python -m onnxsim best.onnx best-sim.onnx #coding=utf-8importcv2importnumpy as npimportonnxruntimeimporttorchimporttorchvisionimporttimeimportrandomfromutils.generalimportnon_max_suppressionclassYOLOV5_ONNX(object):def__init__(self,onnx_path):'''初始化onnx'''self.onnx_session=onnxruntime.I...
据[RuntimeError: CUDA error: no kernel image is available for execution on the device](https://blog.csdn.net/qq_43391414/article/details/110562749)得知,如果你要使用torch 1.7,GPU算力至少要达到5.2。那么根据博主提供的算力表,如果没达标就不用装了 pytorch安装cpu版本。 *ps:我的显卡是RTX2060* 参考...
起初我运行export_onnx.py生成onnx文件之后Opencv读取onnx文件失败了,报错原因跟文章最开始的第(2)节里的一样,这说明在YOLOX的网络结构里有切片操作,经过搜索后,在 yolox\models\network_blocks.py 里有个Focus类,它跟YOLOv5里的Focus是一样的,都是把输入张量切分成4份,然后concat...
onnx_path):'''初始化onnx'''self.onnx_session=onnxruntime.InferenceSession(onnx_path)print(onnxruntime.get_device())self.input_name=self.get_input_name()
#代码一 # onnx_model_path = "D:/work1/yolov5/yolov5/runs/train/exp8/weights/yolov5_s_640.onnx" # # # 准备测试数据 # image_path = "E:/faces/Snipaste_2024-06-04_13-53-20.jpg" import os import cv2 import numpy as np import onnxruntime import time # CLASSES = ['people', ...
yolov5s.onnx # ONNX Runtime or OpenCV DNN with --dnn yolov5s.xml # OpenVINO yolov5s.engine # TensorRT yolov5s.mlmodel # CoreML (MacOS-only) yolov5s_saved_model # TensorFlow SavedModel yolov5s.pb # TensorFlow GraphDef yolov5s.tflite # TensorFlow Lite ...
上图中(a)(b)是ShuffleNetV1的结构,而后面的(c)(d)是ShuffleNetV2的层结构,也是YOLOv5 Lite中的主要结构,分别对应的是结构图中的SFB1_X和SFB2_X SFB1_X结构对应图(d)结构 SFB2_X结构对应图(c)结构 下面稍微讲一下笔者结合论文的理解: Channel Split操作将整个特征图分为c’组(假设为A组)和c-c’(...
yolov5s.onnx # ONNX Runtime or OpenCV DNN with --dnn yolov5s.xml # OpenVINO yolov5s.engine # TensorRT yolov5s.mlmodel # CoreML (MacOS-only) yolov5s_saved_model # TensorFlow SavedModel yolov5s.pb # TensorFlow GraphDef yolov5s.tflite # TensorFlow Lite ...
We trained YOLOv5-cls classification models on ImageNet for 90 epochs using a 4xA100 instance, and we trained ResNet and EfficientNet models alongside with the same default training settings to compare. We exported all models to ONNX FP32 for CPU speed tests and to TensorRT FP16 for GPU ...
ImportError: If required libraries for export (e.g., 'onnx', 'onnx-simplifier') are not installed. AssertionError: If the simplification check fails. Notes: The required packages for this function can be installed via: ``` pip install onnx onnx-simplifier onnxruntime onnxruntime-gpu...