Multi-devices Python API

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Good afternoon!
At the moment, I’m testing the code from HailoRT 4.20.0 User Guides using the multi-device startup Python API. The model is used compiled from HailoModelZoo yolov8m.hef
When running this code, there is absolutely no detection result.
Tell me, please, what could be the problem?

import numpy as np
from hailo_platform import (
    HEF,
    Device,
    VDevice,
    HailoStreamInterface,
    InferVStreams,
    ConfigureParams,
    InputVStreamParams,
    OutputVStreamParams,
    InputVStreams,
    OutputVStreams,
    FormatType,
    HailoSchedulingAlgorithm
)
import cv2
from threading import Thread


def infer(network_group, input_vstreams_params, output_vstreams_params, input_data):
    rep_count = 100
    with InferVStreams(network_group, input_vstreams_params, output_vstreams_params) as infer_pipeline:
        for i in range(rep_count):
            infer_results = infer_pipeline.infer(input_data)
            print(f"Итерация {i + 1}/{rep_count}")
            for stream_name, result in infer_results.items():
                if hasattr(result, 'shape'):
                    print(f"Results for {stream_name}: shape = {result.shape}")
                else:
                    print(f"Results for {stream_name}: {result}")

def create_vdevice_and_infer(hef):
    params = VDevice.create_params()
    params.scheduling_algorithm = HailoSchedulingAlgorithm.ROUND_ROBIN
    params.multi_process_service = True
    params.device_count = 2
    params.group_id = "SHARED"

    with VDevice(params=params) as target:
        configure_params = ConfigureParams.create_from_hef(hef=hef,
                                                           interface=HailoStreamInterface.PCIe)
        # model_name = hef.get_network_group_names()[0]
        # batch_size = 1
        # configure_params[model_name].batch_size = batch_size
        
        network_groups = target.configure(hef, configure_params)
        network_group = network_groups[0]

        input_vstreams_params = InputVStreamParams.make(
            network_group,
            format_type=FormatType.FLOAT32,
        )
        output_vstreams_params = OutputVStreamParams.make(
            network_group,
            format_type=FormatType.FLOAT32
        )

        input_vstream_info = hef.get_input_vstream_infos()[0]        
        image_height, image_width, channels = input_vstream_info.shape

        image_path = 'yolo_on_hailo8/input-images/input_image0.jpeg'
        image = cv2.imread(image_path)
        if image is None:
            raise FileNotFoundError(f"Images {image_path} not found")

        resized_image = cv2.resize(image, (image_width, image_height))
        rgb_image = cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB)
        input_data = np.expand_dims(rgb_image, axis=0).astype(np.uint8) 
        input_data = input_data.astype(np.float32) / 255.0
        input_data = {input_vstream_info.name: input_data}
        
        infer(network_group, input_vstreams_params, output_vstreams_params, input_data)


if __name__ == "__main__":
    hef_path = "yolov8x.hef"
    hef = HEF(hef_path)

    infer_process = Thread(target=create_vdevice_and_infer, args=(hef,))
    infer_process.start()
    infer_process.join()
    print('Done inference')