def enhance(pixbuf,
brightness=1.0,
contrast=1.0,
saturation=1.0,
sharpness=1.0,
autocontrast=False):
"""Return a modified pixbuf from <pixbuf> where the enhancement operations
corresponding to each argument has been performed. A value of 1.0 means
no change. If <autocontrast> is True it overrides the <contrast> value,
but only if the image mode is supported by ImageOps.autocontrast (i.e.
it is L or RGB.)
"""
im = pixbuf_to_pil(pixbuf)
if brightness != 1.0:
im = ImageEnhance.Brightness(im).enhance(brightness)
if autocontrast and im.mode in ('L', 'RGB'):
im = ImageOps.autocontrast(im, cutoff=0.1)
elif contrast != 1.0:
im = ImageEnhance.Contrast(im).enhance(contrast)
if saturation != 1.0:
im = ImageEnhance.Color(im).enhance(saturation)
if sharpness != 1.0:
im = ImageEnhance.Sharpness(im).enhance(sharpness)
return pil_to_pixbuf(im)
def composeForTwitter(self,images):
print("composing for twitter")
strip = Image.new('RGB', (self.twitterLayout["width"], self.twitterLayout["photoDim"]), (0,0,0))
count=0
dim=self.twitterLayout["photoDim"]
#for inFile in glob.glob(os.path.join(imagedir, '*.JPG')):
for img in images:
if count>1: break
#print("\t"+str(inFile))
#img=Image.open(inFile)
posX=5
if count>0:posX=855
posY=dim/2
bbox=img.getbbox()
img=img.crop(((bbox[2]/2)-(bbox[3]/2),0,(bbox[2]/2)+(bbox[3]/2),bbox[3]))
img=img.resize((dim-10,dim-10))
#img = ImageOps.autocontrast(img, cutoff=2)
if self.grey:
img=ImageOps.grayscale(img)
enh=ImageEnhance.Brightness(img)
img=enh.enhance(0.8)
enh=ImageEnhance.Contrast(img)
img=enh.enhance(1.3)
strip.paste(img,(posX,5))
count=count+1
overlay=self.twitterLayout["overlay"]
strip.paste(overlay,None,overlay)
#path=os.path.join(imagedir, 'twitterStrip.PNG')
#path=self.saveImageToOutgoing(strip,"twitter")
#dateString=datetime.datetime.now().strftime('%Y-%m-%d_%H-%M')
#path=os.path.join(self.outgoingPath,dateString+'_twitter.PNG')
#strip.save(path, 'PNG')
print("\n")
return [strip,"twitter"]
#coding=utf-8
import Image, ImageEnhance
pic = Image.open("../images/test2.jpg")
#亮度增强
brightness = ImageEnhance.Brightness(pic)
bright_pic = brightness.enhance(2.0)
bright_pic.show()
bright_pic.save("../images/test6.jpg")
#图像尖锐化
sharpness = ImageEnhance.Sharpness(pic)
sharp_pic = sharpness.enhance(5.0)
sharp_pic.show()
sharp_pic.save("../images/test7.jpg")
#对比度增强
contrast = ImageEnhance.Contrast(pic)
contrast_pic = contrast.enhance(3.0)
contrast_pic.show()
contrast_pic.save("../images/test8.jpg")
def update(self,frame,events):
if self.running:
for key,data in events.iteritems():
if key not in ('dt'):
try:
self.data[key] += data
if (key == 'pupil_positions'):
try:
pupilDict = data[0]
self.pupil_diameter.append(pupilDict.get('diameter'))
except:
print('error');
elif (key == 'gaze_positions'):
try:
gazeDict = data[0]
