cluster4npu/mutliseries.py

import kp
from collections import defaultdict
from typing import Union
import os
import sys
import argparse
import time
import threading
import queue
import numpy as np
import cv2

# PWD = os.path.dirname(os.path.abspath(__file__))
# sys.path.insert(1, os.path.join(PWD, '..'))
IMAGE_FILE_PATH = r"c:\Users\mason\Downloads\kneron_plus_v3.1.2\kneron_plus\res\images\people_talk_in_street_640x640.bmp"
LOOP_TIME = 100


def _image_send_function(_device_group: kp.DeviceGroup,
                         _loop_time: int,
                         _generic_inference_input_descriptor: kp.GenericImageInferenceDescriptor,
                         _image: Union[bytes, np.ndarray],
                         _image_format: kp.ImageFormat) -> None:
    for _loop in range(_loop_time):
        try:
            _generic_inference_input_descriptor.inference_number = _loop
            _generic_inference_input_descriptor.input_node_image_list = [kp.GenericInputNodeImage(
                image=_image,
                image_format=_image_format,
                resize_mode=kp.ResizeMode.KP_RESIZE_ENABLE,
                padding_mode=kp.PaddingMode.KP_PADDING_CORNER,
                normalize_mode=kp.NormalizeMode.KP_NORMALIZE_KNERON
            )]

            kp.inference.generic_image_inference_send(device_group=device_groups[1],
                                                      generic_inference_input_descriptor=_generic_inference_input_descriptor)
        except kp.ApiKPException as exception:
            print(' - Error: inference failed, error = {}'.format(exception))
            exit(0)


def _result_receive_function(_device_group: kp.DeviceGroup,
                             _loop_time: int,
                             _result_queue: queue.Queue) -> None:
    _generic_raw_result = None

    for _loop in range(_loop_time):
        try:
            _generic_raw_result = kp.inference.generic_image_inference_receive(device_group=device_groups[1])

            if _generic_raw_result.header.inference_number != _loop:
                print(' - Error: incorrect inference_number {} at frame {}'.format(
                    _generic_raw_result.header.inference_number, _loop))

            print('.', end='', flush=True)

        except kp.ApiKPException as exception:
            print(' - Error: inference failed, error = {}'.format(exception))
            exit(0)

    _result_queue.put(_generic_raw_result)

model_path = ["C:\\Users\\mason\\Downloads\\kneron_plus_v3.1.2\\kneron_plus\\res\\models\\KL520\\yolov5-noupsample_w640h640_kn-model-zoo\\kl520_20005_yolov5-noupsample_w640h640.nef", r"C:\Users\mason\Downloads\kneron_plus_v3.1.2\kneron_plus\res\models\KL720\yolov5-noupsample_w640h640_kn-model-zoo\kl720_20005_yolov5-noupsample_w640h640.nef"]
SCPU_FW_PATH_520 = "C:\\Users\\mason\\Downloads\\kneron_plus_v3.1.2\\kneron_plus\\res\\firmware\\KL520\\fw_scpu.bin"
NCPU_FW_PATH_520 = "C:\\Users\\mason\\Downloads\\kneron_plus_v3.1.2\\kneron_plus\\res\\firmware\\KL520\\fw_ncpu.bin"
SCPU_FW_PATH_720 = "C:\\Users\\mason\\Downloads\\kneron_plus_v3.1.2\\kneron_plus\\res\\firmware\\KL720\\fw_scpu.bin"
NCPU_FW_PATH_720 = "C:\\Users\\mason\\Downloads\\kneron_plus_v3.1.2\\kneron_plus\\res\\firmware\\KL720\\fw_ncpu.bin"
device_list = kp.core.scan_devices()

grouped_devices = defaultdict(list)

for device in device_list.device_descriptor_list:
    grouped_devices[device.product_id].append(device.usb_port_id)
    
print(f"Found device groups: {dict(grouped_devices)}")

device_groups = []

