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import streamlit as st
import cv2
import numpy as np
from PIL import Image
def process_image(image, operation, rotation_angle=0, blur_value=5):
img_array = np.array(image)
img_cv = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
if operation == "Greyscale":
processed_img = cv2.cvtColor(img_cv, cv2.COLOR_BGR2GRAY)
elif operation == "Rotate":
(h, w) = img_cv.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, rotation_angle, 1.0)
processed_img = cv2.warpAffine(img_cv, M, (w, h))
elif operation == "Edge Detection":
processed_img = cv2.Canny(img_cv, 100, 200)
elif operation == "Blur":
processed_img = cv2.GaussianBlur(img_cv, (blur_value, blur_value), 0)
else:
processed_img = img_cv
return processed_img
def main():
st.title("Image Processing App")
uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
if uploaded_image is not None:
image = Image.open(uploaded_image)
st.image(image, caption="Original Image", use_container_width=True)
operation = st.selectbox("Select an operation", ["None", "Greyscale", "Rotate", "Edge Detection", "Blur"])
rotation_angle = 0
blur_value = 5
if operation == "Rotate":
rotation_angle = st.slider("Select Rotation Angle", -180, 180, 0)
elif operation == "Blur":
blur_value = st.slider("Select Blur Intensity", 1, 25, 5, step=2)
if operation != "None":
processed_img = process_image(image, operation, rotation_angle, blur_value)
st.image(processed_img, caption="Processed Image", use_container_width=True, channels="GRAY" if operation == "Greyscale" or operation == "Edge Detection" else "BGR")
if __name__ == "__main__":
main()
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