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from ultralytics import YOLO | |
import cv2 | |
import numpy as np | |
import os | |
# Load YOLO model (custom-trained or pretrained with compatible classes) | |
model = YOLO("yolov8n.pt") # Replace with "lbw_yolov8.pt" if custom-trained | |
# Target class IDs — update based on your custom model class mapping | |
CLASS_NAMES = { | |
0: "ball", | |
1: "bat", | |
2: "pad", | |
3: "stump", | |
4: "player" | |
} | |
def detect_lbw_event(frames): | |
""" | |
Detects ball, bat, stump, and pad in each frame. | |
Identifies impact and prepares coordinates for trajectory modeling. | |
Returns: | |
dict: { | |
"ball_positions": [x, y] list per frame, | |
"impact_frame": int, | |
"impact_type": str, | |
"objects_per_frame": [ | |
{"ball": (x, y), "pad": (x, y), ...} | |
] | |
} | |
""" | |
ball_positions = [] | |
impact_frame = -1 | |
impact_type = None | |
objects_per_frame = [] | |
for idx, frame in enumerate(frames): | |
results = model(frame)[0] | |
frame_objects = {} | |
for det in results.boxes.data: | |
x1, y1, x2, y2, conf, cls = det.cpu().numpy() | |
class_id = int(cls) | |
class_name = CLASS_NAMES.get(class_id, "unknown") | |
center_x = int((x1 + x2) / 2) | |
center_y = int((y1 + y2) / 2) | |
frame_objects[class_name] = (center_x, center_y) | |
if class_name == "ball": | |
ball_positions.append((idx, center_x, center_y)) | |
objects_per_frame.append(frame_objects) | |
# Basic impact logic: ball overlaps pad or bat | |
if "ball" in frame_objects and ("pad" in frame_objects or "bat" in frame_objects): | |
bx, by = frame_objects["ball"] | |
if "pad" in frame_objects: | |
px, py = frame_objects["pad"] | |
if abs(bx - px) < 30 and abs(by - py) < 30: | |
impact_frame = idx | |
impact_type = "pad" | |
break | |
if "bat" in frame_objects: | |
tx, ty = frame_objects["bat"] | |
if abs(bx - tx) < 30 and abs(by - ty) < 30: | |
impact_frame = idx | |
impact_type = "bat" | |
break | |
return { | |
"ball_positions": ball_positions, | |
"impact_frame": impact_frame, | |
"impact_type": impact_type, | |
"objects_per_frame": objects_per_frame | |
} | |