services/thermal_service.py

# services/thermal_service.py

import cv2
from transformers import pipeline

# Load HuggingFace DETR model
thermal_detector = pipeline("object-detection", model="facebook/detr-resnet-50")

def detect_thermal_anomalies(image_path):
    results = thermal_detector(image_path)  # ✅ directly pass path, not NumPy image!

    thermal_boxes = []
    for result in results:
        if result['score'] > 0.7:
            box = result['box']
            thermal_boxes.append(box)

    return thermal_boxes

def overlay_thermal_boxes(image_path, boxes):
    image = cv2.imread(image_path)

    for box in boxes:
        xmin, ymin, xmax, ymax = box['xmin'], box['ymin'], box['xmax'], box['ymax']
        cv2.rectangle(image, (xmin, ymin), (xmax, ymax), (0, 0, 255), 2)
        cv2.putText(image, 'Hotspot', (xmin, ymin - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

    return image