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import gradio as gr
import cv2
import numpy as np
from skimage.metrics import structural_similarity as ssim
def preprocess_image(image, blur_value):
# Convert to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Apply Gaussian blur to reduce noise
blurred = cv2.GaussianBlur(gray, (blur_value, blur_value), 0)
return blurred
def compare_images(image1, image2, blur_value, technique):
# Preprocess images
gray1 = preprocess_image(image1, blur_value)
gray2 = preprocess_image(image2, blur_value)
# Compute SSIM between the two images
score, diff = ssim(gray1, gray2, full=True)
diff = (diff * 255).astype("uint8")
if technique == "Adaptive Threshold":
_, thresh = cv2.threshold(diff, 30, 255, cv2.THRESH_BINARY_INV)
elif technique == "Otsu's Threshold":
_, thresh = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)
else: # Default to simple binary threshold
_, thresh = cv2.threshold(diff, 50, 255, cv2.THRESH_BINARY)
# Find contours of differences
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Filter out small noise using contour area threshold
filtered_contours = [cnt for cnt in contours if cv2.contourArea(cnt) > 500]
# Create a mask to isolate only the significant added object
mask = np.zeros_like(image1)
cv2.drawContours(mask, filtered_contours, -1, (255, 255, 255), thickness=cv2.FILLED)
# Apply the mask to highlight the object added in the second image
highlighted = cv2.bitwise_and(image2, mask)
# Show the raw difference in magenta
diff_colored = cv2.merge([np.zeros_like(diff), diff, diff])
return highlighted, diff_colored
demo = gr.Interface(
fn=compare_images,
inputs=[
gr.Image(type="numpy", label="Image Without Object"),
gr.Image(type="numpy", label="Image With Object"),
gr.Slider(minimum=1, maximum=15, step=2, value=5, label="Gaussian Blur"),
gr.Dropdown(["Adaptive Threshold", "Otsu's Threshold", "Simple Binary"], label="Thresholding Technique", value="Adaptive Threshold")
],
outputs=[
gr.Image(type="numpy", label="Highlighted Differences"),
gr.Image(type="numpy", label="Raw Difference (Magenta)")
],
title="Object Difference Highlighter",
description="Upload two images: one without an object and one with an object. The app will highlight only the newly added object and show the real differences in magenta."
)
demo.launch()
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