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| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| # Function to compare two images and highlight differences | |
| def compare_images(mockup, ui_screenshot, check_text, check_color, check_spacing): | |
| # Convert images to numpy arrays | |
| mockup_array = np.array(mockup) | |
| ui_screenshot_array = np.array(ui_screenshot) | |
| # Resize images to the same dimensions | |
| if mockup_array.shape != ui_screenshot_array.shape: | |
| height, width = max(mockup_array.shape[0], ui_screenshot_array.shape[0]), max(mockup_array.shape[1], ui_screenshot_array.shape[1]) | |
| mockup_array = cv2.resize(mockup_array, (width, height)) | |
| ui_screenshot_array = cv2.resize(ui_screenshot_array, (width, height)) | |
| # Convert images to grayscale | |
| mockup_gray = cv2.cvtColor(mockup_array, cv2.COLOR_RGB2GRAY) | |
| ui_screenshot_gray = cv2.cvtColor(ui_screenshot_array, cv2.COLOR_RGB2GRAY) | |
| # Compute the absolute difference between the two images | |
| difference = cv2.absdiff(mockup_gray, ui_screenshot_gray) | |
| # Threshold the difference image to get a binary image | |
| _, thresh = cv2.threshold(difference, 30, 255, cv2.THRESH_BINARY) | |
| # Find contours of the differences | |
| contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) | |
| # Create a copy of the original image to draw the differences | |
| highlighted_image = mockup_array.copy() | |
| # Draw red circles around the differences | |
| for contour in contours: | |
| if cv2.contourArea(contour) > 100: # Filter out small differences | |
| x, y, w, h = cv2.boundingRect(contour) | |
| cv2.circle(highlighted_image, (x + w // 2, y + h // 2), 10, (255, 0, 0), -1) | |
| # Convert the highlighted image back to RGB for display | |
| highlighted_image_rgb = cv2.cvtColor(highlighted_image, cv2.COLOR_BGR2RGB) | |
| # Generate a report based on the selected options | |
| report = "Comparison Report:\n" | |
| if check_text: | |
| report += "Text Differences: This feature requires advanced text recognition.\n" | |
| if check_color: | |
| report += "Color Differences: This feature requires color analysis.\n" | |
| if check_spacing: | |
| report += "Spacing Differences: This feature requires layout analysis.\n" | |
| return highlighted_image_rgb, report | |
| # Create the Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("## Welcome to the UI Difference Spotter!") | |
| gr.Markdown("Please upload the design mockup and the developed UI screenshot you want to compare.") | |
| with gr.Row(): | |
| mockup_upload = gr.Image(label="Upload Design Mockup", type="pil") | |
| ui_screenshot_upload = gr.Image(label="Upload Developed UI Screenshot", type="pil") | |
| with gr.Row(): | |
| check_text = gr.Checkbox(label="Check Text Differences", value=True) | |
| check_color = gr.Checkbox(label="Check Color Differences", value=True) | |
| check_spacing = gr.Checkbox(label="Check Spacing Differences", value=True) | |
| with gr.Row(): | |
| compare_button = gr.Button("Compare Images") | |
| with gr.Row(): | |
| highlighted_image = gr.Image(label="Highlighted Differences") | |
| report_output = gr.Textbox(label="Comparison Details", interactive=False) | |
| # Define the event listener for the compare button | |
| compare_button.click( | |
| fn=compare_images, | |
| inputs=[mockup_upload, ui_screenshot_upload, check_text, check_color, check_spacing], | |
| outputs=[highlighted_image, report_output] | |
| ) | |
| # Launch the Gradio app | |
| if __name__ == "__main__": | |
| demo.launch(show_error=True) | |