def meme(self, top_text=" ", bottom_text=" ", filename=""):
if len(top_text) < 2:
top_text = " "
if len(bottom_text) < 2:
bottom_text = " "
img = ImageOps.expand(Image.open(filename), border=80, fill='white')
image_size = img.size
# find biggest font size that works
font_size = int(image_size[1] / 10)
font = ImageFont.truetype(
STATICFILES_DIRS[0] + "/fonts/impact-opt.ttf", font_size)
top_text_size = font.getsize(top_text)
bottom_text_size = font.getsize(bottom_text)
while top_text_size[0] > image_size[0] - 20 or bottom_text_size[
0] > image_size[0] - 20:
font_size = font_size - 1
font = ImageFont.truetype(
STATICFILES_DIRS[0] + "/fonts/Impact.ttf", font_size)
top_text_size = font.getsize(top_text)
bottom_text_size = font.getsize(bottom_text)
# find top centered position for top text
top_text_x = (image_size[0] / 2) - (top_text_size[0] / 2)
top_text_y = 0
top_text_position = (top_text_x, top_text_y)
# find bottom centered position for bottom text
bottom_text_x = (image_size[0] / 2) - (bottom_text_size[0] / 2)
bottom_text_y = image_size[1] - bottom_text_size[1]
bottom_text_position = (bottom_text_x, bottom_text_y)
draw = ImageDraw.Draw(img)
# draw outlines
# there may be a better way
# outline_range = int(font_size / 10)
outline_range = 0
for x in range(-outline_range, outline_range + 1):
for y in range(-outline_range, outline_range + 1):
draw.text((top_text_position[0] + x, top_text_position[1] + y),
top_text, (0, 0, 0),
font=font)
draw.text(
(bottom_text_position[0] + x, bottom_text_position[1] + y),
bottom_text, (0, 0, 0),
font=font)
draw.text(top_text_position, top_text, (0, 0, 0), font=font)
draw.text(bottom_text_position, bottom_text, (0, 0, 0), font=font)
output_path = str(uuid.uuid4().hex) + ".png"
img.save(output_path)
obj = Upload(provider=OBJECT_STORAGE_PROVIDER,
credentials=OBJECT_STORAGE_CREDENTIALS,
file=output_path)
cloud_url = obj.upload_file()
os.remove(os.getcwd() + '/' + output_path)
return cloud_url
def meme(self, image_path):
# base_dir = BASE_DIR
# base_dir += '/' if not base_dir == '/' else ''
image_path = image_path
# thug life meme mask image path
mask_path = STATICFILES_DIRS[0] + "/images/mask.png"
# haarcascade path
casc_path = STATICFILES_DIRS[
0] + "/xml/haarcascade_frontalface_default.xml"
# cascade classifier object
face_cascade = cv2.CascadeClassifier(casc_path)
# read input image
image = cv2.imread(image_path)
print(os.listdir())
print(image, image_path)
# convert image to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# detect faces in grayscale image
faces = face_cascade.detectMultiScale(gray, 1.15)
# open input image as PIL image
background = Image.open(image_path)
# paste mask on each detected face in input image
for (x, y, w, h) in faces:
# just to show detected faces
cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 0), 2)
# imshow('face detected', image)
# waitKey(50)
# open mask as PIL image
mask = Image.open(mask_path)
# resize mask according to detected face
mask = mask.resize((w, h), Image.ANTIALIAS)
# define o
# ffset for mask
offset = (x, y)
# paste mask on background
background.paste(mask, offset, mask=mask)
# paste final thug life meme
file_name = os.path.basename(image_path)
output_path = "thug_" + str(file_name.split(".")[0]) + ".png"
background.save(output_path)
obj = Upload(provider=OBJECT_STORAGE_PROVIDER,
credentials=OBJECT_STORAGE_CREDENTIALS,
file=output_path)
cloud_url = obj.upload_file()
os.remove(os.getcwd() + '/' + output_path)
return cloud_url