self.gaze_point_x.append(gazeDict.get('norm_pos')[0])
self.gaze_point_y.append(gazeDict.get('norm_pos')[1])
self.gaze_point_z.append(gazeDict.get('gaze_point_3d')[2])
except:
print('error')
#image process (OCR) find the condion that show use OCR
except KeyError:
self.data[key] = []
self.data[key] += data
print str(self.cnum)
self.cnum = self.cnum + 1
if len(self.gaze_point_x) > 0 and self.cnum == 30:
print('Enter TO the block')
height = (1 - self.gaze_point_y[-1]) * 720
height = int(height)
image = frame.img
if (height < 100):
image = frame.img[0:height+200, 300:1000]
elif (height > 520):
image = frame.img[height-100:720, 300:1000]
else:
image = frame.img[height-100:height+200, 300:1000]
cv2.imwrite('/home/eyetracking/pupil/'+"frame%d.jpg" %self.cnum,image)
image=Image.open('/home/eyetracking/pupil/'+"frame%d.jpg" %self.cnum)
enhancer = ImageEnhance.Contrast(image)
image = enhancer.enhance(4)
totemp = sys.stdout
sys.stdout = codecs.open('/home/eyetracking/pupil/ocr.txt', encoding='utf-8', mode='w+') #save the OCR
print image_to_string(image)
sys.stdout.close()
sys.stdout = totemp
try:
i=300
for line in open('/home/eyetracking/pupil/ocr.txt'):
i=i+20
cv2.putText(dst, line,(0,i), cv2.FONT_HERSHEY_COMPLEX,0.6,(0,0,255))
cv2.imshow("window",dst)
cv2.waitKey(33)
except Exception as error:
print(error)
self.timestamps.append(frame.timestamp)
self.writer.write_video_frame(frame)
self.frame_count += 1
# # cv2.putText(frame.img, "Frame %s"%self.frame_count,(200,200), cv2.FONT_HERSHEY_SIMPLEX,1,(255,100,100))
self.button.status_text = self.get_rec_time_str()
#fbase="/media/1A8F-0227/Landsat/LT50150282011282EDC00/LT50150282011282EDC00"
#fbase="/cygdrive/d/Landsat/LT50190272011278EDC00/LT50190272011278EDC00"
#fbase="/media/Acer/cygwin/home/Petey/data/landsat/LE70160282011169EDC00"
#outfile="image2.pgm"
fbase = sys.argv[1]
outfile = sys.argv[2]
factor = 1
fblue = fbase + "_B1.TIF"
fgreen = fbase + "_B2.TIF"
fred = fbase + "_B3.TIF"
iblue = Image.open(fblue)
contr = ImageEnhance.Contrast(iblue)
iblue = contr.enhance(factor)
igreen = Image.open(fgreen)
contr = ImageEnhance.Contrast(igreen)
igreen = contr.enhance(factor)
ired = Image.open(fred)
contr = ImageEnhance.Contrast(ired)
ired = contr.enhance(factor)
irgb = Image.merge("RGB", (ired, igreen, iblue))
#color=ImageEnhance.Color(irgb)
#final=color.enhance(5)
#final.save(outfile)
irgb.save(outfile)
greenF = gl.glob(
'/home/jghao/research/data/des_realimage/des-google/testrun_stripe82_fieldF_r/*.fits'
)
redF = gl.glob(
'/home/jghao/research/data/des_realimage/des-google/testrun_stripe82_fieldF_i/*.fits'
)
blueF.sort()
greenF.sort()
redF.sort()
scale = [0.025 / 8., 0.025 / 8., 0.05 / 8.]
img = colorImg(redF[i],
greenF[i],
blueF[i],
scale=[0.025 / 8., 0.025 / 8., 0.05 / 8.])
