services/thermal_service.py

from transformers import pipeline
import cv2

# Load DETR model from Hugging Face
object_detector = pipeline("object-detection", model="facebook/detr-resnet-50")

def detect_thermal_anomalies(image_path):
    """
    Simulate thermal anomalies using DETR object detection.
    If an object has a high confidence and occupies a big bounding box, simulate a "hotspot."
    """
    image = cv2.imread(image_path)
    results = object_detector(image)

    anomalies = []
    for result in results:
        score = result.get('score', 0)
        box = result.get('box', {})
        width = box.get('width', 0)
        height = box.get('height', 0)
        area = width * height

        # Simulate: large bounding boxes + high score = thermal anomaly
        if score > 0.7 and area > 5000:  # adjust thresholds if needed
            anomalies.append({
                "label": result.get('label', ''),
                "score": score,
                "bbox": box
            })

    return anomalies