File size: 1,372 Bytes
43cc773
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3e5cb6b
43cc773
 
 
 
 
 
 
 
3e5cb6b
 
 
 
43cc773
3e5cb6b
 
 
43cc773
3e5cb6b
 
43cc773
3e5cb6b
 
 
43cc773
3e5cb6b
 
43cc773
3e5cb6b
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
"""

    PROJECT: GaussianHighPassFilter
    FILENAME: app.py
    AUTHOR: David NAISSE
    DATE: August 22, 2022

    DESCRIPTION: App script.
    
"""

import numpy as np
import streamlit as st
from PIL import Image
from scipy import ndimage

# Page config
st.set_page_config(layout="centered")
st.title("High Pass Filter for Images")
st.write('High pass filter applied to images. ')

left, right = st.columns([3, 2])

# Uploader
img_or_video = left.file_uploader("Upload an image: ", type=['.jpg', '.png', '.jpeg'])

# Display example selection
size = int(right.number_input('Filter size (ex: 3x3): ', min_value=3, max_value=500, value=3, help='Filter size. '))

# Init. empty texts
filter_text = right.empty()
size_text = right.empty()

# Default image or uploaded one
original = Image.open("resource/example.jpg" if img_or_video is None else img_or_video)
image = np.array(original)
gray = np.array(original.convert('L'))

# Apply high pass
lowpass = ndimage.gaussian_filter(gray, size)
gauss_highpass = gray - lowpass

# Display original
st.image(1-gauss_highpass, caption='High Pass')

# Update elements
filter_text.write(f'Using filter of size {size}x{size}. ')
size_text.write(f'Image size: {gauss_highpass.shape}')

# Split UI in 2
left2, right2 = st.columns([5, 5])

# Display img
left2.image(image, caption='Original')
right2.image(lowpass, caption='Low Pass')