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import streamlit as st
from PIL import Image
import numpy as np
import io
import zipfile
# Title of the app
st.title("Image Transformation App")
# Upload image files
uploaded_files = st.file_uploader("Upload Images", type=["jpg", "jpeg", "png"], accept_multiple_files=True)
if uploaded_files:
images = [Image.open(file) for file in uploaded_files]
st.header("Uploaded Images")
for i, image in enumerate(images):
st.image(image, caption=f"Image {i+1}", use_container_width=True)
# Transformation options
st.header("Select Transformations")
options = st.multiselect("Choose transformations:", [
"Rotation",
"Scaling",
"Shearing",
"Cropping",
])
# Parameters for transformations
angle = scale_factor = shear_factor = left = top = right = bottom = None
if "Rotation" in options:
angle = st.slider("Rotation Angle (degrees):", 0, 360, 90)
if "Scaling" in options:
scale_factor = st.slider("Scaling Factor:", 0.1, 3.0, 1.0)
if "Shearing" in options:
shear_factor = st.slider("Shearing Factor:", -0.5, 0.5, 0.0)
if "Cropping" in options:
left = st.slider("Left Crop:", 0, min([image.width for image in images]) - 1, 0)
top = st.slider("Top Crop:", 0, min([image.height for image in images]) - 1, 0)
right = st.slider("Right Crop:", left + 1, min([image.width for image in images]), min([image.width for image in images]))
bottom = st.slider("Bottom Crop:", top + 1, min([image.height for image in images]), min([image.height for image in images]))
# Perform transformations
transformed_images = []
for image in images:
transformed_image = image.copy()
if "Rotation" in options and angle is not None:
transformed_image = transformed_image.rotate(angle)
if "Scaling" in options and scale_factor is not None:
new_size = (int(transformed_image.width * scale_factor), int(transformed_image.height * scale_factor))
transformed_image = transformed_image.resize(new_size)
if "Shearing" in options and shear_factor is not None:
matrix = [
1, shear_factor, 0,
0, 1, 0
]
transformed_image = transformed_image.transform(transformed_image.size, Image.AFFINE, matrix)
if "Cropping" in options and left is not None and top is not None and right is not None and bottom is not None:
transformed_image = transformed_image.crop((left, top, right, bottom))
transformed_images.append(transformed_image)
# Display transformed images
st.header("Transformed Images")
for i, transformed_image in enumerate(transformed_images):
st.image(transformed_image, caption=f"Transformed Image {i+1}", use_column_width=True)
# Download all transformed images as a zip file
if transformed_images:
zip_buffer = io.BytesIO()
with zipfile.ZipFile(zip_buffer, "w") as zf:
for i, transformed_image in enumerate(transformed_images):
img_buffer = io.BytesIO()
transformed_image.save(img_buffer, format="PNG")
zf.writestr(f"transformed_image_{i+1}.png", img_buffer.getvalue())
zip_buffer.seek(0)
st.download_button(
label="Download All Transformed Images",
data=zip_buffer,
file_name="Transformed_images.zip",
mime="application/zip",
)
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