commit 84277e4e7ec3481dd9ae171f70638bd1f7616b49
Author: Gasper Spagnolo <gasper.spagnolo@outlook.com>
Date:   Sat Oct 15 17:07:41 2022 +0200

    first commit

diff --git a/assignment1/.gitignore b/assignment1/.gitignore
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+__pycache__
+.venv/
diff --git a/assignment1/UZ_utils.py b/assignment1/UZ_utils.py
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+"""
+Before the first run, you need to have all necessary Python packages installed. For
+that we highly recommend firstly creating Virtual Environment, to have your
+development environment seperated from other projects (https://docs.python.org/3/tutorial/venv.html).
+
+In system terminal then run: "pip install numpy opencv-python matplotlib Pillow"
+"""
+
+import numpy as np
+import cv2 as cv2
+from matplotlib import pyplot as plt
+from PIL import Image
+from typing import Union
+
+
+def imread(path: str) -> np.float64:
+    """
+    Reads an image in RGB order. Image type is transformed from uint8 to float, and
+    range of values is reduced from [0, 255] to [0, 1].
+    """
+    I = Image.open(path).convert('RGB')  # PIL image.
+    I = np.asarray(I)  # Converting to Numpy array.
+    I = I.astype(np.float64) / 255
+    return np.float64(I)
+
+
+def imread_gray(path: str) -> np.float64:
+    """
+    Reads an image in gray. Image type is transformed from uint8 to float, and
+    range of values is reduced from [0, 255] to [0, 1].
+    """
+    I = Image.open(path).convert('L')  # PIL image opening and converting to gray.
+    I = np.asarray(I)  # Converting to Numpy array.
+    I = I.astype(np.float64) / 255
+    return np.float64(I)
+
+
+def imshow(img: Union[np.float64, np.uint8], title=None) -> None:
+    """
+    Shows an image. Image can be of types:
+    - type uint8, in range [0, 255]
+    - type float, in range [0, 1]
+    """
+
+    if len(img.shape) == 3:
+        plt.imshow(img)  # if type of data is "float", then values have to be in [0, 1]
+    else:
+        plt.imshow(img)
+        plt.set_cmap('gray')  # also "hot", "nipy_spectral"
+        plt.colorbar()
+    if title is not None:
+        plt.title(title)
+
+    plt.show()
+
+
+def signal_show(*signals):
+    """
+    Plots all given 1D signals in the same plot.
+    Signals can be Python lists or 1D numpy array.
+    """
+    for s in signals:
+        if type(s) == np.ndarray:
+            s = s.squeeze()
+        plt.plot(s)
+    plt.show()
+
+
+def convolve(I: np.ndarray, *ks):
+    """
+    Convolves input image I with all given kernels.
+
+    :param I: Image, should be of type float64 and scaled from 0 to 1.
+    :param ks: 2D Kernels
+    :return: Image convolved with all kernels.
+    """
+    for k in ks:
+        k = np.flip(k)  # filter2D performs correlation, so flipping is necessary
+        I = cv2.filter2D(I, cv2.CV_64F, k)
+    return I
+
+
+if __name__ == '__main__':  # False if this file is imported to another file and executed from there.
+
+    # For this to work you need to put an image "image.jpg" to where you run the script.
+
+    # Read an image in rgb (check the code in "UZ_utils" for details).
+    I = imread('image.jpg')  # see the definition above
+    imshow(I, 'rgb')
+    print(I.shape, I.dtype, np.max(I))
+
+    # gray
+    I = imread_gray('image.jpg')  # see the definition above
+    imshow(I, 'gray')
+    print(I.shape, I.dtype, np.max(I))
+
+    # Image filtering.
+    I = np.zeros((20, 20), dtype=float)
+    I[5, 5] = 1
+    k = np.array([[1, 2, 3, 4, 5]], dtype=float)
+    I = convolve(I, k, k.T)  # see the definition above
+    imshow(I)
+
+    # Plotting 1D signal.
+    x = np.arange(0, 10, .1)  # From 0 to 10 with 0.1 step.
+    y = np.sin(x)
+    signal_show(y, 2 * y)  # see the definition above
diff --git a/assignment1/images/bird.jpg b/assignment1/images/bird.jpg
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diff --git a/assignment1/images/eagle.jpg b/assignment1/images/eagle.jpg
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diff --git a/assignment1/images/umbrellas.jpg b/assignment1/images/umbrellas.jpg
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diff --git a/assignment1/instructions.pdf b/assignment1/instructions.pdf
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diff --git a/assignment1/solution.py b/assignment1/solution.py
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+import UZ_utils as uz
+import numpy as np
+
+##
+## EXCERCISE 1
+##
+
+# Display image
+def one_a() -> np.float64:
+    image = uz.imread('./images/bird.jpg')
+    print(image.shape)
+    print(image.dtype)
+    uz.imshow(image, 'Bird')
+    return np.float64(image) 
+
+# Convert loaded image into grayscale
+def one_b(image: np.float64) -> None:
+    print(image)
+    
+
+def main():
+    image = one_a()
+    one_b(image)
+
+
+
+if __name__ == "__main__":
+    main()