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easyolo python library

Project description

EasYoloD

Easy Yolo Detect

用户快速部署yolo的识别程序,支持onnxruntime, opencv(dnn), openvino

仅需简短几行代码即可实现yolo目标检测

Provider 介绍

  1. onnxruntime:
    • cpu: 适配性最高的版本,不需要GPU即可执行
    • gpu: onnxruntime-gpu 需要英伟达GPU,并且安装对应版本cuda,cudnn之后才能使用,速度快
    • onnxdml: onnxruntime-directml 不需要使用特定GPU,核显也可以允许,而且不需要安装任何额外程序,速度一般,而且仅适用与windos系统
  2. openvino:
    • cpu: 同onnx的cpu一样
    • gpu: 仅适用于intel的GPU,其他GPU不可用
  3. opencv:
    • cpu: 同上
    • gpu: 需要单独编译带有cuda的opencv包,并正确配置路径,并且安装好cuda和cudnn,速度快

安装和使用

pip install easyolod

Requirements

  • Python 3.8-3.12
  • opencv-python <= 4.10.0.84
  • numpy <= 1.26

使用:

import easyolod

easyolod.init(provider='onnxruntime',gpu=False) # onnxruntime-directml 则使用onnxdml,openvino使用 openvino
model = easyolod.Model()
# conf 置信度
# ious
# namse 可以是文件,也可以是一个list
model.load('modelpath', conf, ious, names)
# or 你使用的是opencv dnn yolov4的weight模型
# model.load('config path', 'weight path', inputsize, names, conf, nms)

result = model.detect(img=image)
# or 你希望自己处理输出
# result = model.detect_only(img=image)

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