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8b483f2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | 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 |