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import numpy as np
import pyarrow as pa
from dora import DoraStatus
from ultralytics import YOLO
pa.array([])
CAMERA_WIDTH = 960
CAMERA_HEIGHT = 540
model = YOLO("yolov8n.pt")
class Operator:
"""
Infering object from images
"""
def on_event(
self,
dora_event,
send_output,
) -> DoraStatus:
if dora_event["type"] == "INPUT":
frame = (
dora_event["value"].to_numpy().reshape((CAMERA_HEIGHT, CAMERA_WIDTH, 3))
)
frame = frame[:, :, ::-1] # OpenCV image (BGR to RGB)
results = model(frame, verbose=False) # includes NMS
boxes = np.array(results[0].boxes.xyxy.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)
send_output("bbox", pa.array(arrays.ravel()), dora_event["metadata"])
return DoraStatus.CONTINUE
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