] | |
| CLASS_NAMES = {0: "Accident", 1: "Non-accident", 2: "Fire"} | |
| ALERT_CLASSES = {"Accident", "Fire"} | |
| def predict_image(file_path, conf_threshold=0.3): | |
| """Run YOLO inference on an image and return detections list.""" | |
| results = model(file_path, conf=conf_threshold, verbose=False) | |
| result = results[0] | |
| detections = [] | |
| for box in result.boxes: | |
| cls_id = int(box.cls[0]) | |
| conf = float(box.conf[0]) | |
| label = CLASS_NAMES.get(cls_id, "unknown") | |
| detections.append({"label": label, "confidence": round(conf, 3)}) | |
| return detections | |
| def haversine_km(lat1, lon1, lat2, lon2): | |
| """Calculate great-circle distance in km between two lat/lon points.""" | |
| R = 6371 | |
| dlat = math.radians(lat2 - lat1) | |
| dlon = math.radians(lon2 - lon1) | |
| a = ( | |
| math.sin(dlat / 2) ** 2 | |
| + math.cos(math.radians(lat1)) | |
| * math.cos(math.radians(lat2)) | |
| * math.sin(dlon / 2) ** 2 | |
| ) | |
| return R * 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a)) | |
| def get_ip_location(): | |
| """Get approximate location via free IP geolocation (no API key).""" | |
| try: | |
| r = requests.get("http://ip-api.com/json/", timeout=5) | |
| d = r.json() | |
| if d.get("status") == "success": | |
| return { | |
| "lat": d["lat"], | |
| "lon": d["lon"], | |
| "city": d.get("city", ""), | |
| "region": d.get("regionName", ""), | |
| "country": d.get("country", ""), | |
| } | |
| except Exception: | |
| pass | |
| return None | |
| def fetch_hospitals(lat, lon, radius_m=5000): | |
| """Query OpenStreetMap Overpass API for hospitals within radius_m metres.""" | |
| query = f""" | |
| [out:json][timeout:10]; | |
| ( | |
| node["amenity"="hospital"](around:{radius_m},{lat},{lon}); | |
| way["amenity"="hospital"](around:{radius_m},{lat},{lon}); | |
| relation["amenity"="hospital"](around:{radius_m},{lat},{lon}); | |
| ); | |
| out center body; | |
| """ | |
| try: | |
| r = requests.post( | |
| "https://overpass-api.de/api/interpreter", | |
| data={"data": query}, | |
| timeout=15, | |
| ) | |
| elements = r.json().get("elements", []) | |
| except Exception: | |
| return [] | |
| hospitals = [] | |
| for el in elements: | |
| tags = el.get("tags", {}) | |
| if el["type"] == "node": | |
| h_lat, h_lon = el["lat"], el["lon"] | |
| else: | |
| c = el.get("center", {}) | |
| h_lat = c.get("lat", lat) | |
| h_lon = c.get("lon", lon) | |
| dist = haversine_km(lat, lon, h_lat, h_lon) | |
| hospitals.append( | |
| { | |
| "name": tags.get("name", "Unnamed Hospital"), | |
| "lat": h_lat, | |
| "lon": h_lon, | |
| "distance_km": round(dist, 2), | |
| "phone": tags.get("phone", tags.get("contact:phone", None)), | |
| "emergency": tags.get("emergency", "unknown"), | |
| } | |
| ) | |
| hospitals.sort(key=lambda h: h["distance_km"]) | |
| return hospitals |