Movatterモバイル変換

[0]ホーム
URL:

Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

 Sign up
Appearance settings

Commit433cc05

Browse files
committed
add image transformations tutorial
1 parent2f6da6e commit433cc05

File tree

10 files changed

+194
-0
lines changed

10 files changed

+194
-0
lines changed

‎README.md

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -52,6 +52,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
5252
-[Skin Cancer Detection using TensorFlow in Python](https://www.thepythoncode.com/article/skin-cancer-detection-using-tensorflow-in-python). ([code](machine-learning/skin-cancer-detection))
5353
-[How to Perform Malaria Cells Classification using TensorFlow 2 and Keras in Python](https://www.thepythoncode.com/article/malaria-cells-classification). ([code](machine-learning/malaria-classification))
5454
-[How to Make a Barcode Reader in Python](https://www.thepythoncode.com/article/making-a-barcode-scanner-in-python). ([code](general/barcode-reader))
55+
-[Image Transformations using OpenCV in Python](https://www.thepythoncode.com/article/image-transformations-using-opencv-in-python). ([code](machine-learning/image-transformation))
5556
-[Building a Speech Emotion Recognizer using Scikit-learn](https://www.thepythoncode.com/article/building-a-speech-emotion-recognizer-using-sklearn). ([code](machine-learning/speech-emotion-recognition))
5657
-[How to Convert Speech to Text in Python](https://www.thepythoncode.com/article/using-speech-recognition-to-convert-speech-to-text-python). ([code](machine-learning/speech-recognition))
5758
-[Top 8 Python Libraries For Data Scientists and Machine Learning Engineers](https://www.thepythoncode.com/article/top-python-libraries-for-data-scientists).
Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,3 @@
1+
#[Image Transformations using OpenCV in Python](https://www.thepythoncode.com/article/image-transformations-using-opencv-in-python)
2+
To run all the scripts, you need to install the requirements:
3+
-`pip3 install -r requirements.txt`
120 KB
Loading
Lines changed: 24 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,24 @@
1+
importnumpyasnp
2+
importcv2
3+
importmatplotlib.pyplotasplt
4+
5+
# read the input image
6+
img=cv2.imread("city.jpg")
7+
# convert from BGR to RGB so we can plot using matplotlib
8+
img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
9+
# disable x & y axis
10+
plt.axis('off')
11+
# show the image
12+
plt.imshow(img)
13+
plt.show()
14+
15+
# get 200 pixels from 100 to 300 on both x-axis & y-axis
16+
# change that if you will, just make sure you don't exceed cols & rows
17+
cropped_img=img[100:300,100:300]
18+
# disable x & y axis
19+
plt.axis('off')
20+
# show the resulting image
21+
plt.imshow(cropped_img)
22+
plt.show()
23+
# save the resulting image to disk
24+
plt.imsave("city_cropped.jpg",cropped_img)
Lines changed: 34 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,34 @@
1+
importnumpyasnp
2+
importcv2
3+
importmatplotlib.pyplotasplt
4+
5+
# read the input image
6+
img=cv2.imread("city.jpg")
7+
# convert from BGR to RGB so we can plot using matplotlib
8+
img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
9+
# disable x & y axis
10+
plt.axis('off')
11+
# show the image
12+
plt.imshow(img)
13+
plt.show()
14+
15+
# get the image shape
16+
rows,cols,dim=img.shape
17+
18+
# transformation matrix for x-axis reflection
19+
M=np.float32([[1,0,0 ],
20+
[0,-1,rows],
21+
[0,0,1 ]])
22+
# transformation matrix for y-axis reflection
23+
# M = np.float32([[-1, 0, cols],
24+
# [ 0, 1, 0 ],
25+
# [ 0, 0, 1 ]])
26+
# apply a perspective transformation to the image
27+
reflected_img=cv2.warpPerspective(img,M,(int(cols),int(rows)))
28+
# disable x & y axis
29+
plt.axis('off')
30+
# show the resulting image
31+
plt.imshow(reflected_img)
32+
plt.show()
33+
# save the resulting image to disk
34+
plt.imsave("city_reflected.jpg",reflected_img)
Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,3 @@
1+
