Adding Python script to generate SystemC TB data

- Adding installation script of Python OpenCV in Linux.
- Adding script to read an image, convert it to gray scale, apply sobel
  in x and y, and then combine them in a single one. Script also
  generates output images for each of the stage.
- Adding a JupyterNotebook version of the script that can be run also in
  Collab tool.

Author: ErickOF

tools/datagen/datagen.ipynb

@@ -0,0 +1,88 @@
+#!/usr/bin/python3
+"""
+Script to generate the data required for SystemC testbench.
+"""
+from typing import Tuple
+
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+def apply_sobel_filter(image_path: str
+    )-> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
+    """Applies the Sobel filter in X and Y to a input image and returns each
+    step.
+
+    Args:
+        image_path (str): Path to the input image
+
+    Returns:
+        Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: A tuple
+            containing the gray image, the sobel in x, the sobel in y, and the
+            sobel combining x and y.
+    """
+    # Read the image
+    image: np.ndarray = cv2.imread(image_path)
+
+    # BGR to grayscale
+    gray_img: np.ndarray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Apply Sobel in x direction
+    sobel_x_img: np.ndarray = cv2.Sobel(gray_img, cv2.CV_64F, 1, 0, ksize=3)
+    sobel_x_uint8: np.ndarray = np.uint8(np.absolute(sobel_x_img))
+
+    # Apply Sobel in y direction
+    sobel_y_img: np.ndarray = cv2.Sobel(gray_img, cv2.CV_64F, 0, 1, ksize=3)
+    sobel_y_uint8: np.ndarray = np.uint8(np.absolute(sobel_y_img))
+
+    # Combine sobel
+    sobel_combined_img: np.ndarray = cv2.magnitude(sobel_x_img, sobel_y_img)
+
+    # Convert to 8-bit image
+    sobel_combined_uint8: np.ndarray = np.uint8(np.absolute(sobel_combined_img))
+
+    # Display the results
+    plt.figure(figsize=(10, 8))
+
+    plt.subplot(2, 2, 1)
+    plt.title('Original Image')
+    plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+    plt.axis('off')
+
+    plt.subplot(2, 2, 2)
+    plt.title('Grayscale Image')
+    plt.imshow(gray_img, cmap='gray')
+    plt.axis('off')
+
+    plt.subplot(2, 2, 3)
+    plt.title('Sobel X')
+    plt.imshow(np.uint8(np.absolute(sobel_x_img)), cmap='gray')
+    plt.axis('off')
+
+    plt.subplot(2, 2, 4)
+    plt.title('Sobel Y')
+    plt.imshow(np.uint8(np.absolute(sobel_y_img)), cmap='gray')
+    plt.axis('off')
+
+    plt.figure(figsize=(5, 5))
+    plt.title('Sobel Combined')
+    plt.imshow(sobel_combined_uint8, cmap='gray')
+    plt.axis('off')
+
+    plt.show()
+
+    return (gray_img, sobel_x_uint8, sobel_y_uint8, sobel_combined_uint8)
+
+
+if __name__ == '__main__':
+    img_name: str = 'car'
+    img_ext: str = 'jpg'
+    img_path: str = f'src/imgs/{img_name}.{img_ext}'
+    gray, sobel_x, sobel_y, sobel_combined = apply_sobel_filter(img_path)
+
+    cv2.imwrite(f'src/imgs/{img_name}_grayscale_image.{img_ext}', gray)
+    cv2.imwrite(f'src/imgs/{img_name}_sobel_x_result.{img_ext}', np.uint8(np.absolute(sobel_x)))
+    cv2.imwrite(f'src/imgs/{img_name}_sobel_y_result.{img_ext}', np.uint8(np.absolute(sobel_y)))
+    cv2.imwrite(f'src/imgs/{img_name}_sobel_combined_result.{img_ext}', sobel_combined)
+

tools/datagen/datagen.py

@@ -0,0 +1,5 @@
+#!/bin/bash
+
+sudo pip3 install opencv-python
+
+python3 -c "import cv2; print(f'OpenCV: {cv2.__version__}')"