ehImg = ImageEnhance.Contrast(img)
newImg = ehImg.enhance(1.2)
newImg.crop((5, 10, 2044, 4090))
newImg.save('descolor.png', format='PNG')
#img.save('/home/jghao/research/data/des_realimage/des-google/testrun_stripe82_color/'+blueF[i][-30:-21]+'.PNG',format="PNG")
#-----sdss image ----
redF = 'fpC-100006-i1-0062.fit.gz'
greenF = 'fpC-100006-r1-0062.fit.gz'
blueF = 'fpC-100006-g1-0062.fit.gz'
scale = [0.025, 0.025, 0.045]
img = colorImg(redF, greenF, blueF, scale=[0.025, 0.025, 0.045])
#---des image ---
def __call__(self, im):
contrast = ImageEnhance.Contrast(im)
im = contrast.enhance(np.random.normal(1, self.sigma))
return im
def visualize_image(self, importances, img_name, image_title, vmin, vmax):
"""Render the visualization for a single image
and save it to a file.
Args:
self: The Visualization instance to use.
importances: Array of importance values.
img_name: Name of imagefile to visualize.
image_title: Title that gets displayed above the visualization.
vmin: Importances with an absolute value below vmin won't get
rendered.
vmax: Importances with an absolute value above vmax won't get
rendered.
"""
img_path = os.path.join(self.datamanager.PATHS["IMG"], img_name)
if not os.path.isfile(img_path):
return
img = Image.open(os.path.join(self.datamanager.PATHS["IMG"], img_name))
# convert image to grayscale
if img.mode != "L":
grayscale = img.convert('L').convert('RGB')
else:
img = img.convert('RGB')
grayscale = img
# reduce contrast of grayscale image
contrast = ImageEnhance.Contrast(grayscale)
grayscale = contrast.enhance(0.5)
heatmap = self.heatmap_data(img_name, importances, (img.size[1], img.size[0]))
has_negative = (heatmap < 0.0).any() # is this an image with negative weights?
pos_heat = np.ma.masked_less(heatmap, vmin)
if has_negative:
pos_colormap = cm.Reds
neg_heat = np.ma.masked_greater(heatmap, -vmin)
neg_colormap = self.reverse_color_map(cm.Blues)
else:
pos_colormap = cm.Reds
# create visualization
gridspec = GridSpec(2, 2, height_ratios=[1,3])
# original thumbnail
img_subplot = pl.subplot(gridspec[0, 0])
img_subplot.axis('off')
img_subplot.imshow(img)
# heatmap thumbnail
heat_subplot = pl.subplot(gridspec[0, 1])
heat_subplot.axis('off')
axes_heat = heat_subplot.imshow(pos_heat, cmap=pos_colormap, alpha=1.0, vmin=vmin, vmax=vmax)
ticks = np.linspace(vmin, vmax, 10)
if has_negative:
axes_neg = heat_subplot.imshow(neg_heat, cmap=neg_colormap, alpha=1.0, vmin=-vmax, vmax=-vmin)
# combined subplot of grayscale image and heatmap
combined_subplot = pl.subplot(gridspec[1, :])
combined_subplot.axis('off')
combined_subplot.imshow(grayscale)
combined_subplot.imshow(pos_heat, cmap=pos_colormap, alpha=0.55)
divider = make_axes_locatable(combined_subplot)
cax = divider.append_axes("right", size=0.25, pad=0.33)
pl.colorbar(axes_heat, cax=cax, ticks=ticks)
if has_negative:
combined_subplot.imshow(neg_heat, cmap=neg_colormap, alpha=0.55)
cax = divider.append_axes("left", size=0.25, pad=0.33)
neg_cb = pl.colorbar(axes_neg, cax=cax, ticks=-ticks)
neg_cb.ax.yaxis.set_ticks_position("left")
# save figure
fig_path = os.path.join(self.datamanager.PATHS["RESULTS"], "_".join(image_title.lower().split()[0:2]))
if not os.path.isdir(fig_path):
os.makedirs(fig_path)
pl.suptitle(image_title)
