|
|
import streamlit as st |
|
|
import cv2 |
|
|
import numpy as np |
|
|
from PIL import Image |
|
|
|
|
|
def process_image(image, option, brightness_level=0, rotation_angle=0): |
|
|
if option == "🖤 Convert to Grayscale": |
|
|
return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) |
|
|
elif option == "🌈 Convert to Color": |
|
|
return cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) if len(image.shape) == 2 else image |
|
|
elif option == "🌪️ Blur Image": |
|
|
return cv2.GaussianBlur(image, (15, 15), 0) |
|
|
elif option == "☀️ Increase Brightness": |
|
|
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) |
|
|
hsv[:, :, 2] = np.clip(hsv[:, :, 2] + brightness_level, 0, 255) |
|
|
return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) |
|
|
elif option == "⚡ Edge Detection": |
|
|
return cv2.Canny(image, 100, 200) |
|
|
elif option == "🔄 Rotate Image": |
|
|
(h, w) = image.shape[:2] |
|
|
center = (w // 2, h // 2) |
|
|
matrix = cv2.getRotationMatrix2D(center, rotation_angle, 1.0) |
|
|
return cv2.warpAffine(image, matrix, (w, h)) |
|
|
return image |
|
|
|
|
|
st.title("📷 Image Processing App") |
|
|
|
|
|
uploaded_file = st.file_uploader("📂 Upload an image...", type=["jpg", "png", "jpeg"]) |
|
|
|
|
|
if uploaded_file is not None: |
|
|
image = np.array(Image.open(uploaded_file)) |
|
|
|
|
|
col1, col2 = st.columns(2) |
|
|
with col1: |
|
|
st.markdown("### 🏞️ Original Image") |
|
|
st.image(image, use_container_width=True) |
|
|
|
|
|
with col2: |
|
|
st.markdown("### 🎨 Processed Image") |
|
|
options = [ |
|
|
"🖼️ Original", |
|
|
"🖤 Convert to Grayscale", |
|
|
"🌈 Convert to Color", |
|
|
"🔄 Rotate Image", |
|
|
"🌪️ Blur Image", |
|
|
"⚡ Edge Detection", |
|
|
"☀️ Increase Brightness" |
|
|
] |
|
|
selected_option = st.selectbox("🎛️ Select an Operation", options) |
|
|
|
|
|
brightness_level = 0 |
|
|
rotation_angle = 0 |
|
|
|
|
|
if selected_option == "☀️ Increase Brightness": |
|
|
brightness_level = st.slider("🔆 Brightness Level", -100, 100, 0) |
|
|
elif selected_option == "🔄 Rotate Image": |
|
|
rotation_angle = st.slider("🌀 Rotation Angle", -180, 180, 0) |
|
|
|
|
|
processed_image = process_image(image, selected_option, brightness_level, rotation_angle) |
|
|
|
|
|
if len(processed_image.shape) == 2: |
|
|
st.image(processed_image, use_container_width=True, channels="GRAY") |
|
|
else: |
|
|
st.image(processed_image, use_container_width=True) |
|
|
|
