import cv2
import numpy as np

def get_class_color(class_id):
    """Generates a consistent color for each class ID."""
    np.random.seed(class_id)
    return tuple(np.random.randint(0, 255, 3).tolist())

def draw_box(frame, x1, y1, x2, y2, conf, class_id, class_name):
    """Draws a bounding box and label on the frame (BGR format)."""
    x1, y1, x2, y2 = map(int, [x1, y1, x2, y2])
    color = get_class_color(class_id)
    label = f"{class_name} {conf:.2f}"
    
    cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
    cv2.putText(frame, label, (x1, max(0, y1 - 10)),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)

def apply_nms(boxes, iou_thresh=0.4):
    """
    Applies Non-Maximum Suppression (NMS) to filter overlapping bounding boxes.
    """
    if not boxes:
        return []

    xywh = []
    confs = []
    for b in boxes:
        x1, y1, x2, y2, c, cid, cname = b
        w = x2 - x1
        h = y2 - y1
        xywh.append([x1, y1, w, h])
        confs.append(c)

    xywh = np.array(xywh)
    confs = np.array(confs)

    idxs = cv2.dnn.NMSBoxes(xywh.tolist(), confs.tolist(), 0.25, iou_thresh)
    if idxs is None or len(idxs) == 0:
        return []

    return [boxes[i] for i in idxs.flatten()]