Upload app/utils.py with huggingface_hub

app/utils.py

@@ -0,0 +1,101 @@
+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