for product_id, usb_port_id in grouped_devices.items():
    try:
        group = kp.core.connect_devices(usb_port_id)
        device_groups.append(group)
        print(f"Successfully connected to group for product ID {product_id} with ports{usb_port_id}")
    except kp.ApiKPException as e:
        print(f"Failed to connect to group for product ID {product_id}: {e}")
        
print(device_groups)

print('[Set Device Timeout]')
kp.core.set_timeout(device_group=device_groups[0], milliseconds=5000)
kp.core.set_timeout(device_group=device_groups[1], milliseconds=5000)
print(' - Success')

try:
    print('[Upload Firmware]')
    kp.core.load_firmware_from_file(device_group=device_groups[0],
                                    scpu_fw_path=SCPU_FW_PATH_520,
                                    ncpu_fw_path=NCPU_FW_PATH_520)
    kp.core.load_firmware_from_file(device_group=device_groups[1],
                                    scpu_fw_path=SCPU_FW_PATH_720,
                                    ncpu_fw_path=NCPU_FW_PATH_720)
    print(' - Success')
except kp.ApiKPException as exception:
    print('Error: upload firmware failed, error = \'{}\''.format(str(exception)))
    exit(0)

print('[Upload Model]')
model_nef_descriptors = []
# for group in device_groups:
model_nef_descriptor = kp.core.load_model_from_file(device_group=device_groups[0], file_path=model_path[0])
model_nef_descriptors.append(model_nef_descriptor)
model_nef_descriptor = kp.core.load_model_from_file(device_group=device_groups[1], file_path=model_path[1])
model_nef_descriptors.append(model_nef_descriptor)
print(' - Success')

"""
prepare the image
"""
print('[Read Image]')
img = cv2.imread(filename=IMAGE_FILE_PATH)
img_bgr565 = cv2.cvtColor(src=img, code=cv2.COLOR_BGR2BGR565)
print(' - Success')

"""
prepare generic image inference input descriptor
"""
print(model_nef_descriptors)
generic_inference_input_descriptor = kp.GenericImageInferenceDescriptor(
    model_id=model_nef_descriptors[1].models[0].id,
)

"""
starting inference work
"""
print('[Starting Inference Work]')
print(' - Starting inference loop {} times'.format(LOOP_TIME))
print(' - ', end='')
result_queue = queue.Queue()

send_thread = threading.Thread(target=_image_send_function, args=(device_groups[1],
                                                                    LOOP_TIME,
                                                                    generic_inference_input_descriptor,
                                                                    img_bgr565,
                                                                    kp.ImageFormat.KP_IMAGE_FORMAT_RGB565))

receive_thread = threading.Thread(target=_result_receive_function, args=(device_groups[1],
                                                                            LOOP_TIME,
                                                                            result_queue))

start_inference_time = time.time()

send_thread.start()
receive_thread.start()

try:
    while send_thread.is_alive():
        send_thread.join(1)

    while receive_thread.is_alive():
        receive_thread.join(1)
except (KeyboardInterrupt, SystemExit):
    print('\n - Received keyboard interrupt, quitting threads.')
    exit(0)

end_inference_time = time.time()
time_spent = end_inference_time - start_inference_time

try:
    generic_raw_result = result_queue.get(timeout=3)
except Exception as exception:
    print('Error: Result queue is empty !')
    exit(0)
print()

print('[Result]')
print(" - Total inference {} images".format(LOOP_TIME))
print(" - Time spent: {:.2f} secs, FPS = {:.1f}".format(time_spent, LOOP_TIME / time_spent))

"""
retrieve inference node output 
"""
print('[Retrieve Inference Node Output ]')
inf_node_output_list = []
for node_idx in range(generic_raw_result.header.num_output_node):
    inference_float_node_output = kp.inference.generic_inference_retrieve_float_node(node_idx=node_idx,
                                                                                        generic_raw_result=generic_raw_result,
                                                                                        channels_ordering=kp.ChannelOrdering.KP_CHANNEL_ORDERING_CHW)
    inf_node_output_list.append(inference_float_node_output)

print(' - Success')

print('[Result]')
print(inf_node_output_list)