使用Keras和Tensorflow设置和安装Mask RCNN(demo执行)

本文详细介绍了Mask R-CNN的安装步骤,包括创建Anaconda虚拟环境、安装依赖库、克隆项目仓库、安装pycocotools、下载预训练权重及测试验证等关键环节。

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参考:

https://blog.youkuaiyun.com/wc781708249/article/details/79438972

Mask RCNN paper: https://arxiv.org/pdf/1703.06870.pdf

video

概述如何安装

Step 1: create a conda virtual environment with python 3.6
Step 2: install the dependencies
Step 3: Clone the Mask_RCNN repo
Step 4: install pycocotools
Step 5: download the pre-trained weights
Step 6: Test it

Step 1: create a conda virtual environment with python 3.6

we will be using Anaconda with python 3.6.
If you don’t have Anaconda, follow this tutorial
https://www.youtube.com/watch?v=T8wK5loXkXg

conda create -n MaskRCNN python=3.6 pip

Step 2: install the dependencies

(1)place the requirements.txt in your cwdir(我使用的是下一个Mask RCNN的requirements.txt)
https://github.com/markjay4k/Mask-RCNN-series/blob/master/requirements.txt

(2)run these commands

source actvitate MaskRCNN
pip install -r requirements.txt

Step 3: Clone the Mask_RCNN repo

git clone https://github.com/matterport/Mask_RCNN.git

Step 4: install pycocotools

(1)clone this repo

git clone https://github.com/philferriere/cocoapi.git

(2)use pip to install pycocotools

pip install git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI

Step 5: download the pre-trained weights

(1)Go here https://github.com/matterport/Mask_RCNN/releases

(2)download the mask_rcnn_coco.h5 file

(3)place the file in the Mask_RCNN directory

Step 6: Test it

在jupyter中运行demo.ipynb,.ipynb只能jupyter打开

open up the demo.ipynb and run it

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