Spaces:
Sleeping
Sleeping
File size: 1,589 Bytes
3f4b254 525a687 3f4b254 a93abe5 3f4b254 a93abe5 3f4b254 a93abe5 3f4b254 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
import streamlit as st
import cv2
import numpy as np
from PIL import Image
st.title("📸Image Processing App")
# Upload image
uploaded_file = st.file_uploader("Upload an Image", type=["png", "jpg", "jpeg"])
if uploaded_file is not None:
image = Image.open(uploaded_file)
# Convert PIL image to OpenCV format
img_array = np.array(image)
# Show original image
st.subheader("Original vs Processed Image")
col1, col2 = st.columns(2)
with col1:
st.image(image, caption="Original Image", use_container_width=True)
processed_image = img_array # Initialize processed_image with original image
# Convert to Grayscale
if st.button("Convert to Grayscale"):
processed_image = cv2.cvtColor(img_array, cv2.COLOR_RGB2GRAY)
# Rotate Image
angle = st.slider("Select Rotation Angle", -180, 180, 0)
if st.button("Rotate Image"):
(h, w) = img_array.shape[:2]
center = (w // 2, h // 2)
matrix = cv2.getRotationMatrix2D(center, angle, 1.0)
processed_image = cv2.warpAffine(img_array, matrix, (w, h))
# Add Text Overlay
text = st.text_input("Enter text to overlay on the image", "Hello")
if st.button("Apply Text Overlay"):
image_copy = img_array.copy()
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(image_copy, text, (50, 50), font, 1, (255, 0, 0), 2, cv2.LINE_AA)
processed_image = image_copy
# Show processed image in the second column
with col2:
st.image(processed_image, caption="Processed Image", use_container_width=True)
|