Create app.py

app.py

@@ -0,0 +1,111 @@
+import gradio as gr
+import fitz  # PyMuPDF
+import cv2
+from pdf2image import convert_from_path
+import numpy as np
+import os
+from fpdf import FPDF
+
+# Convert PDFs to images
+def convert_pdf_to_images(pdf_path, dpi=300):
+    images = convert_from_path(pdf_path, dpi=dpi, poppler_path="/usr/bin")
+    return [cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) for image in images]
+
+# Align images
+def align_images(img1, img2):
+    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
+    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+    orb = cv2.ORB_create()
+    kp1, des1 = orb.detectAndCompute(gray1, None)
+    kp2, des2 = orb.detectAndCompute(gray2, None)
+    bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
+    matches = bf.match(des1, des2)
+    matches = sorted(matches, key=lambda x: x.distance)
+    src_pts = np.float32([kp1[m.queryIdx].pt for m in matches]).reshape(-1, 1, 2)
+    dst_pts = np.float32([kp2[m.trainIdx].pt for m in matches]).reshape(-1, 1, 2)
+    matrix, _ = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
+
+    # Validate if alignment is good enough
+    if matrix is None or len(matches) < 10:  # Check if sufficient matches exist
+        raise ValueError("Alignment failed. Insufficient matches between images.")
+
+    aligned_img = cv2.warpPerspective(img2, matrix, (img1.shape[1], img1.shape[0]))
+    return aligned_img
+
+# Compare visual changes
+def compare_visual_changes(orig_img, edit_img):
+    diff = cv2.absdiff(orig_img, edit_img)
+    gray_diff = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
+
+    # Apply Gaussian blur to reduce noise
+    blurred_diff = cv2.GaussianBlur(gray_diff, (5, 5), 0)
+
+    # Apply thresholding
+    _, thresh = cv2.threshold(blurred_diff, 70, 255, cv2.THRESH_BINARY)
+
+    # Morphological operations to clean noise
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
+    cleaned = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
+
+    contours, _ = cv2.findContours(cleaned, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    overlay = edit_img.copy()
+
+    for cnt in contours:
+        if cv2.contourArea(cnt) > 100:  # Filter out small regions
+            x, y, w, h = cv2.boundingRect(cnt)
+            cv2.rectangle(overlay, (x, y), (x + w, y + h), (0, 0, 255), 2)  # Red bounding box
+
+    return overlay
+
+# Generate visual comparison report
+def generate_visual_report(images, output_path):
+    pdf = FPDF()
+    for img in images:
+        temp_path = "temp_image.png"
+        cv2.imwrite(temp_path, img)
+        pdf.add_page()
+        pdf.image(temp_path, x=10, y=10, w=190)
+        os.remove(temp_path)
+
+    pdf.output(output_path)
+    return output_path
+
+# Perform only visual comparison
+def generate_visual_comparison(original_pdf, edited_pdf):
+    original_images = convert_pdf_to_images(original_pdf)
+    edited_images = convert_pdf_to_images(edited_pdf)
+
+    visual_combined_images = []
+    for orig_img, edit_img in zip(original_images, edited_images):
+        aligned_img = align_images(orig_img, edit_img)
+        highlighted_img = compare_visual_changes(orig_img, aligned_img)
+        visual_combined_images.append(np.hstack((orig_img, highlighted_img)))
+
+    # Generate visual changes report
+    visual_report_path = generate_visual_report(
+        visual_combined_images, "outputs/visual_changes.pdf"
+    )
+
+    return visual_report_path
+
+# Gradio interface function
+def pdf_visual_comparison(original_pdf, edited_pdf):
+    visual_path = generate_visual_comparison(original_pdf.name, edited_pdf.name)
+    return visual_path
+
+# Gradio interface
+interface = gr.Interface(
+    fn=pdf_visual_comparison,
+    inputs=[
+        gr.File(label="Upload Original PDF", file_types=[".pdf"]),
+        gr.File(label="Upload Edited PDF", file_types=[".pdf"])
+    ],
+    outputs=[
+        gr.File(label="Download Visual Changes Report")
+    ],
+    title="PDF Visual Comparison Tool",
+    description="Upload two PDFs: the original and the edited version. The tool generates a visual changes report."
+)
+
+if __name__ == "__main__":
+    interface.launch()