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This is a python project of deep learning for scene labeling.

Course Project in Telecom Paristech


Here is the structure of the project,

prim_dl
├── data
│   ├── data_stanford
│   │   ├── images
│   │   └── labels
│   └── test
└── scripts

  • data, data forlder, ignored by git. We train the model by the backgroud dataset from Stanford Lab. Also there are data below test for debug
  • scripts, contain the relative fonctions

Environment

I write this instruction under ubuntu 14.04


Fonctions

file_system.py

  • Create new folder
  • Delete the folder with subfolder

image_proc.py

  • Open and convert the image to a special type
  • Show the image
  • Get the laplacien pyramid
  • Lecun local contrast normalization

cnn

  • To be done ...

segmentation

  • To be done ...