HailoRT minimal working example for Python and Hailo8

omria · December 29, 2024, 8:58pm

First off, thanks a ton for your contribution! Your minimal working example (MWE) is awesome and really drives home the importance of having simple, clear, and beginner-friendly examples for developers to use as a starting point when working with Hailo devices.

I wanted to let you know that we’ve got some inference working examples ready to go in our GitHub repo. Check them out here:

github.com

hailo-ai/Hailo-Application-Code-Examples/blob/main/runtime/python/utils.py

from typing import List, Generator, Optional, Tuple, Dict
from pathlib import Path
from functools import partial
import queue
from loguru import logger
import numpy as np
from PIL import Image
from hailo_platform import (HEF, VDevice,
                            FormatType, HailoSchedulingAlgorithm)
IMAGE_EXTENSIONS: Tuple[str, ...] = ('.jpg', '.png', '.bmp', '.jpeg')


class HailoAsyncInference:
    def __init__(
        self, hef_path: str, input_queue: queue.Queue,
        output_queue: queue.Queue, batch_size: int = 1,
        input_type: Optional[str] = None, output_type: Optional[Dict[str, str]] = None,
        send_original_frame: bool = False) -> None:
        """
        Initialize the HailoAsyncInference class with the provided HEF model

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Feel free to take a look and let us know what you think. Your feedback is super valuable in helping us make our resources even better for the developer community.

Thanks again for your contribution and for helping us improve the Hailo experience for everyone!

Best Regards,
Omria

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HailoRT minimal working example for Python and Hailo8

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