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)