initial commit

.vscode/settings.json

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+{
+    "python.pythonPath": "C:\\Users\\atari\\Miniconda3\\envs\\chouse\\python.exe"
+}

learning_cofigurations/sample_shape_mobilenetv2_201118.lcfg

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+{ModelName} {Epoch} {batch_size} {Optmizer} {Loss_rate} {} {} {save_period}
+MobileNetV2 5000 100 

recorder.py

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+import os
+import sys
+import pandas
+import torch
+import torchvision

train_model_1.0.py

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+import argparse
+import torch
+import torchvision.models
+import sys
+import pandas
+
+
+
+'''
+filename:train_model_1.0.py
+create date: 11/17/2020 Tue
+Author: Jeong Geol Kim
+Contact: atarib4816@gmail.com
+Description: This .py file will train, save weight and save Results with parameters. parameters will input by .txt file.
+eg) train_model_1.0.py -r train_parameter.lcfg
+guidelines for train_parameter.txt
+filename format: partofarchitecture_backbone_yymmdd.lcfg
+eg) shapesort_mobilenetv2_201118.txt
+'''
+
+
+def Params_Set():
+    '''
+    Description: read options from .lcfg and initialize learning options.
+    You should write 
+    '''
+    HELP_TEXT = "how to use .py" #TODO: write description more precisely
+    N_OF_PARAMS = 3 #from now on, .txt file has 3 pramas(backbone Name, iterations, save period)
+
+    parser = argparse.ArgumentParser(description = HELP_TEXT)
+    parser.add_argument("-r", required = True, help = '.lcfg file contains with learning configures')
+    args = parser.parse_args()
+
+    f = open(args.r, 'r')    
+    p_string = f.readline()
+    f.close()
+    params = p_string.split()
+
+    if str(args.r[-4:]) != 'lcfg':
+        print ("Error: {} is wrong filename extension. Learning configures must written in .lcfg file")
+        return 
+    elif len(params) != N_OF_PARAMS: 
+        print("Error: {} is broken. please check learning configures.".format(args.r))
+        return
+    else:
+        print("---Learning Options---")
+        print("Backbone Name: {}".format(params[0]))
+        print("Number of iterations: {}".format(params[1]))
+        print("Period of saving weight: {}".format(params[2]))
+        return params, args.r
+
+
+def Preprocess():
+    pass
+
+
+
+def Model_Construct():
+    pass
+
+def Train():
+    pass
+
+def Save_Weight():
+    pass
+
+
+def Result():
+    pass
+
+
+
+
+if __name__ == "__main__":
+    #get all params from option files
+    params, name_of_lcfg = Params_Set()
+
+    Preprocess()
+
+    Model_Construct()
+
+    Train()   
+
+    Save_Weight()
+
+    Result()
+
+
+
+
+

weights_backup/sample_shape_mobilenetv2_201118/100_sample_shape_mobilenetv2_201118.rtf

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+{\rtf1}

weights_backup/sample_shape_mobilenetv2_201118/200_sample_shape_mobilenetv2_201118 - Copy.rtf

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+{\rtf1}