Adding MVP code

app.py

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+import cv2
+import numpy as np
+from skimage.metrics import structural_similarity as ssim  # works after installing scikit-image
+import gradio as gr
+
+# ---------------------------
+# Function to compare images
+# ---------------------------
+def compare_images(img1, img2):
+    # Convert to grayscale
+    grayA = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
+    grayB = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+
+    # Resize to match (if slightly different sizes)
+    if grayA.shape != grayB.shape:
+        h = min(grayA.shape[0], grayB.shape[0])
+        w = min(grayA.shape[1], grayB.shape[1])
+        grayA = cv2.resize(grayA, (w, h))
+        grayB = cv2.resize(grayB, (w, h))
+
+    # Compute SSIM score + diff map
+    score, diff = ssim(grayA, grayB, full=True)
+    diff = (diff * 255).astype("uint8")
+
+    # Threshold the diff
+    thresh = cv2.threshold(diff, 0, 255,
+                           cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
+
+    # Find contours of differences
+    cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
+                               cv2.CHAIN_APPROX_SIMPLE)
+
+    # Draw bounding boxes on differences
+    img_diff = img2.copy()
+    for c in cnts:
+        (x, y, w, h) = cv2.boundingRect(c)
+        cv2.rectangle(img_diff, (x, y), (x + w, y + h), (0, 0, 255), 2)
+
+    summary = f"Similarity Score: {score:.4f}. Changes detected: {len(cnts)}"
+
+    return img1, img2, img_diff, summary
+
+
+# ---------------------------
+# Gradio UI
+# ---------------------------
+with gr.Blocks() as demo:
+    gr.Markdown("## 🖼️ Visual Regression\nUpload two screenshots to detect differences.")
+
+    with gr.Row():
+        img1 = gr.Image(type="numpy", label="Baseline Screenshot")
+        img2 = gr.Image(type="numpy", label="New Screenshot")
+
+    btn = gr.Button("Compare")
+
+    with gr.Row():
+        out1 = gr.Image(label="Baseline")
+        out2 = gr.Image(label="New")
+        out3 = gr.Image(label="Differences Highlighted")
+
+    summary = gr.Label(label="Summary")
+
+    btn.click(fn=compare_images, inputs=[img1, img2],
+              outputs=[out1, out2, out3, summary])
+
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+opencv-python-headless
+scikit-image
+gradio
+numpy