pl.savefig(os.path.join(fig_path, img_name + ".png"), format="png")
pl.clf()
def enhance(eimage):
enh = ImageEnhance.Contrast(eimage)
enh.enhance(1.3).show("30% more contrast")
from pytesser import *
import ImageEnhance
image = Image.open('C:/Users/Administrator/Desktop/snap.png')
enhancer = ImageEnhance.Contrast(image)
image_enhancer = enhancer.enhance(4)
str = image_to_string(image_enhancer)
print(str)
elif y + linewidth/2 >= im.shape[1]:
im[:, y:im.shape[1]] = color
else:
im[:, (y-linewidth/2):(y+linewidth/2)] = color
return im
if __name__ == '__main__':
im1 = cv2.cvtColor(cv2.imread(sys.argv[1]), cv2.COLOR_BGR2RGB)
SIZE_X = 740
SIZE_Y = 880
# matrix = perspectiveTransform([(628, 163), (1666, 147), (2716, 128), \
# (632, 1237), (1675, 1266), (2734, 1219), \
# (632, 2346), (1683, 2337), (2745, 2341)], \
# [(0, 0), (SIZE/2, 0), (SIZE, 0), \
# (0, SIZE/2), (SIZE/2, SIZE/2), (SIZE, SIZE/2), \
# (0, SIZE), (SIZE/2, SIZE), (SIZE, SIZE)]) # (-3, -6)
matrix = perspectiveTransform([(51, 18), (734, 42), \
(9, 878), (745, 871)], \
[(0, 0), (SIZE_X, 0), \
(0, SIZE_Y), (SIZE_X, SIZE_Y)])
#im2 = cv2.warpPerspective(im1, linalg.inv(matrix), (800, 800))
im2 = cv2.warpPerspective(im1, matrix, (SIZE_X, SIZE_Y))
#im2 = drawLines(im2, linewidth=6, interval=SIZE/10, color=np.array([127,255,127]))
im_pil = Image.fromarray(im2)
im_pil = ImageEnhance.Contrast(im_pil).enhance(1.5)
im_pil = ImageEnhance.Brightness(im_pil).enhance(1.1)
# Rotate
# im_pil.show()
im_pil.save('armyCard.png')
def application(environ,start_response):
request = environ['QUERY_STRING']
left, right, top, bottom, background, print_type = request.split(';', 6)
if print_type == 'big' : zoom= 14 # 35 tiles
else : zoom= 15 # 63 tiles
left=float(left)
right=float(right)
top=float(top)
bottom=float(bottom)
# we print only pistes, here
db='pistes-mapnik'
conn = psycopg2.connect("dbname="+db+" user=mapnik")
cur = conn.cursor()
sql=" SELECT count(*) FROM planet_osm_line WHERE st_intersects(planet_osm_line.way,st_transform( ST_MakeEnvelope("+str(left)+","+ str(bottom)+","+ str(right)+","+ str(top)+", 4326),900913));"
cur.execute(" \
SELECT count(*) \
FROM planet_osm_line WHERE \
st_intersects(\
planet_osm_line.way,\
st_transform( ST_MakeEnvelope(%s,%s,%s,%s, 4326),900913)) and \"piste:type\" = 'nordic'; "\
, (left, bottom, right, top))
result=cur.fetchall()
cur.close()
conn.close()
if result[0][0]==0L:
response_body=str(result[0][0])+' pistes found'
status = '200 OK'
response_headers = [('Content-Type', 'text/plain'),('Content-Length', str(len(response_body)))]
start_response(status, response_headers)
return [response_body]
#~ if background == 'osm':
#~ url='http://tile.openstreetmap.org/'
#~ ext='png'
#~ else :
#~ url= 'http://otile1.mqcdn.com/tiles/1.0.0/osm/'
#~ ext='jpg'
url='http://tile.openstreetmap.org/'
ext='png'
bg = getImage(url, left, right, top, bottom, zoom,'osm',ext)
enhancer = ImageEnhance.Brightness(bg)
bg = enhancer.enhance(1.2)
enhancer = ImageEnhance.Contrast(bg)
bg = enhancer.enhance(0.8)
contours = getImage('http://tiles.pistes-nordiques.org/tiles-contours/', left, right, top, bottom, zoom,'osm',ext)
r, g, b, a = contours.split()
mask = Image.merge("L", (a,))
v=numpy.asarray(mask)*0.5
v=numpy.uint8(v)
value=Image.fromarray(v)
