项目作者: postor

项目描述 :
无人机视角语义分割数据集 aeroscapes 的训练及预测 | train with drone view dataset aeroscapes and predict
高级语言: Python
项目地址: git://github.com/postor/train-aeroscapes-with-gluon.git


train-aeroscapes-with-gluon

无人机视角语义分割数据集 aeroscapes 的训练及预测 | train with drone view dataset aeroscapes and predict

quick glance: https://www.youtube.com/watch?v=yYhGy2Akg2o&list=PLM1v95K5B1ntVsYvNJIxgRPppngrO_X4s

环境 | depends on

  • mxnet,gluon-cv

训练 | training

  1. 准备数据集 | prepare dataset

数据集的谷歌网盘链接在这里:https://github.com/ishann/aeroscapes | Google Drive link of dataset here

解压并将数据集放到文件夹 ./aeroscapes | unzip and put aeroscapes dataset inside folder ./aeroscapes

  1. train-aeroscapes-with-gluon
  2. aeroscapes/
  3. JPEGImages/
  4. 3269 RGB images.
  5. SegmentationClass/
  6. 3269 ground-truth segmentation masks.
  7. Visualizations/
  8. 3269 RGB ground-truth segmentation visualizations.
  9. ImageSets/
  10. Training and validation splits for data.

然后放入数语义分析据集的txt文件 | then prepare Segmentation dataset txt

  1. mv Segmentation/ aeroscapes/ImageSets/
  1. 运行训练 | run training
  1. python3 train_fcn.py

参数调整参考 train_fcn.py | params refer train_fcn.py

生成模型参数文件路径: runs/pascal_aug/fcn/default/checkpoint.params | output weights here

pretrained params(google drive): https://drive.google.com/file/d/1__mNQFFjCMonBI9tktN80Erx-e6blCSa/view?usp=sharing

检测 | predict

  1. cp runs/pascal_aug/fcn/default/checkpoint.params ./
  2. python3 predict.py

输入 | input:

test.jpg

输出 | output:

output.jpg