win10环境配置maskrcnn_benchmark

最近在找实例分割代码，我在win10环境下配置，配置了很久很久，很多坑，记录一下

项目简介

Maskrcnn_Benchmark 是 MaskRCNN 的 Pytorch 实现版本，MaskRCNN是本身是Tensorflow实现,用于实例分割。

项目地址：https://github.com/facebookresearch/maskrcnn-benchmark?spm=a2c4e.10696291.0.0.76e419a4t4nrMc

环境准备

win10 Home + Anaconda3 + CUDA 9.0 + CUDNN 7.1 + visualcppbuildtools_full

最后一个软件看可以代替 Visual Studio

下载地址：https://pan.baidu.com/s/1J0CAz_d9semPyiEWu8nIbg 提取码：k490

安装步骤

按照官方教程以及一些改动即可。

参照这个博客： https://www.jianshu.com/p/e9680d0bfa5c

下述是官方安装教程搬运，具体参照上述博客更好。

open a cmd and change to desired installation directory
from now on will be refered as INSTALL_DIR
conda create --name maskrcnn_benchmark
conda activate maskrcnn_benchmark
 
# this installs the right pip and dependencies for the fresh python
conda install ipython
 
# maskrcnn_benchmark and coco api dependencies
pip install ninja yacs cython matplotlib tqdm opencv-python
 
# follow PyTorch installation in https://pytorch.org/get-started/locally/
# we give the instructions for CUDA 9.0
## Important : check the cuda version installed on your computer by running the command in the cmd :
nvcc -- version
conda install -c pytorch pytorch-nightly torchvision cudatoolkit=9.0
 
git clone https://github.com/cocodataset/cocoapi.git
 
    #To prevent installation error do the following after commiting cocooapi :
    #using file explorer  naviagate to cocoapi\PythonAPI\setup.py and change line 14 from:
    #extra_compile_args=['-Wno-cpp', '-Wno-unused-function', '-std=c99'],
    #to
    #extra_compile_args={'gcc': ['/Qstd=c99']},
    #Based on  https://github.com/cocodataset/cocoapi/issues/51
 
cd cocoapi/PythonAPI
python setup.py build_ext install
 
# navigate back to INSTALL_DIR
cd ..
cd ..
# install apex
 
git clone https://github.com/NVIDIA/apex.git
cd apex
python setup.py install --cuda_ext --cpp_ext
# navigate back to INSTALL_DIR
cd ..
# install PyTorch Detection
 
git clone https://github.com/Idolized22/maskrcnn-benchmark.git
cd maskrcnn-benchmark
 
# the following will install the lib with
# symbolic links, so that you can modify
# the files if you want and won't need to
# re-build it
python setup.py build develop

踩坑

我卡了三天，各种安装卸载Visual Studio,总结以下问题：

• 可以不需要Visual Studio！！！

• pytorch1.0中，torchvision安装错误

  出问题先import torch import torchvision 看是否出错，我的torchvision是pillow库出错，换了个版本的pillow库解决的。

• 编译时找不到文件

  上述提到到编译软件需要添加环境变量

• CUDA编译错误

  CUDA文件需要按照上述安装步骤中做相应改动，我文件改错了所以导致cuda一直出错

• Link Error 链接错误

  直接百度错误，复制两个文件到一个目录即可

Demo运行

Jupyter Notebook 程序我这边没跑起来，但是摄像头demo、自己的本地demo跑起来了，Jupyter Notebook demo跑不起来可以用以下的代码代替：运行直接 python demo.py .

#!--*-- coding:utf-8 --*--
 
import matplotlib.pyplot as plt
import matplotlib.pylab as pylab
 
#import requests
from io import BytesIO
from PIL import Image
import numpy as np
 
pylab.rcParams['figure.figsize'] = 20, 12
 
from maskrcnn_benchmark.config import cfg
from predictor import COCODemo
 
 
# 参数配置文件
config_file = "../configs/caffe2/e2e_mask_rcnn_R_50_FPN_1x_caffe2.yaml"
 
cfg.merge_from_file(config_file)
cfg.merge_from_list(["MODEL.DEVICE", "cpu"])
# cfg.MODEL.WEIGHT = '../pretrained/e2e_mask_rcnn_R_50_FPN_1x.pth'
 
coco_demo = COCODemo(cfg, min_image_size=800, confidence_threshold=0.7, )
 
 
imgfile = '../images/1.jpg'
pil_image = Image.open(imgfile).convert("RGB")
 
image = np.array(pil_image)[:, :, [2, 1, 0]]
 
# forward predict
predictions = coco_demo.run_on_opencv_image(image)
 
# vis
plt.subplot(1, 2, 1)
plt.imshow(image[:,:,::-1])
plt.axis('off')
 
plt.subplot(1, 2, 2)
plt.imshow(predictions[:,:,::-1])
plt.axis('off')
plt.show()

效果图