3 篇文章带有标签 “tensorboard”

Get Started YOLOv5

Quick Start Examples

Install

# clone
git clone https://github.com/ultralytics/yolov5
cd yolov5

# create virtual python environments
python -m venv yolov5_env
source yolov5_env/bin/activate
python -m pip install --upgrade pip

# install
pip install -r requirements.txt

Inference import torch # Model model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # or yolov5m, yolov5l, yolov5x, custom # Images img = 'https://ultralytics.com/images/zidane.jpg' # or file, Path, PIL, OpenCV, numpy, list # Inference results = model(img) # Results results.print() # or .show(), .save(), .

在YOLOv5中运行JupyterLab和TensorBoard

构建可用的JupyterLab和TensorBoard

  • 启动YOLOv5容器
docker run --ipc=host --runtime nvidia -it -p 8888:8888 \
    -v ${dataset_dir}:/usr/src/app/project \
    ultralytics/yolov5:latest
  • 安装版本1的TensorBoard。(解决FAQ1的问题:jupyter-tensorboard 0.2.0不支持高于TensorBoard 2.0的版本。YOLOv5镜像中安装的TensorBoard 2.4的版本。)
pip uninstall tensorboard -y && pip install tensorboard==1.15
  • 运行JupyterLab
jupyter lab --no-browser --ip 0.0.0.0 --port 8888
  • 本地浏览器进行访问
http://ip:8888/lab

FAQ Launcher Error - Invalid response: 500 Internal Server Error Uncaught exception POST /api/tensorboard?1609481325314 (192.168.1.

使用RetinaNet算法训练自定义数据集

训练自己的数据集

标注数据

LabelImg

#标注后的目录结构
project
└── labelimg
    ├── 20190128155421222575013.jpg
    ├── 20190128155421222575013.xml
    ├── 20190128155703035712899.jpg
    ├── 20190128155703035712899.xml
    ├── 20190129091126392737624.jpg
    └── 20190129091126392737624.xml

构建镜像

  • 拉取
$ sudo docker pull gouchicao/keras-retinanet:latest
  • 手动构建
FROM gouchicao/tensorflow:2.2.0-gpu-jupyter-opencv4-pillow-wget-curl-git-nano
LABEL maintainer="wang-junjian@qq.com"
WORKDIR /
RUN mkdir -p /root/.keras/models/ && \
    wget -O /root/.keras/models/ResNet-50-model.keras.h5 https://github.com/fizyr/keras-models/releases/download/v0.0.1/ResNet-50-model.keras.h5
RUN git clone --depth 1 --recurse-submodules https://github.com/gouchicao/keras-retinanet.git
WORKDIR /keras-retinanet/keras-retinanet
# 提前安装指定版本 keras==2.3.1 解决错误 TypeError: type object got multiple values for keyword argument 'training'
RUN pip install keras==2.3.1 && \
    pip install . && \
    python setup.py build_ext --inplace
WORKDIR /keras-retinanet