Commit
•
0217301
1
Parent(s):
a95c77a
the simplest version
Browse files- .gitignore +1 -0
- configs/augmentations.json +9 -0
- images/parrot.jpg +0 -0
- src/main.py +66 -0
.gitignore
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.ipynb_checkpoints
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configs/augmentations.json
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{
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"ToGray": [],
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"ToSepia": [],
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"Blur": [{"name" : "blur_limit",
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"type" : "int_interval",
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"limits" : [3, 100],
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"defaults" : [3, 7]}
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]
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}
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images/parrot.jpg
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src/main.py
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import numpy as np
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import os
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import matplotlib.pyplot as plt
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from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
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import cv2
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import json
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import albumentations as A
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import streamlit as st
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def load_image(image_name, path_to_folder = '../images'):
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path_to_image = os.path.join(path_to_folder, image_name)
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image = cv2.imread(path_to_image)
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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return image
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def show_int_interval(name, limits, defaults, **kwargs):
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min_max_interval = st.sidebar.slider(name, limits[0], limits[1], defaults)
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return min_max_interval
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# dict from param name to function showing this param
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param2func = {
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'int_interval': show_int_interval
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}
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st.title('Demo of Albumentations transforms')
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# selecting the image
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path_to_images = 'images'
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image_names_list = [x for x in os.listdir(path_to_images) if x[-3:] in ['jpg', 'peg', 'png']]
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image_name = st.sidebar.selectbox('Select an image:', image_names_list)
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image = load_image(image_name, path_to_images)
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# selecting the transformation
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path_to_config = 'configs/augmentations.json'
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with open(path_to_config, 'r') as config_file:
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augmentations = json.load(config_file)
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transform_name = st.sidebar.selectbox('Select a transformation:', list(augmentations.keys()))
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transform_params = augmentations[transform_name]
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# show the transform options
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if len(transform_params) == 0:
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st.sidebar.text(transform_name + ' transform has no parameters')
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else:
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for param in transform_params:
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param['value'] = param2func[param['type']](**param)
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params_string = ','.join([param['name'] + '=' + str(param['value']) for param in transform_params] + ['p=1.0'])
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params_string = '(' + params_string + ')'
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st.text('Press R to update')
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exec('transform = A.' + transform_name + params_string)
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st.image([image, transform(image = image)['image']],
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caption = ['Original image', 'Transformed image'],
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width = 320)
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st.text(str(transform.__doc__))
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