Issue 008 (#10)

* Created package folder

* PEP8 style fixes

* Basic CLI argument handling with argparse

* OpenCV now >3

* Fixed license info related to third party: OpenCV

* Added gitignore

* Ready for PyPI:test

.gitignore

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+# Created by .gitignore support plugin (hsz.mobi)
+### Python template
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+.idea/
+.ropeproject/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.cache
+nosetests.xml
+coverage.xml
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Vim nonsense
+*.swp

MANIFEST.in

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+include README.md LICENSE
+include autocrop/*

autocrop/__init__.py

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+import argparse
+import os
+import sys
+
+# Inject vendored directory into system path.
+v_path = os.path.abspath(os.path.sep.join([os.path.dirname(os.path.realpath(__file__)), 'vendor']))
+sys.path.insert(0, v_path)
+
+# Inject patched directory into system path.
+v_path = os.path.abspath(os.path.sep.join([os.path.dirname(os.path.realpath(__file__)), 'patched']))
+sys.path.insert(0, v_path)
+
+from .autocrop import cli
+
+if __name__ == '__main__':
+    cli()
+

autocrop/__version__.py

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+__title__ = 'autocrop'
+__description__ = 'Automatically crops faces from batches of pictures'
+__author__ = 'François Leblanc'
+__version__ = '0.1.1'

autocrop/autocrop.py

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+from __future__ import print_function
+
+import argparse
+from contextlib import contextmanager
+import cv2
+import glob
+import numpy as np
+import os
+import shutil
+import sys
+
+from .__version__ import __title__, __description__, __author__, __version__
+
+
+# Internal variables
+fixexp = True                 # Flag to fix underexposition
+marker = False                # Flag for gamma correct
+INPUT_FILETYPES = ['*.jpg', '*.jpeg']
+INCREMENT = 0.06
+GAMMA_THRES = 0.001 
+GAMMA = 0.90
+FACE_RATIO = 6
+
+# Load XML Resource
+cascFile= 'haarcascade_frontalface_default.xml'
+d = os.path.dirname(sys.modules['autocrop'].__file__)
+cascPath = os.path.join(d, cascFile)
+
+# Define directory change within context
+@contextmanager
+def cd(newdir):
+    prevdir = os.getcwd()
+    os.chdir(os.path.expanduser(newdir))
+    try:
+        yield
+    finally:
+        os.chdir(prevdir)
+
+# Define simple gamma correction fn
+def gamma(img, correction):
+    img = cv2.pow(img/255.0, correction)
+    return np.uint8(img*255)
+
+def main(path, fheight, fwidth):
+    """Given path containing image files to process, will
+    1) copy them to `path/bkp`, and 
+    2) create face-cropped versions and place them in `path/crop`
+    """
+    errors = 0
+    # Create the haar cascade
+    faceCascade = cv2.CascadeClassifier(cascPath)
+
+    with cd(path):
+        files_grabbed = []
+        for files in INPUT_FILETYPES:
+            files_grabbed.extend(glob.glob(files))
+
+        for file in files_grabbed:
+            image = cv2.imread(file)
+            gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+            # Scale the image
+            height, width = (image.shape[:2])
+            minface = int(np.sqrt(height*height + width*width) / 8)
+
+            # ====== Detect faces in the image ======
+            faces = faceCascade.detectMultiScale(
+                gray,
+                scaleFactor=1.1,
+                minNeighbors=5,
+                minSize=(minface, minface),
+                flags = cv2.CASCADE_FIND_BIGGEST_OBJECT | cv2.CASCADE_DO_ROUGH_SEARCH
+            )
+
+            # Handle no faces
+            if len(faces) == 0: 
+                print(' No faces can be detected in file {0}.'.format(str(file)))
+                errors += 1
+                break
+
+            # Copy to /bkp
+            shutil.copy(file, 'bkp')
+
+            # Make padding from probable biggest face
+            x, y, w, h = faces[-1]
+            pad = h / FACE_RATIO
+
+            # Make sure padding is contained within picture
+            while True:  # decreases pad by 6% increments to fit crop into image. Can lead to very small faces.
+                if y-2*pad < 0 or y+h+pad > height or int(x-1.5*pad) < 0 or x+w+int(1.5*pad) > width:
+                    pad = (1 - INCREMENT) * pad
+                else:
+                    break
+
+            # Crop the image from the original
+            h1 = int(x-1.5*pad) 
+            h2 = int(x+w+1.5*pad)
+            v1 = int(y-2*pad)
+            v2 = int(y+h+pad)
+            image = image[v1:v2, h1:h2]
+
+            # Resize the damn thing
+            image = cv2.resize(image, (fheight, fwidth), interpolation = cv2.INTER_AREA)
+
+            # ====== Dealing with underexposition ======
+            if fixexp == True:
+                # Check if under-exposed
+                uexp = cv2.calcHist([gray], [0], None, [256], [0,256])
+
+                if sum(uexp[-26:]) < GAMMA_THRES * sum(uexp) :
+                    marker = True
+                    image = gamma(image, GAMMA)
+
+            # Write cropfile
+            cropfilename = '{0}'.format(str(file))
+            cv2.imwrite(cropfilename, image)
+
+            # Move files to /crop
+            shutil.move(cropfilename, 'crop')
+
+    # Stop and print timer
+    print(' {0} files have been cropped'.format(len(files_grabbed) - errors))
+
+def cli():
+    parser = argparse.ArgumentParser(description='Automatically crops faces from batches of pictures')
+    parser.add_argument('-p', '--path', default='photos', help='Path where images to crop are located')
+    parser.add_argument('-w', '--width', type=int, default=500, help='Width of the cropped files in pixels')
+    parser.add_argument('-H', '--height', type=int, default=500, help='Height of the cropped files in pixels')
+
+    args = parser.parse_args()
+    print('Processing images in folder:', args.path)
+
+    main(args.path, args.height, args.width)
+