matplotlib
2+
opencv-python
3+
numpy
Lines changed: 32 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,32 @@
1+
importnumpyasnp
2+
importcv2
3+
importmatplotlib.pyplotasplt
4+
5+
# read the input image
6+
img=cv2.imread("city.jpg")
7+
# convert from BGR to RGB so we can plot using matplotlib
8+
img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
9+
# disable x & y axis
10+
plt.axis('off')
11+
# show the image
12+
plt.imshow(img)
13+
plt.show()
14+
15+
# get the image shape
16+
rows,cols,dim=img.shape
17+
18+
#angle from degree to radian
19+
angle=np.radians(10)
20+
#transformation matrix for Rotation
21+
M=np.float32([[np.cos(angle),-(np.sin(angle)),0],
22+
[np.sin(angle),np.cos(angle),0],
23+
[0,0,1]])
24+
# apply a perspective transformation to the image
25+
rotated_img=cv2.warpPerspective(img,M, (int(cols),int(rows)))
26+
# disable x & y axis
27+
plt.axis('off')
28+
# show the resulting image
29+
plt.imshow(rotated_img)
30+
plt.show()
31+
# save the resulting image to disk
32+
plt.imsave("city_rotated.jpg",rotated_img)
Lines changed: 30 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,30 @@
1+
importnumpyasnp
2+
importcv2
3+
importmatplotlib.pyplotasplt
4+
5+
# read the input image
6+
img=cv2.imread("city.jpg")
7+
# convert from BGR to RGB so we can plot using matplotlib
8+
img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
9+
# disable x & y axis
10+
plt.axis('off')
11+
# show the image
12+
plt.imshow(img)
13+
plt.show()
14+
15+
# get the image shape
16+
rows,cols,dim=img.shape
17+
18+
#transformation matrix for Scaling
19+
M=np.float32([[1.5,0 ,0],
20+
[0,1.8,0],
21+
[0,0,1]])
22+
# apply a perspective transformation to the image
23+
scaled_img=cv2.warpPerspective(img,M,(cols*2,rows*2))
24+
# disable x & y axis
25+
plt.axis('off')
26+
# show the resulting image
27+
plt.imshow(scaled_img)
28+
plt.show()
29+
# save the resulting image to disk
30+
plt.imsave("city_scaled.jpg",scaled_img)
Lines changed: 37 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,37 @@
1+
importnumpyasnp
2+
importcv2
3+
importmatplotlib.pyplotasplt
4+
5+
# read the input image
6+
img=cv2.imread("city.jpg")
7+
# convert from BGR to RGB so we can plot using matplotlib
8+
img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
9+
# disable x & y axis
10+
plt.axis('off')
11+
# show the image
12+
plt.imshow(img)
13+
plt.show()
14+
15+
# get the image shape
16+
rows,cols,dim=img.shape
17+
18+
# transformation matrix for Shearing
19+
# shearing applied to x-axis
20+
M=np.float32([[1,0.5,0],
21+
[0,1 ,0],
22+
[0,0 ,1]])
23+
# shearing applied to y-axis
24+
# M = np.float32([[1, 0, 0],
25+
# [0.5, 1, 0],
26+
# [0, 0, 1]])
27+
28+
29+
# apply a perspective transformation to the image
30+
sheared_img=cv2.warpPerspective(img,M,(int(cols*1.5),int(rows*1.5)))
31+
# disable x & y axis
32+
plt.axis('off')
33+
# show the resulting image
34+
plt.imshow(sheared_img)
35+
plt.show()
36+
# save the resulting image to disk
37+
plt.imsave("city_sheared.jpg",sheared_img)
Lines changed: 30 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,30 @@
1+
importnumpyasnp
2+
importcv2
3+
importmatplotlib.pyplotasplt
4+
5+
# read the input image
6+
img=cv2.imread("city.jpg")
7+
# convert from BGR to RGB so we can plot using matplotlib
8+
img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
9+
# disable x & y axis
10+
plt.axis('off')
11+
# show the image
12+
plt.imshow(img)
13+
plt.show()
14+
15+
# get the image shape
16+
rows,cols,dim=img.shape
17+
18+
# transformation matrix for translation
19+
M=np.float32([[1,0,50],
20+
[0,1,50],
21+
[0,0,1]])
22+
# apply a perspective transformation to the image
23+
translated_img=cv2.warpPerspective(img,M, (cols,rows))
24+
# disable x & y axis
25+
plt.axis('off')
26+
# show the resulting image
27+
plt.imshow(translated_img)
28+
plt.show()
29+
# save the resulting image to disk
30+
plt.imsave("city_translated.jpg",translated_img)

0 commit comments

Comments
 (0)
[8]ページ先頭
©2009-2025 Movatter.jp