Create utils.py

utils.py

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+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()]