tests(LiveFT): skeleton for testing the FFT

- for more confidence when replacing the FFT algorithm

LiveFT_testing.py

@@ -0,0 +1,50 @@
+import pymupdf
+import io
+from PIL import Image
+import cv2
+import numpy as np
+import sys
+from pathlib import Path
+
+paths = ("images/singleObjects", "images/arrays")
+
+def pixmapToCV(pix):
+    # Get the width and height of the pixmap
+    width = pix.width
+    height = pix.height
+
+    # Extract pixel data as a byte array
+    img_data = pix.samples
+
+    # Create a NumPy array from the byte data
+    img_array = np.frombuffer(img_data, dtype=np.uint8).reshape((height, width, pix.n))
+
+    # Convert from RGB to BGR if necessary (OpenCV uses BGR format)
+    if pix.n == 3:  # RGB
+        img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
+    elif pix.n == 4:  # RGBA
+        img_array = cv2.cvtColor(img_array, cv2.COLOR_RGBA2BGR)
+
+    return img_array
+
+def pdfToCV(pdf_path, page_number=0):
+    # Open the PDF file
+    pdf_document = pymupdf.open(pdf_path)
+
+    # Get the specified page
+    page = pdf_document.load_page(page_number)
+
+    # Convert PIL image to OpenCV format (BGR)
+    cv2_image = pixmapToCV(page.get_pixmap())
+
+    return cv2_image  # Return the OpenCV frame
+
+# calc the fft for every image in each path given above
+for pdf_path in [pdf for p in paths for pdf in Path(p).iterdir()]:
+    print(pdf_path)
+    frame = pdfToCV(pdf_path)
+    if frame is None:
+        continue
+    cv2.imshow("Extracted Image", frame)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()