#!/usr/bin/env python3 # -*- coding: utf-8 -*- import os import cv2 import numpy as np from ultralytics import YOLO from dora import Node import pyarrow as pa model = YOLO("/home/peiji/yolov8n.pt") node = Node() IMAGE_WIDTH = int(os.getenv("IMAGE_WIDTH", 960)) IMAGE_HEIGHT = int(os.getenv("IMAGE_HEIGHT", 540)) for event in node: event_type = event["type"] if event_type == "INPUT": event_id = event["id"] if event_id == "image": print("[object detection] received image input") image = event["value"].to_numpy().reshape((IMAGE_HEIGHT, IMAGE_WIDTH, 3)) frame = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) frame = frame[:, :, ::-1] # OpenCV image (BGR to RGB) results = model(frame) # includes NMS # Process results boxes = np.array(results[0].boxes.xywh.cpu()) conf = np.array(results[0].boxes.conf.cpu()) label = np.array(results[0].boxes.cls.cpu()) # concatenate them together arrays = np.concatenate((boxes, conf[:, None], label[:, None]), axis=1) node.send_output("bbox", pa.array(arrays.ravel()), event["metadata"]) else: print("[object detection] ignoring unexpected input:", event_id) elif event_type == "STOP": print("[object detection] received stop") elif event_type == "ERROR": print("[object detection] error: ", event["error"]) else: print("[object detection] received unexpected event:", event_type)