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import os
import streamlit as st
import albumentations as A
from utils import (
load_augmentations_config,
get_arguments,
get_placeholder_params,
select_transformations,
show_random_params,
)
from visuals import (
select_image,
show_credentials,
show_docstring,
get_transormations_params,
)
def main():
# get CLI params: the path to images and image width
path_to_images, width_original = get_arguments()
if not os.path.isdir(path_to_images):
st.title("There is no directory: " + path_to_images)
else:
# select interface type
interface_type = st.sidebar.radio(
"Select the interface mode", ["Simple", "Professional"]
)
# select image
status, image = select_image(path_to_images, interface_type)
if status == 1:
st.title("Can't load image")
if status == 2:
st.title("Please, upload the image")
else:
# image was loaded successfully
placeholder_params = get_placeholder_params(image)
# load the config
augmentations = load_augmentations_config(
placeholder_params, "configs/augmentations.json"
)
# get the list of transformations names
transform_names = select_transformations(augmentations, interface_type)
# get parameters for each transform
transforms = get_transormations_params(transform_names, augmentations)
try:
# apply the transformation to the image
data = A.ReplayCompose(transforms)(image=image)
error = 0
except ValueError:
error = 1
st.title(
"The error has occurred. Most probably you have passed wrong set of parameters. \
Check transforms that change the shape of image."
)
# proceed only if everything is ok
if error == 0:
augmented_image = data["image"]
# show title
st.title("Demo of Albumentations")
# show the images
width_transformed = int(
width_original / image.shape[1] * augmented_image.shape[1]
)
st.image(image, caption="Original image", width=width_original)
st.image(
augmented_image,
caption="Transformed image",
width=width_transformed,
)
# comment about refreshing
st.write("*Press 'R' to refresh*")
# random values used to get transformations
show_random_params(data, interface_type)
# print additional info
for transform in transforms:
show_docstring(transform)
st.code(str(transform))
show_credentials()
if __name__ == "__main__":
main()
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