bg.paste(contours.convert('RGB'),None,value)
hs = getImage('http://tiles2.pistes-nordiques.org/hillshading/', left, right, top, bottom, zoom,'tms',ext)
r, g, b, a = hs.split()
mask = Image.merge("L", (a,))
v=numpy.asarray(mask)*0.5
v=numpy.uint8(v)
value=Image.fromarray(v)
bg.paste(hs.convert('RGB'),None,value)
pistes = getImage('http://tiles.pistes-nordiques.org/tiles-pistes2/', left, right, top, bottom, zoom,'osm',ext)
r, g, b, a = pistes.split()
mask = Image.merge("L", (a,))
bg.paste(pistes.convert('RGB'),None,mask)
bg=bg.convert('RGB')
cartouche= Image.open(os.path.dirname(__file__)+'/cartouche.png')
cartouche.load()
r, g, b, a = cartouche.split()
mask = Image.merge("L", (a,))
v=numpy.asarray(mask)
v=numpy.uint8(v)
value=Image.fromarray(v)
bg.paste(cartouche.convert('RGB'),(0,0),value)
s = bg.size
printout = Image.new('RGB', (s[0]+40, s[1]+40), 'white')
printout.paste(bg,(20,20))
randFilename = random.randrange(0, 100001, 2)
PIL_images_dir = '/var/www/tmp/'
printout_filename = 'printout'+str(randFilename)+'.pdf'
outname=PIL_images_dir + printout_filename
#bg.save(outname,'png', ppi=pistes.info['ppi'])
printout.save(outname,'PDF', resolution=200.0, quality=90)
response_body='/tmp/'+printout_filename
status = '200 OK'
response_headers = [('Content-Type', 'text/plain'),('Content-Length', str(len(response_body)))]
start_response(status, response_headers)
return [response_body]
def contrast(image, factor):
enh = ImageEnhance.Contrast(image)
return enh.enhance(factor)
def processImageFile(im_file, out_file):
im = Image.open(im_file)
enh = ImageEnhance.Contrast(im)
eim = enh.enhance(1.25) #.show("30% more contrast");
eim.save(out_file)
def contrast_img(img_name, new_img='new_img.jpg'):
img = Image.open(img_name)
contrast = ImageEnhance.Contrast(img)
contrast_img = contrast.enhance(2.0)
contrast_img.save(new_img)
def cont(imagefile, factor=10):
im=Image.open(imagefile)
enhancer = ImageEnhance.Contrast(im)
enhancer.enhance(factor).show("Contrast %f" % factor)
return
# Calculate the shaded relief
shaded = np.sin(altitude * deg2rad) * np.sin(slope * deg2rad) \
+ np.cos(altitude * deg2rad) * np.cos(slope * deg2rad) \
* np.cos((azimuth - 90.0) * deg2rad - aspect)
shaded = shaded * 255
# Convert the numpy array back to an image
relief = Image.fromarray(shaded).convert("L")
# Smooth the image several times so it's not pixelated
for i in range(10):
relief = relief.filter(ImageFilter.SMOOTH_MORE)
log.info("Creating map image")
# Increase the hillshade contrast to make
# it stand out more
e = ImageEnhance.Contrast(relief)
relief = e.enhance(2)
# Crop the image to match the SRTM image. We lose
# 2 pixels during the hillshade process
base = Image.open(osm_img + ".jpg").crop((0, 0, w - 2, h - 2))
# Enhance base map contrast before blending
e = ImageEnhance.Contrast(base)
base = e.enhance(1)
# Blend the the map and hillshade at 90% opacity
topo = Image.blend(relief.convert("RGB"), base, .9)
## Draw the GPX tracks
# Convert the coordinates to pixels
points = []
for x, y in zip(lons, lats):
enhancer = ImageEnhance.Color(im)
imGray = enhancer.enhance(0.).convert("L").resize(
(options.res_size, options.res_size),
Image.ANTIALIAS).filter(ImageFilter.MedianFilter(options.kernel_size))
print "done."
