Criar projeto de imagens processing para publicacao

README.md

@@ -2,22 +2,23 @@
 
 Description. 
 The package package_name is used to:
-	- 
-	-
+	Processing:
+	   	- Histogram matching
+		- Sttructural similarity
+		- Resize image
+	Utils:
+		- Read image
+		- Save image
+		- Plot image
+		- Plot result
+		- Plot histogram
 
 ## Installation
 
 Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name
 
 ```bash
-pip install package_name
-```
-
-## Usage
-
-```python
-from package_name import file1_name
-file1_name.my_function()
+pip install image-processing-package
 ```
 
 ## Author

image-processing-package/image_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 de same shape."
+    gray_image1 = rgb2gray(image1)
+    gray_image2 = rgb2gray(image2)
+    (score, difference_image) = structural_similarity(gray_image1, gray_image2, full=True)
+    print("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

image-processing-package/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

image-processing-package/utils/io.py

@@ -0,0 +1,8 @@
+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) 

image-processing-package/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.tight_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()

setup.py

@@ -7,14 +7,14 @@
     requirements = f.read().splitlines()
 
 setup(
-    name="package_name",
+    name="image-processing-package",
     version="0.0.1",
-    author="my_name",
-    author_email="my_email",
-    description="My short description",
+    author="Heliton",
+    author_email="",
+    description="Processar Imagens",
     long_description=page_description,
     long_description_content_type="text/markdown",
-    url="my_github_repository_project_link"
+    url="https://github.com/hprimo/image-processing-package",
     packages=find_packages(),
     install_requires=requirements,
     python_requires='>=3.8',