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assignment1/UZ_utils.py

@@ -11,9 +11,10 @@ import cv2 as cv2
 from matplotlib import pyplot as plt
 from PIL import Image
 from typing import Union
+import numpy.typing as npt
 
 
-def imread(path: str) -> np.float64:
+def imread(path: str) -> npt.NDArray[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].
@@ -21,10 +22,10 @@ def imread(path: str) -> np.float64:
     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)
+    return I
 
 
-def imread_gray(path: str) -> np.float64:
+def imread_gray(path: str) -> npt.NDArray[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].
@@ -32,10 +33,10 @@ def imread_gray(path: str) -> np.float64:
     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)
+    return I
 
 
-def imshow(img: Union[np.float64, np.uint8], title=None) -> None:
+def imshow(img: Union[npt.NDArray[np.float64], np.uint8], title=None) -> None:
     """
     Shows an image. Image can be of types:
     - type uint8, in range [0, 255]

assignment1/solution.py

@@ -1,5 +1,6 @@
 import UZ_utils as uz
 import numpy as np
+import numpy.typing as npt
 
 #######################################
 # EXCERCISE 1: Basic image processing #
@@ -9,23 +10,28 @@ def excercise_one() -> None:
     image = one_a()
     one_b(image)
     
-
 # Display image
-def one_a() -> np.float64:
+def one_a() -> npt.NDArray[np.float64]:
     image = uz.imread('./images/bird.jpg')
-    print(image.shape)
-    print(image.dtype)
     uz.imshow(image, 'Birdie')
-    return np.float64(image) 
+    return image
 
 # Convert loaded image into grayscale
-def one_b(image: np.float64) -> None:
-    print(image)
+def one_b(image: npt.NDArray[np.float64]) -> None:
+    grayscale_image = np.zeros(image.shape[:2])
     
+    for i in range(image.shape[0]):
+        for j in range(image.shape[1]):
+            grayscale_image[i, j] = (image[i, j, 0] + image[i,j, 1] + image[i, j, 2]) / 3
 
+    uz.imshow(grayscale_image, 'Birdie grayscale')
+
+def one_c():
+    #todo
+    assert(1 == 1)
+    
 def main() -> None:
     excercise_one() 
 
-
 if __name__ == "__main__":
     main()