print "applying threshold... ",
hist = scipy.ndimage.filters.gaussian_filter1d(np.array(
imGray.histogram()[100:200]),
sigma=10)
val = np.argmin(hist) + options.threshold
contrast = ImageEnhance.Contrast(imGray)
imGray = contrast.enhance(2.5)
sharper = ImageEnhance.Sharpness(imGray)
imGray = sharper.enhance(0.5)
imGray.save("temp.bmp")
im.convert("L").resize((options.res_size, options.res_size),
Image.ANTIALIAS).save("temp2.bmp")
Img = plt.imread("temp.bmp")[::-1]
#Img -= val
#Img = Img.clip(min=val)
Img2 = plt.imread("temp2.bmp")[::-1]
plt.imshow(Img, cmap='gray')
plt.draw()
from PIL import Image
import ImageEnhance
im = Image.open("captcha.jpg")
nx, ny = im.size
im2 = im.resize((int(nx * 5), int(ny * 5)), Image.BICUBIC)
im2.save("final_pic.png")
enh = ImageEnhance.Contrast(im)
enh.enhance(1.3).show("30% more contrast")
import ImageEnhance
import urllib2
pcurl = 'http://www.pythonchallenge.com/pc/return/'
img_url = 'http://www.pythonchallenge.com/pc/return/cave.jpg'
request = urllib2.Request(img_url)
base64string = base64.encodestring('{0}:{1}'.format('huge',
'file')).replace('\n', '')
request.add_header("Authorization", "Basic {0}".format(base64string))
img = urllib2.urlopen(request)
with open('cave.jpg', 'wb') as img_file:
img_file.write(img.read())
image = Image.open('cave.jpg')
for x in xrange(image.size[0]):
for y in xrange(image.size[1]):
if (x + y) % 2 != 0:
image.putpixel((x, y), (0, 0, 0))
bright = ImageEnhance.Brightness(image)
image = bright.enhance(2.5)
contrast = ImageEnhance.Contrast(image)
image = contrast.enhance(3.0)
image.show()
image.save('cave.png')
# the image shows the word 'evil'
print "The next url is {0}{1}.html".format(pcurl, 'evil')
toint=False)
kss_red = kss
#kss_hsv = rgb_to_hsv(kss)
#kss_hsv[:,:,0] = 0/360.
#kss_red = hsv_to_rgb(kss_hsv)
print "Downsample: ", downsample, " size: ", size, " style: ", txt
print "Memory Check (ps): ", get_mem() / 1024.**3
redblueorange = kss_red + h2s_orange + fes_blue
redblueorange[redblueorange > 1] = 1
im = PIL.Image.fromarray(
(redblueorange * 255).astype('uint8')[::-1, :])
im.save(prefix + 'Trapezium_GEMS_mosaic_redblueorange_%s%s.png' %
(txt, size))
im = ImageEnhance.Contrast(im).enhance(1.5)
im.save(prefix +
'Trapezium_GEMS_mosaic_redblueorange_%s%s_contrast.png' %
(txt, size))
im = ImageEnhance.Brightness(im).enhance(1.5)
im.save(
prefix +
'Trapezium_GEMS_mosaic_redblueorange_%s%s_contrast_bright.png' %
(txt, size))
print "Downsample: ", downsample, " size: ", size, " style: ", txt
print "Memory Check (ps): ", get_mem() / 1024.**3
output = prefix + 'Trapezium_GEMS_mosaic_redblueorange_%s%s.png' % (
txt, size)
avm.embed(output, output)
# -*- coding:utf-8 -*-
import Image
import ImageEnhance
import ImageFilter
import sys
image_name = "./testpic/1.jpg"
# 去除干扰点
im = Image.open(image_name)
im = im.filter(ImageFilter.MedianFilter())
enchancer = ImageEnhance.Contrast(im)
im = im.convert('1')
im.show()
s = 12 #启始 切割点 x
t = 2 #启始 切割点 y
w = 10 #切割 宽 +y
h = 15 #切割 长 +x
im_new = []
for i in range(4): #验证码切割
im1 = im.crop((s + w * i + i * 2, t, s + w * (i + 1) + i * 2, h))
im_new.append(im1)
im_new[0].show() #测试查看
xsize, ysize = im_new[0].size
def _contrast_fired(self):
print "Contrast enhancing the image!"
