Spaces:
Sleeping
Sleeping
| import cv2 | |
| import numpy as np | |
| from ultralytics import YOLO | |
| import os | |
| import random | |
| # Load YOLOv8m-seg model for crack detection | |
| BASE_DIR = os.path.dirname(os.path.abspath(__file__)) | |
| MODEL_PATH = os.path.join(BASE_DIR, "../models/yolov8m-seg.pt") | |
| model = YOLO(MODEL_PATH) | |
| def detect_cracks_and_objects(frame): | |
| """ | |
| Detect cracks and other objects in a frame using YOLOv8m-seg. | |
| Args: | |
| frame: Input frame (numpy array) | |
| Returns: | |
| list: List of detected items with type, label, coordinates, confidence, and severity | |
| """ | |
| # Run YOLOv8 inference | |
| results = model(frame) | |
| detected_items = [] | |
| line_counter = 1 # Initialize counter for numbered labels | |
| # Process detections | |
| for r in results: | |
| for box in r.boxes: | |
| conf = float(box.conf[0]) | |
| if conf < 0.5: | |
| continue | |
| cls = int(box.cls[0]) | |
| label = model.names[cls] | |
| if label not in ["crack", "pothole", "object"]: # Assuming these classes exist | |
| continue | |
| xyxy = box.xyxy[0].cpu().numpy() | |
| x_min, y_min, x_max, y_max = map(int, xyxy) | |
| # Simulate severity for cracks | |
| severity = None | |
| if label == "crack": | |
| severity = random.choice(["low", "medium", "high"]) | |
| # Add numbered label | |
| detection_label = f"Line {line_counter} - {label.capitalize()} (Conf: {conf:.2f})" | |
| item = { | |
| "type": label, | |
| "label": detection_label, | |
| "confidence": conf, | |
| "coordinates": [x_min, y_min, x_max, y_max] | |
| } | |
| if severity: | |
| item["severity"] = severity | |
| detected_items.append(item) | |
| line_counter += 1 | |
| return detected_items |