yolo_ball_detector.py

from ultralytics import YOLO
import cv2

# ✅ Use the pretrained YOLOv8n model (no custom model required)
model = YOLO("yolov8n.pt")

def detect_ball_yolo(frame):
    results = model(frame, verbose=False)[0]
    ball_coords = []

    for box in results.boxes:
        cls = int(box.cls[0])
        conf = float(box.conf[0])
        # 🏏 Sports ball class in COCO = 32
        if cls == 32 and conf > 0.4:
            x1, y1, x2, y2 = map(int, box.xyxy[0])
            cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
            ball_coords.append((cx, cy))

    # Only return the most confident detection
    return ball_coords[:1] if ball_coords else []