im = Image.open("image.jpg")
im_contrast_enhanced = ImageEnhance.Contrast(im).enhance(2)
im_contrast_enhanced.save("image.jpg", "JPEG")
self.display_image()
print s
if do_view == True:
ratio = float(MAXWIDTH) / s[0]
print ratio
wi = s[0] * ratio
print wi
hi = s[1] * ratio
print int(hi)
im.thumbnail((int(wi), int(hi)), Image.ANTIALIAS)
brightness = 1.15
enhancer = ImageEnhance.Brightness(im)
bright = enhancer.enhance(brightness)
contrast = 1.7
enhancer = ImageEnhance.Contrast(bright)
im = enhancer.enhance(contrast)
#im = ImageOps.autocontrast(im)
im.save(outfile, "JPEG")
except IOError:
print "cannot create thumbnail for '%s'" % zipdest
#fm.unzipFile(ziploc, location_to+"/"+os.path.splitext(zip)[0])
print "done!"
print fm.list_dir(location)
sys.exit(0)
for infile in sys.argv[1:]:
outfile = os.path.splitext(infile)[0] + ".thumbnail"
def enhance(image, factor):
image = ImageEnhance.Color(image).enhance(factor / 5)
image = ImageEnhance.Contrast(image).enhance(factor)
return image
def ocr_word(mouse_x, mouse_y):
# Return None if occur unsupported language.
src_lang = setting_config.get_translate_config("src_lang")
if not LANGUAGE_OCR_DICT.has_key(src_lang):
show_message(_("Sorry, select-and-translate does not support %s yet") % _(src_lang), _("Cancel"), _("Ok, I understand"), lambda : ocr_log(src_lang))
return None
# Return None if found any ocr package need install before continue.
ocr_pkg_name = LANGUAGE_OCR_DICT[src_lang]
pkg_names = get_install_packages([ocr_pkg_name])
if len(pkg_names):
show_message(_("An OCR package is required to enable word recognition"), _("Cancel"), _("Install"), lambda : install_packages(pkg_names))
return None
# Return None if mouse at trayicon area.
if constant.TRAYAREA_TOP < mouse_y < constant.TRAYAREA_BOTTOM:
return None
# Ocr word under cursor.
lang = ocr_pkg_name.split("tesseract-ocr-")[1].replace("-", "_")
x = max(mouse_x - screenshot_width / 2, 0)
y = max(mouse_y - screenshot_height / 2, 0)
width = min(mouse_x + screenshot_width / 2, screen_width) - x
height = min(mouse_y + screenshot_height / 2, screen_height) - y
scale = 2
tool = pyocr.get_available_tools()[0]
output_format = xcb.xproto.ImageFormat.ZPixmap
plane_mask = 2**32 - 1
reply = conn.core.GetImage(
output_format,
root,
x,
y,
width,
height,
plane_mask).reply()
# Get screenshot image data.
image_data = reply.data.buf()
image = Image.frombuffer("RGBX", (width, height), image_data, "raw", "BGRX").convert("RGB")
