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import streamlit as st
import cv2
import numpy as np
from PIL import Image
st.title("OpenCV Image Processing")
st.write("This is a simple web app to demonstrate how to use OpenCV with Streamlit.")
uploaded_file = st.file_uploader(
"Choose an image...", type=["png", "jpg", "jpeg"])
if uploaded_file is not None:
st.text("Image uploaded successfully.")
st.write("Please select an option from the checkboxes below:")
options = {
"Show Grayscale": False,
"Resize Image": False,
"Crop Image": False,
"Rotate Image": False,
"Flip Image": False,
}
for option_name in options:
options[option_name] = st.checkbox(option_name)
st.subheader("Original vs Processed Image")
col1, col2 = st.columns(2)
if uploaded_file is not None: # Check if a file was actually uploaded
image = Image.open(uploaded_file).convert(
"RGB") # CRUCIAL: Convert to RGB immediately
original_image = np.array(image)
processed_image = original_image.copy()
with col1:
st.image(original_image, caption="Original Image",
channels="RGB") # Display in RGB
if any(options.values()):
if options["Show Grayscale"]:
processed_image = cv2.cvtColor(
processed_image, cv2.COLOR_RGB2GRAY)
if options["Resize Image"]:
width = st.slider(
"New Width", 100, original_image.shape[1] * 2, original_image.shape[1], step=10)
height = st.slider(
"New Height", 100, original_image.shape[0] * 2, original_image.shape[0], step=10)
processed_image = cv2.resize(processed_image, (width, height))
if len(processed_image.shape) == 2:
processed_image = cv2.cvtColor(
processed_image, cv2.COLOR_GRAY2RGB)
if options["Crop Image"]:
x1 = st.slider("X1", 0, original_image.shape[1], 0)
y1 = st.slider("Y1", 0, original_image.shape[0], 0)
x2 = st.slider(
"X2", 0, original_image.shape[1], original_image.shape[1])
y2 = st.slider(
"Y2", 0, original_image.shape[0], original_image.shape[0])
processed_image = processed_image[y1:y2, x1:x2]
if len(processed_image.shape) == 2:
processed_image = cv2.cvtColor(
processed_image, cv2.COLOR_GRAY2RGB)
if options["Rotate Image"]:
angle = st.slider("Rotation Angle", -180, 180, 0)
rows, cols = processed_image.shape[:2]
M = cv2.getRotationMatrix2D((cols / 2, rows / 2), angle, 1)
processed_image = cv2.warpAffine(
processed_image, M, (cols, rows))
if len(processed_image.shape) == 2:
processed_image = cv2.cvtColor(
processed_image, cv2.COLOR_GRAY2RGB)
if options["Flip Image"]:
flip_mode = st.selectbox(
"Flip Mode", [("Vertical", 0), ("Horizontal", 1), ("Both", -1)])
processed_image = cv2.flip(processed_image, flip_mode[1])
if len(processed_image.shape) == 2:
processed_image = cv2.cvtColor(
processed_image, cv2.COLOR_GRAY2RGB)
with col2:
if len(processed_image.shape) == 3:
processed_channels = "RGB" # Display in RGB
elif len(processed_image.shape) == 2:
processed_channels = "GRAY"
else:
processed_channels = None
if processed_channels:
st.image(processed_image, caption="Processed Image",
channels=processed_channels)
else:
st.write("Unexpected image format after processing.")
else:
with col2:
st.write("No processing applied yet.")
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