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inovisao
pynovisao
Commits
365f0bf0
Commit
365f0bf0
authored
Oct 07, 2020
by
Diego André Sant'Ana
🤞
Browse files
fix problems in load files and load model with keras
parent
9e4ef8cc
Changes
3
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3 changed files
with
7 additions
and
22 deletions
+7
-22
src/classification/cnn_keras.py
src/classification/cnn_keras.py
+3
-18
src/interface/tk_interface.py
src/interface/tk_interface.py
+2
-2
src/pynovisao.py
src/pynovisao.py
+2
-2
No files found.
src/classification/cnn_keras.py
View file @
365f0bf0
...
...
@@ -198,12 +198,11 @@ class CNNKeras(Classifier):
predict_directory
=
File
.
make_path
(
dataset
,
test_dir
)
CLASS_NAMES
=
np
.
loadtxt
(
self
.
labels_file
.
value
,
str
)
# Create a Keras class
# Create a Keras class
if
not
os
.
path
.
exists
(
File
.
make_path
(
predict_directory
,
"png"
)):
os
.
makedirs
(
File
.
make_path
(
predict_directory
,
"png"
))
for
file
in
os
.
listdir
(
predict_directory
):
print
(
File
.
make_path
(
predict_directory
,
file
))
#
print(File.make_path(predict_directory, file))
if
os
.
path
.
splitext
(
file
)[
-
1
]
==
".tif"
:
try
:
img
=
Image
.
open
(
File
.
make_path
(
predict_directory
,
file
))
...
...
@@ -216,7 +215,7 @@ class CNNKeras(Classifier):
else
:
print
(
File
.
make_path
(
predict_directory
,
file
))
#os.symlink(File.make_path(predict_directory, file),File.make_path(predict_directory, 'png', file))
print
(
"Classes load from file examples/labels.txt"
)
print
(
CLASS_NAMES
)
try
:
...
...
@@ -227,11 +226,7 @@ class CNNKeras(Classifier):
self
.
model
=
load_model
(
self
.
weight_path
)
#path_classes = self.weight_path.replace( "_model.h5", "_classes.npy")
print
(
"Load Model H5:"
+
self
.
weight_path
)
#np_load_old = np.load
#modify the default parameters of np.load
#np.load = lambda *a,**k: np_load_old(*a, allow_pickle=True, **k)
#CLASS_NAMES = np.load(path_classes).item().keys()
except
Exception
as
e
:
raise
IException
(
"Can't load the model in "
+
str
(
e
))
...
...
@@ -250,21 +245,11 @@ class CNNKeras(Classifier):
classify_generator
,
classify_generator
.
samples
,
verbose
=
2
)
one_hot_output
=
np
.
argmax
(
output_classification
,
axis
=
1
)
print
(
len
(
one_hot_output
))
print
(
one_hot_output
)
#output_classification = self.model.predict_generator(classify_generator)
#one_hot_output = np.argmax(output_classification, axis=1)
#one_hot_output = one_hot_output.tolist()
classes
=
[]
for
index
in
range
(
0
,
len
(
one_hot_output
)):
#print(index)
classes
.
append
(
CLASS_NAMES
[
one_hot_output
[
index
]])
#print(len(classes))
return
classes
def
train
(
self
,
dataset
,
training_data
,
force
=
False
):
...
...
src/interface/tk_interface.py
View file @
365f0bf0
...
...
@@ -26,7 +26,7 @@ else:
self
.
Menu
=
Menu
self
.
Image
=
Image
self
.
Log
=
Log
self
.
Pop
=
Pop
self
.
Pop
up
=
Pop
self
.
CustomGrid
=
CustomGrid
self
.
SelectDialog
=
SelectDialog
self
.
ChooseOneDialog
=
ChooseOneDialog
...
...
@@ -36,7 +36,7 @@ else:
tk_local
.
Menu
=
tk_menu
.
Menu
tk_local
.
Image
=
tk_canvas
.
Image
tk_local
.
Log
=
tk_logger
.
Log
tk_local
.
Pop
=
tk_popup
.
Popup
tk_local
.
Pop
up
=
tk_popup
.
Popup
tk_local
.
CustomGrid
=
tk_customframe
.
CustomGrid
tk_local
.
SelectDialog
=
tk_customdialog
.
SelectDialog
tk_local
.
ChooseOneDialog
=
tk_customdialog
.
ChooseOneDialog
...
...
src/pynovisao.py
View file @
365f0bf0
...
...
@@ -558,7 +558,7 @@ class Act(object):
self
.
_gt_segments
=
[
None
]
*
(
max
(
list_segments
)
+
1
)
# New and optimized classification
tmp
=
"tmp"
tmp
=
"
.
tmp"
File
.
remove_dir
(
File
.
make_path
(
self
.
dataset
,
tmp
))
self
.
tk
.
append_log
(
"Generating test images... (%0.3f seconds)"
,
(
TimeUtils
.
get_time
()
-
start_time
))
...
...
@@ -618,7 +618,7 @@ class Act(object):
len_classes
=
sum
([
len_segments
[
idx
]
for
idx
in
idx_segment
])
popup_info
+=
"%-16s%-16s%0.2f%%
\n
"
%
(
cl
[
"name"
].
value
,
str
(
len_classes
),
(
len_classes
*
100.0
)
/
len_total
)
print
(
popup_info
)
self
.
tk
.
refresh_image
(
self
.
_image
)
self
.
tk
.
popup
(
popup_info
)
else
:
...
...
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