# First make image grey and scale bigger.
image = image.convert("L").resize((width * scale, height * scale))
# image.save("old.png") # debug
# Second enhance image with contrast and sharpness.
image = ImageEnhance.Contrast(image).enhance(1.5)
# I found uncomment below code have better result. ;)
# image = ImageEnhance.Sharpness(image).enhance(2.0)
# image.save("new.png") # debug
word_boxes = tool.image_to_string(
image,
lang=lang,
builder=pyocr.builders.WordBoxBuilder())
cursor_x = (mouse_x - x) * scale
cursor_y = (mouse_y - y) * scale
for word_box in word_boxes[::-1]:
((left_x, left_y), (right_x, right_y)) = word_box.position
if (left_x <= cursor_x <= right_x and left_y <= cursor_y <= right_y):
word = filter_punctuation(word_box.content)
# Return None if ocr word is space string.
if word.isspace():
return None
else:
return word
return None
logexp=logii)
rgb_small[:, :, 3] = 255
rgb_small_pil = rgb_small[::
-1, :, :] # reverse y axis because PIL is backwards
#rgb_small_pil[np.max(rgb_small_pil,axis=2)>=255,:] = 255
#rgb_small_pil[:,:,3] = np.uint8(256)-rgb_small_pil[:,:,3]
im = PIL.Image.fromarray(rgb_small_pil)
print "Saving GEMS mosaic ", time.time() - t0
im.save(prefix + 'OrionBNKL_GEMS_mosaic_logexp%ii_small.png' % logii)
print "Fin small image %i. t=%0.1f s" % (logii, time.time() - t0)
kbackground = PIL.Image.new("RGB", im.size, (0, 0, 0))
kbackground.paste(im, mask=im.split()[3])
print "Saving GEMS mosaic with black bg ", time.time() - t0
#kbackground.save(prefix+'OrionBNKL_GEMS_mosaic_logexp%ii_blackbg_small.png' % (logii))
kbackground_contrast = ImageEnhance.Contrast(kbackground).enhance(1.5)
kbackground_contrast.save(
prefix + 'OrionBNKL_GEMS_mosaic_logexp%ii_blackbg_contrast_small.png' %
(logii))
kbackground_bright = ImageEnhance.Brightness(kbackground_contrast).enhance(
1.5)
kbackground_bright.save(
prefix +
'OrionBNKL_GEMS_mosaic_logexp%ii_blackbg_contrast_bright_small.png' %
(logii))
for logii in xrange(0, 2):
print "Making large image %i. t=%0.1f s" % (logii, time.time() - t0)
rgb_large = np.ones([myshape[0], myshape[1], 4], dtype='uint8')
rgb_large[:, :, 1] = logscale(ks, xmin=ksmin, xmax=ksmax, logexp=logii)
rgb_large[:, :, 0] = logscale(h2, xmin=h2min, xmax=h2max, logexp=logii)
def brightness(self, windowCenter):
enhancer = ImageEnhance.Contrast(self.img)
self.img = enhancer.enhance(float(windowCenter))
def other(im):
#out=im.rotate(45)
#out=im.filter(ImageFilter.DETAIL)
out = ImageEnhance.Contrast(im)
out.enhance(1.5).show('50% more contrast')
#coding:utf-8
import Image
import pytesseract
import ImageEnhance
img = Image.open('11.png')
img = img.convert('RGBA')
img = img.convert('L')
img.save('end_9.png')
sharpness = ImageEnhance.Sharpness(img) # Sharpened
img = sharpness.enhance(7.0)
img.save('end_0.png')
#img = ImageEnhance.Color(img) # Black and white
#img = img.enhance(0)
img.save('end_1.png')
#img = ImageEnhance.Brightness(img) # Increase brightness
#img = img.enhance(3)
img.save('end_2.png')
img = ImageEnhance.Contrast(img) # High contrast
img = img.enhance(8)
img.save('end_3.png')
#img = ImageEnhance.Color(img)
#img = img.convert('L')
