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import streamlit as st
import cv2
import numpy as np
from PIL import Image
from io import BytesIO
# Function to apply Lightroom-like filters
def apply_filter(img):
# Convert PIL Image to OpenCV format
img = np.array(img)
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
# Exposure: Adjust brightness
exposure = -0.31
img = cv2.convertScaleAbs(img, alpha=1.0, beta=exposure * 100)
# Contrast
contrast = -18
alpha = 1 + contrast / 100.0 # Scaling factor
img = cv2.convertScaleAbs(img, alpha=alpha, beta=0)
# Highlights and Shadows
highlights = -100
shadows = 50
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
v = hsv[:, :, 2].astype(np.float32)
v = np.clip(v + highlights, 0, 255)
v = np.clip(v + shadows, 0, 255)
hsv[:, :, 2] = v.astype(np.uint8)
img = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
# Whites and Blacks
whites = 12
blacks = -20
img = np.clip(img + whites, 0, 255).astype(np.uint8)
img = np.clip(img + blacks, 0, 255).astype(np.uint8)
# Temperature and Tint
temp = -2
tint = 2
b, g, r = cv2.split(img)
b = np.clip(b + temp * 10, 0, 255).astype(np.uint8)
r = np.clip(r + tint * 10, 0, 255).astype(np.uint8)
img = cv2.merge((b, g, r))
# Vibrance
vibrance = 70
lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
l, a, b = cv2.split(lab)
a = np.clip(a * (1 + vibrance / 100.0), 0, 255).astype(np.uint8)
b = np.clip(b * (1 + vibrance / 100.0), 0, 255).astype(np.uint8)
img = cv2.merge((l, a, b))
img = cv2.cvtColor(img, cv2.COLOR_LAB2BGR)
# Saturation
saturation = 20
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
s = hsv[:, :, 1].astype(np.float32)
s = np.clip(s * (1 + saturation / 100.0), 0, 255).astype(np.uint8)
hsv[:, :, 1] = s
img = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
# Texture (Clarity approximation)
texture = 4
kernel = np.array([[-1, -1, -1], [-1, 8 + texture, -1], [-1, -1, -1]])
img = cv2.filter2D(img, -1, kernel)
# Sharpening
sharpening = 18
radius = 1.2
gaussian = cv2.GaussianBlur(img, (0, 0), sigmaX=radius)
img = cv2.addWeighted(img, 1 + sharpening / 100.0, gaussian, -sharpening / 100.0, 0)
return img
# Streamlit app
st.title("Classic Photo Editor")
st.write("Upload an image to apply the Lightroom-like filter.")
# Upload image
uploaded_file = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
if uploaded_file:
# Open the uploaded image
img = Image.open(uploaded_file)
# Display the original image
st.subheader("Original Image")
st.image(img, use_column_width=True)
# Apply the filter
st.subheader("Filtered Image")
filtered_img = apply_filter(img)
# Convert back to PIL Image for display
filtered_pil = Image.fromarray(cv2.cvtColor(filtered_img, cv2.COLOR_BGR2RGB))
st.image(filtered_pil, use_column_width=True)
# Provide download button
buf = BytesIO()
filtered_pil.save(buf, format="JPEG")
byte_im = buf.getvalue()
st.download_button(
label="Download Filtered Image",
data=byte_im,
file_name="filtered_image.jpg",
mime="image/jpeg"
)
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