def render2(data):
scale = 2.0
max_courses = 100
frequencies = { normalized(course['name']): course['watch_time'] for course in data['user_courses'] \
if course['watch_time'] > 0 }
for course in data['category_courses']:
name = normalized(course['name'])
if name not in frequencies:
frequencies[name] = 1
if len(frequencies) > max_courses: break
mask = Image.open(img_dir + 'circle.png')
width, height = mask.size
mask = np.array(
mask.resize((int(mask.size[0] / float(scale)),
int(mask.size[1] / float(scale)))))
wordcloud = WordCloud(scale=scale, background_color='white', width=int(width/float(scale)), height=int(width/float(scale)), margin=2, font_path=font_dir + 'msyhl.ttc', mask=mask) \
.generate_from_frequencies(frequencies).to_image()
l, t = 42, 594
r, b = 1458, 2328
wordcloud = wordcloud.crop((l, t, r, b))
pos = l, t
canvas = Image.open(img_dir + '2.png')
canvas.paste(wordcloud, pos)
printer(canvas, (800, 170), data['max_category'], 'msyh.ttc', 150)
printer(canvas, (920, 400), '%3d' % data['max_cnt'], 'ELEPHNT.TTF', 120)
return canvas
