Main

README.md

@@ -2,8 +2,15 @@
 
 Description. 
 The package package_name is used to:
-	- 
-	-
+	- Processing
+		- Histogram matching 
+		- Structural similaryty
+	- Utils:
+		- Read image
+		- Save image
+		- Plot image
+		- Plot result
+		- Plot histogram
 
 ## Installation
 
@@ -21,7 +28,7 @@ file1_name.my_function()
 ```
 
 ## Author
-My_name
+Vinicius
 
 ## License
 [MIT](https://choosealicense.com/licenses/mit/)

processing/combination.py

@@ -0,0 +1,17 @@
+import numpy as np
+from skimage.color import rgb2gray
+from skimage.exposure import match_histograms
+from skimage.metrics import structural_similarity
+
+def find_difference(image1, image2):
+    assert image1.shape == image2.shape, "Specify 2 images with the same shape"
+    gray_image1 = rgb2gray(image1)
+    gray_image2 = rgb2gray(image2)
+    (score, difference_image) = structural_similarity(gray_image1, gray_image2, full=True)
+    print(f"Similarity of the images:", score)
+    normalized_difference_image =(difference_image-np.min(difference_image))/(np.max(difference_image)-np.min(difference_image))
+    return normalized_difference_image
+
+def transfer_histogram(image1, image2):
+    matched_image = match_histograms(image1, image2, multichannel=True)
+    return matched_image

processing/transformation.py

@@ -0,0 +1,8 @@
+from skimage.transform import resize
+
+def resize_image(image, proportion):
+    assert 0 <= proportion  <= 1, "Specify a valid proportion between 0 and 1."
+    height = round(image.shape[0]*proportion)
+    width = round(image.shape[1]*proportion)
+    image_resized = resize(image, (height, width), anti_aliasing=True)
+    return image_resized 

requirements.txt

@@ -0,0 +1,3 @@
+matplotlib
+numpy
+scikit-image >= 0.16.1

setup.py

@@ -14,7 +14,7 @@
     description="My short description",
     long_description=page_description,
     long_description_content_type="text/markdown",
-    url="my_github_repository_project_link"
+    url="my_github_repository_project_link", #eu adicionei essa virgula, se der pau, remover
     packages=find_packages(),
     install_requires=requirements,
     python_requires='>=3.8',

utils/io.py

@@ -0,0 +1,7 @@
+from skimage.io import imread, imsave
+def read_image(path, is_gray = False):
+    image = imread(path, as_gray = is_gray)
+    return image
+
+def save_image(image, path):
+    imsave(path, image)

utils/plot.py

@@ -0,0 +1,28 @@
+import matplotlib.pyplot as plt
+
+def plot_image(image):
+    plt.figure(figsize=(12, 4))
+    plt.imshow(image, cmap='gray')
+    plt.axis('off')
+    plt.show()
+
+def plot_result(*args):
+    number_images = len(args)
+    fig, axis = plt.subplots(nrows=1, ncols = number_images, figsize=(12, 4))
+    names_lst = ['Image()'.format(i) for i in range(1, number_images)]
+    names_lst.append('Result')
+    for ax, name, image in zip(axis, names_lst, args):
+        ax.set_title(name)
+        ax.imshow(image, cmap = 'gray')
+        ax.axis('off')
+    fig.light_layout()
+    plt.show()
+
+def plot_histogram(image):
+    fig, axis = plt.subplots(nrows = 1, ncols = 3, figsize = (12, 4), sharex = True, sharey = True)
+    color_lst = ['red', 'green', 'blue']
+    for index, (ax, color) in enumerate(zip(axis, color_lst)):
+        ax.set_title('() histogram'.format(color.title()))
+        ax.hist(image[:, :, index].ravel(), bins = 256, color = color, alpha = 0.8)
+    fig.tight_layout
+    plt.show()