inital commit

adaptive_threshold/__init__.py

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+#!/usr/bin/env python
+"""This programm converts an image into an adaptiveThreshold one.
+
+Usage:
+  adaptive_threshold -i <source> -o <output> [-s <int>] [-b <int>] [-n]
+  adaptive_threshold -h | --help
+
+Options:
+  -i <source> --input <source>      Path to input image
+  -o <target> --output <target>     Path to output image
+  -b <int> --brightness <int>       Change brightness of the output image
+  -s <int> --size <int>             Size of local area
+  -n --invert                       Flip black/white
+  -h --help                         Show this screen.
+"""
+from docopt import docopt
+import numpy as np
+import cv2 as cv
+
+def apply(img, size=21, brightness=2):
+    size = size or 21
+    brightness = brightness or 2
+    return cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY, int(size), int(brightness))
+
+# face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
+# faces = face_cascade.detectMultiScale(img, 1.3, 5)
+# for (x,y,w,h) in faces:
+#     # To draw a rectangle in a face
+#     #cv.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2)
+#     roi_gray = img[y:y+h, x:x+w]
+#     thresh = roi_gray.mean()
+#     # img[x:x+w,y:y+h]
+#
+#     ret,th1 = cv.threshold(img, thresh*1.2, 255,cv.THRESH_BINARY)
+
+def main():
+    arguments = docopt(__doc__)
+    img = cv.imread(arguments["--input"],0)
+    out = apply(img,arguments["--size"],arguments["--brightness"])
+    if arguments["--invert"]:
+        out = np.abs(out==0)*255
+    cv.imwrite(arguments["--output"], out)
+
+if __name__ == '__main__':
+    main()

setup.py

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+from setuptools import setup, find_packages
+
+setup(
+    name='adaptive_threshold',
+    version='0.0.1',
+    packages=find_packages(include=['adaptive_threshold', 'adaptive_threshold.*']),
+    install_requires=[
+        'opencv-python-headless',
+        'numpy>=1.14.5',
+        'docopt',
+    ],
+    entry_points={
+      'console_scripts': ['adaptive_threshold=adaptive_threshold:main']
+    }
+)