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import streamlit as st
import cv2
import numpy as np
from PIL import Image
st.set_page_config(page_title="Image Processing MVP", layout="wide")
st.title("Image Processing MVP")
st.markdown(
"""
<style>
.stFileUploader label {
font-size: 20px;
font-weight: 500;
color: #1f77b4;
}
.stRadio label {
font-size: 20px;
font-weight: 500;
color: #1f77b4;
}
.stRadio div {
display: flex;
gap: 20px;
}
</style>
""",
unsafe_allow_html=True,
)
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.write("Processing...")
action = st.radio("Choose an action:", ('A', 'B'))
image_np = np.array(image)
if action == 'A':
processed_image = image_np.copy()
elif action == 'B':
processed_image = image_np.copy()
rows, cols, _ = processed_image.shape
num_spots = 50
for _ in range(num_spots):
x, y = np.random.randint(0, cols), np.random.randint(0, rows)
cv2.circle(processed_image, (x, y), 10, (0, 0, 0), -1)
col1, col2 = st.columns(2)
with col1:
st.image(image, caption='Uploaded Image', use_column_width=True)
with col2:
st.image(processed_image, caption='Processed Image', use_column_width=True)
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