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Resize and crop an image based on OpenCV detected faces
import sys
from PIL import Image, ImageDraw
import cv
except ImportError:
print 'Could not import cv, trying opencv'
import as cv
def main():
source_image ='example.jpg')
source_width, source_height = source_image.size
print 'Image is {}x{}'.format(source_width, source_height)
target_width = 1000
target_height = 200
# Make image a reasonable size to work with. Using the source_height will
# make sure it's just resized to the target_width
source_image.thumbnail((target_width, source_height), Image.ANTIALIAS)
# Find the faces and show us where they are
faces = faces_from_pil_image(source_image)
faces_found_image = draw_faces(source_image, faces)
# Get details about where the faces are so we can crop
top_of_faces = top_face_top(faces)
bottom_of_faces = bottom_face_bottom(faces)
all_faces_height = bottom_of_faces - top_of_faces
print 'Faces are {} pixels high'.format(all_faces_height)
if all_faces_height >= target_width:
print 'Faces take up more than the final image, you need better logic'
exit_code = 1
# Figure out where to crop and show the results
face_buffer = 0.5 * (target_height - all_faces_height)
top_of_crop = int(top_of_faces - face_buffer)
coords = (0, top_of_crop, target_width, top_of_crop + target_height)
print 'Cropping to', coords
final_image = source_image.crop(coords)
exit_code = 0
return exit_code
def faces_from_pil_image(pil_image):
"Return a list of (x,y,h,w) tuples for faces detected in the PIL image"
storage = cv.CreateMemStorage(0)
facial_features = cv.Load('haarcascade_frontalface_alt.xml', storage=storage)
cv_im = cv.CreateImageHeader(pil_image.size, cv.IPL_DEPTH_8U, 3)
cv.SetData(cv_im, pil_image.tostring())
faces = cv.HaarDetectObjects(cv_im, facial_features, storage)
# faces includes a `neighbors` field that we aren't going to use here
return [f[0] for f in faces]
def top_face_top(faces):
coords = [f[1] for f in faces]
# Top left corner is 0,0 so we need the min for highest face
return min(coords)
def bottom_face_bottom(faces):
# Top left corner is 0,0 so we need the max for lowest face. Also add the
# height of the faces so that we get the bottom of it
coords = [f[1] + f[3] for f in faces]
return max(coords)
def draw_faces(image_, faces):
"Draw a rectangle around each face discovered"
image = image_.copy()
drawable = ImageDraw.Draw(image)
for x, y, w, h in faces:
absolute_coords = (x, y, x + w, y + h)
return image
if __name__ == '__main__':
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