def run():
for r,d,fs in os.walk(os.path.join(att_dir,'tmp')):
null = [ os.remove(os.path.join(r,f)) for f in fs]
attachments.check_att(att_dir)
pdfs = dict([(os.path.join(att_dir,'tmp/tmp_{0:04d}.pdf'.format(idx)), \
os.path.join(att_dir,f))
for idx, f in enumerate(os.listdir(att_dir)) if '.pdf' in f.lower()])
for k,v in pdfs.iteritems(): os.rename(v,k)
#Convert PDFs
res = 300
cvsub = ['''convert -density {2} {0} {1}; rm {0}'''.\
format(p , p.replace('.pdf','.png'), res)
for p in pdfs.keys()]
for c in cvsub:
print 'calling for ' + c
subprocess.call(c,shell = True)
#Find all files produced by convert
inp_files=[ os.path.join(att_dir,'tmp',e) for e in
it.chain(\
*[filter( lambda x: os.path.splitext(os.path.basename(key))[0]\
in x and True or False,
os.listdir(os.path.join(att_dir,'tmp')))
for key in pdfs.keys()])]
bluechannels = []
x_inches = .25
y_inches = .15
skip = 5
#open them and get the blue channels
for i in inp_files:
full = mpimg.imread(i)
if isflipped(full):
full = transpose(full,(1,0,2))
blue= squeeze(full[:,:,2])
others = np.sum(full[:,:,0:2],2)
blue = blue - others
blue[less(blue,0)] = 0.
blue[greater(blue,0)] = 1.
xrad = floor(res/skip*x_inches)
yrad = floor(res/skip*y_inches)
bluesmall = blue[::skip,::skip]
bluesmall = ss.order_filter( bluesmall, ones((xrad,1)), xrad-1)
bluesmall = ss.order_filter( bluesmall, ones((1,yrad)), yrad-1)
#FLIP THE CLUSTERS JUST TO BE CONFUSING
cls = cluster_img(bluesmall)
cls = [cl.T * 5 for cl in cls]
root = os.path.join(att_dir,'pages')
if not os.path.isdir(root): os.mkdir(root)
num_max = max(array([0] + list(it.chain(*[re.findall(re.compile('[\d]+'),f) for f in os.listdir(root)])),int))
this_folder = os.path.join(root,'page_{0:05d}'.format(num_max+1))
os.mkdir(this_folder)
Image.fromarray(transpose(array(blue*255,dtype=np.uint8),(1,0))).save(open(os.path.join(this_folder,'blue.png'),'w'))
Image.fromarray(transpose(array(full*255,dtype=np.uint8),(1,0,2))).save(open(os.path.join(this_folder,'full.png'),'w'))
outline_folder = os.path.join(this_folder,'highlights')
for idx,c in enumerate(cls):
bounds =array([ np.min(c[0]),np.min(c[1]),np.max(c[0]),np.max(c[1])])
b0 = array(bounds)
bounds =bounds + 100 *array( [-1,-1,1,1] )
clip_bounds(bounds, shape(blue.T))
subimg = full[bounds[0]:bounds[2], bounds[1]:bounds[3]]
coords = { 'full_bounds':list(bounds),
'cluster_bounds':list(b0)}
Image.fromarray(transpose(array(subimg*255,dtype=np.uint8),(1,0,2))).save(open(os.path.join(this_folder,'hl_{0:02d}.png').format(idx),'w'))
fopen = open('hl_{0:02d}.txt'.format(idx), 'w')
fopen.write(simplejson.dumps(coords))
fopen.close()
def get_all(): attachments.check_att(att_dir )
def get_all():
attachments.check_att(att_dir)