AntoineH/smart_augmentation
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1er resultats experience TF sequentiels

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Harle, Antoine (Contracteur) 2019-11-12 18:14:10 -05:00
parent ddac630548
commit 3cffac9852
2 changed files with 37 additions and 53 deletions
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37
higher/compare_res.py
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@ -1,29 +1,5 @@
from utils import *
tf_names = [
## Geometric TF ##
'Identity',
'FlipUD',
'FlipLR',
'Rotate',
'TranslateX',
'TranslateY',
'ShearX',
'ShearY',
## Color TF (Expect image in the range of [0, 1]) ##
'Contrast',
'Color',
'Brightness',
'Sharpness',
'Posterize',
'Solarize', #=>Image entre [0,1] #Pas opti pour des batch
#Non fonctionnel
#'Auto_Contrast', #Pas opti pour des batch (Super lent)
#'Equalize',
]
if __name__ == "__main__":
#### Comparison ####
@ -44,15 +20,17 @@ if __name__ == "__main__":
#plot_compare(filenames=files, fig_name="res/compare")
## Acc, Time, Epochs = f(n_tf) ##
fig_name="res/TF_nb_tests_compare"
fig_name="res/TF_seq_tests_compare"
inner_its = [0, 10]
dataug_epoch_starts= [0, -1]
TF_nb = range(1,14+1)
dataug_epoch_starts= [0]
TF_nb = 14 #range(1,14+1)
N_seq_TF= [1, 2, 3, 4, 6]
fig, ax = plt.subplots(ncols=3, figsize=(30, 8))
for in_it in inner_its:
for dataug in dataug_epoch_starts:
filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF)-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, dataug, in_it) for n_tf in TF_nb]
#filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF)-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(n_tf, dataug, in_it) for n_tf in TF_nb]
filenames =["res/TF_nb_tests/log/Aug_mod(Data_augV4(Uniform-{} TF x {})-LeNet)-200 epochs (dataug:{})- {} in_it.json".format(TF_nb, n_tf, dataug, in_it) for n_tf in N_seq_TF]
all_data=[]
#legend=""
@ -62,7 +40,8 @@ if __name__ == "__main__":
data = json.load(json_file)
all_data.append(data)
n_tf = [len(x["Param_names"]) for x in all_data]
n_tf = N_seq_TF
#n_tf = [len(x["Param_names"]) for x in all_data]
acc = [x["Accuracy"] for x in all_data]
epochs = [len(x["Log"]) for x in all_data]
time = [x["Time"][0] for x in all_data]