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Update repo for new organization

Jérôme BUISINE 1 year ago
parent
commit
ee12267d9c
3 changed files with 4 additions and 39 deletions
  1. 1 1
      LICENCE
  2. 3 2
      README.md
  3. 0 36
      julia_train_model.jl

+ 1 - 1
LICENCE

@@ -1,5 +1,5 @@
 MIT License
-Copyright (c) <year> <copyright holders>
+Copyright (c) 2019 prise-3d
 
 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
 

+ 3 - 2
README.md

@@ -6,7 +6,8 @@
 pip install -r requirements.txt
 ```
 
-Generate all needed data for each metrics
+Generate all needed data for each metrics (which equires the the whole dataset. In order to get it, you need to contact us.
+
 ```bash
 python generate_all_data.py --metric all
 ```
@@ -177,4 +178,4 @@ All others bash scripts are used to combine and run multiple model combinations.
 
 ## License
 
-[MIT](https://github.com/prise-3d/Thesis-NoiseDetection-metrics/blob/master/LICENSE)
+[The MIT license](https://github.com/prise-3d/Thesis-NoiseDetection-metrics/blob/master/LICENSE)

+ 0 - 36
julia_train_model.jl

@@ -1,36 +0,0 @@
-using DataFrames
-using CSV
-using PyCall, JLD, PyCallJLD
-using ArgParse
-
-
-function main(args)
-
-    # initialize the settings (the description is for the help screen)
-    s = ArgParseSettings(description = "Example 1 for argparse.jl: minimal usage.")
-
-    @add_arg_table s begin
-        "--data"    
-        #    arg_type = Int           # only Int arguments allowed
-        #    nargs = '?'              # '?' means optional argument
-        #    default = 0              # this is used when the option is not passed
-        #    constant = 1             # this is used if --opt1 is paseed with no argument
-            help = "Data file for train and test"
-        
-        "--output"
-            help = "output model name"
-
-        "choice"
-            help = "Model choice"
-    end
-
-    parsed_args = parse_args(s) # the result is a Dict{String,Any}
-
-    println(parsed_args["data"])
-    println("Parsed args:")
-    for (key,val) in parsed_args
-        println("  $key  =>  $(repr(val))")
-    end
-end
-
-main(ARGS)