app.py

import cv2
import numpy as np
import gradio as gr

def sift_ransac_matching(image, template):
    # Convert to grayscale
    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    gray_template = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY)

    # Initialize SIFT detector
    sift = cv2.SIFT_create()

    # Find the keypoints and descriptors with SIFT
    kp1, des1 = sift.detectAndCompute(gray_image, None)
    kp2, des2 = sift.detectAndCompute(gray_template, None)

    # BFMatcher with default params
    bf = cv2.BFMatcher()
    matches = bf.knnMatch(des1, des2, k=2)

    # Apply ratio test
    good_matches = []
    for m, n in matches:
        if m.distance < 0.75 * n.distance:
            good_matches.append(m)

    if len(good_matches) > 4:
        # Extract location of good matches
        src_pts = np.float32([kp1[m.queryIdx].pt for m in good_matches]).reshape(-1, 1, 2)
        dst_pts = np.float32([kp2[m.trainIdx].pt for m in good_matches]).reshape(-1, 1, 2)

        # Use RANSAC to find homography
        M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)

        if M is not None:
            # Compute the match score
            num_matches = np.sum(mask)
            match_score = num_matches / len(good_matches)  # Matching score as a ratio

            # Set a threshold for match score
            threshold = 0.8  # Adjust this threshold as needed

            # Determine if the template is found based on the match score
            if match_score >= threshold:
                return "Template found"
            else:
                return "Template not found"
        else:
            return "Template not found"
    else:
        return "Not enough good matches are found. Template not found"

# Gradio interface
iface = gr.Interface(
    fn=sift_ransac_matching,
    inputs=[
        gr.Image(type="numpy", label="Image"),
        gr.Image(type="numpy", label="Template"),
    ],
    outputs=gr.Text(label="Result"),
    title="Advanced Template Matching",
    description="Upload an image and a template to check if the template is present in the image using SIFT and RANSAC.",
)

iface.launch()