1 files changed, 0 insertions, 151 deletions
diff --git a/jm2l/captcha.py.orig b/jm2l/captcha.py.orig
deleted file mode 100644
index 8ec778f..0000000
--- a/jm2l/captcha.py.orig
+++ /dev/null
@@ -1,151 +0,0 @@
-# Stolen from tgcaptcha/plugins
-# http://code.google.com/p/tgcaptcha/source/browse/trunk/tgcaptcha/plugins/image/vanasco_dowty/captcha.py
-
-import random
-from PIL import Image, ImageDraw, ImageFont, ImageFilter
-from io import BytesIO
-import math
-from pyramid.view import view_config
-from .words import TabMots
-from pyramid.response import Response
-
-class Captcha_Img(object):
-    def __init__( self, width, height):
-        self.width = width
-        self.height = height
-        self._layers = [
-            _PyCaptcha_SineWarp(amplitudeRange = (4, 8) , periodRange=(0.65,0.73) ),
-        ]
-        
-    def getImg(self):
-        """Get a PIL image representing this CAPTCHA test, creating it if necessary"""
-        if not self._image:
-            self._image = self.render()
-        return self._image
-
-    def render(self):
-        """Render this CAPTCHA, returning a PIL image"""
-        size = (self.width,self.height)
-        #img = Image.new("RGB", size )
-        img = self._image
-        for layer in self._layers:
-            img = layer.render( img ) or img
-        self._image = img
-        return self._image
-
-class _PyCaptcha_WarpBase(object):
-    """Abstract base class for image warping. Subclasses define a
-       function that maps points in the output image to points in the input image.
-       This warping engine runs a grid of points through this transform and uses
-       PIL's mesh transform to warp the image.
-       """
-    filtering = Image.BILINEAR
-    resolution = 40
-
-    def get_transform(self, image):
-        """Return a transformation function, subclasses should override this"""
-        return lambda x, y: (x, y)
-
-    def render(self, image):
-        r = self.resolution
-        xPoints = image.size[0] // r + 2
-        yPoints = image.size[1] // r + 2
-        f = self.get_transform(image)
-
-        # Create a list of arrays with transformed points
-        xRows = []
-        yRows = []
-        for j in xrange(yPoints):
-            xRow = []
-            yRow = []
-            for i in xrange(xPoints):
-                x, y = f(i*r, j*r)
-
-                # Clamp the edges so we don't get black undefined areas
-                x = max(0, min(image.size[0]-1, x))
-                y = max(0, min(image.size[1]-1, y))
-
-                xRow.append(x)
-                yRow.append(y)
-            xRows.append(xRow)
-            yRows.append(yRow)
-
-        # Create the mesh list, with a transformation for
-        # each square between points on the grid
-        mesh = []
-        for j in xrange(yPoints-1):
-            for i in xrange(xPoints-1):
-                mesh.append((
-                    # Destination rectangle
-                    (i*r, j*r,
-                     (i+1)*r, (j+1)*r),
-                    # Source quadrilateral
-                    (xRows[j  ][i  ], yRows[j  ][i  ],
-                     xRows[j+1][i  ], yRows[j+1][i  ],
-                     xRows[j+1][i+1], yRows[j+1][i+1],
-                     xRows[j  ][i+1], yRows[j  ][i+1]),
-                    ))
-
-        return image.transform(image.size, Image.MESH, mesh, self.filtering)
-
-class _PyCaptcha_SineWarp(_PyCaptcha_WarpBase):
-    """Warp the image using a random composition of sine waves"""
-
-    def __init__(self,
-                 amplitudeRange = (1,1),#(2, 6),
-                 periodRange    = (1,1)#(0.65, 0.73),
-                 ):
-        self.amplitude = random.uniform(*amplitudeRange)
-        self.period = random.uniform(*periodRange)
-        self.offset = (random.uniform(0, math.pi * 2 / self.period),
-                       random.uniform(0, math.pi * 2 / self.period))
-                       
-    def get_transform(self, image):
-        return (lambda x, y,
-                a = self.amplitude,
-                p = self.period,
-                o = self.offset:
-                (math.sin( (y+o[0])*p )*a + x,
-                 math.sin( (x+o[1])*p )*a + y))
-
-@view_config(route_name='captcha')
-def DoCaptcha(request):
-    ImgSize = (230,100)
-    WorkImg = Image.new( 'RGBA', ImgSize, (255, 255, 255, 0) )
-    Xmax, Ymax = WorkImg.size
-    # Write something on it
-    draw = ImageDraw.Draw(WorkImg)
-
-    # use a truetype font
-    #font = ImageFont.truetype("/var/lib/defoma/gs.d/dirs/fonts/LiberationMono-Regular.ttf", 40)
-    # use it
-    font = ImageFont.truetype("jm2l/static/fonts/LiberationMono-Regular.ttf",40)
-    # Re-position
-    # Choose a word for captcha
-    text = random.choice(TabMots)
-    Xt, Yt = font.getsize(text)
-    OrX, OrY = (ImgSize[0]-Xt)//2, (ImgSize[1]-Yt)//2
-    draw.text((OrX, OrY), text, font=font, fill="#000000")
-    # Apply a Blur
-    # WorkImg=WorkImg.filter(ImageFilter.BLUR)
-    # Apply a DETAIL
-    WorkImg=WorkImg.filter(ImageFilter.DETAIL)
-    # randomize parameters for perspective
-    ax, ay = (random.uniform(0.9,1.2) , random.uniform(0.9,1.2)) 
-    tx, ty = (random.uniform(0,0.0003),random.uniform(0,0.0003))
-    bx, by = (random.uniform(0.5,0.8),random.uniform(0,0.2))
-    # Apply perspective to Captcha
-    WorkImg= WorkImg.transform(ImgSize, Image.PERSPECTIVE, (ax, bx, -25, by, ay, -10, tx, ty))
-    # Apply SinWarp to Captcha
-    tr = Captcha_Img(Xmax, Ymax)
-    tr._image = WorkImg
-    WorkImg = tr.render()
-    # Apply a Smooth on it
-    WorkImg=WorkImg.filter(random.choice([ImageFilter.SMOOTH, ImageFilter.SMOOTH_MORE]))
-    # Save Result
-    request.session['Captcha'] = text
-    #session.save()
-    ImgHandle = BytesIO()
-    WorkImg.save(ImgHandle,'png')
-    ImgHandle.seek(0)
-    return Response(app_iter=ImgHandle, content_type = 'image/png')