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#!/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)
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