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HVM Image Clf
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pjm363 (Philip Monaco)
HVM Image Clf
Commits
f5a1060e
Commit
f5a1060e
authored
3 years ago
by
pjm363 (Philip Monaco)
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Merge branch '6-create-a-parsing-for-the-training-and-test-input-sets' into 'main'
Resolve "Create a parsing for the training and test input sets." Closes
#6
See merge request
!1
parents
f23488f7
5901d98f
Branches
7-create-function-to-batch-shuffle-training-data-2
9-principal-component-analysis
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1 merge request
!1
Resolve "Create a parsing for the training and test input sets."
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README.md
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README.md
data_processing.py
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data_processing.py
image_preprocessing.ipynb
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image_preprocessing.ipynb
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README.md
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#
HVM Image Clf
#
Introduction
# Prerequisites for Use
1.
Download the training data
[
Here
](
https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Training_Input.zip
)
2.
Download the training ground truth
[
Here
](
https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Training_GroundTruth.zip
)
3.
Download the test data images
[
Here
](
https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Validation_Input.zip
)
4.
Download the test data ground truth
[
Here
](
https://isic-challenge-data.s3.amazonaws.com/2018/ISIC2018_Task3_Validation_GroundTruth.zip
)
5.
Unzip the files into the data folder in this repository.
\ No newline at end of file
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data_processing.py
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import
os
import
cv2
#vision task package opencv-python
import
pandas
as
pd
import
glob
import
numpy
as
np
def
load_transform_images
(
folder
):
"""
[summary]
Args:
filename ([type]): [description]
"""
images
=
[
cv2
.
imread
(
file
,
flags
=
cv2
.
IMREAD_GRAYSCALE
)
for
file
in
glob
.
glob
(
"
./data/
"
+
folder
+
"
/*.jpg
"
)]
return
images
def
transform
(
data
):
flat
=
[]
df
=
pd
.
DataFrame
()
for
i
,
img
in
enumerate
(
data
):
scale
=
(
img
.
astype
(
np
.
float32
)
-
127.5
)
/
127.5
scale
=
scale
.
reshape
(
1
,
-
1
)
df
=
df
.
append
(
pd
.
Series
(
scale
[
0
]),
ignore_index
=
True
)
return
df
# def batch_data(data):
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image_preprocessing.ipynb
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