Add Chris's plugin utility converter and wxpython plugin.

scikits/image/io/_plugin_util.py

@@ -0,0 +1,69 @@
+import numpy as np
+
+# utilities to make life easier for plugin writers.
+
+
+def prepare_for_display(npy_img):
+    '''Convert a 2D or 3D numpy array of any dtype into a
+    3D numpy array with dtype uint8. This array will
+    be suitable for use in passing to gui toolkits for
+    image display purposes.
+
+    Parameters
+    ----------
+    npy_img : ndarray, 2D or 3D
+        The image to convert for display
+
+    Returns
+    -------
+    out : ndarray, 3D dtype=np.uint8
+        The converted image. This is guaranteed to be a contiguous array.
+
+    Notes
+    -----
+    If the input image is floating point, it is assumed that the data
+    is in the range of 0.0 - 1.0. No check is made to assert this
+    condition. The image is then scaled to be in the range 0 - 255
+    and then cast to np.uint8
+
+    For all other dtypes, the array is simply cast to np.uint8
+
+    If a 2D array is passed, the single channel is replicated
+    to the 2nd and 3rd channels.
+
+    If the array contains an alpha channel, this channel is
+    ignored.
+
+    '''
+    if len(npy_img.shape) < 2:
+        raise ValueError('Image must be 2D or 3D array')
+
+    height = npy_img.shape[0]
+    width = npy_img.shape[1]
+
+    out = np.empty((height, width, 3), dtype=np.uint8)
+
+    if len(npy_img.shape) == 2 or \
+       (len(npy_img.shape) == 3 and npy_img.shape[2] == 1):
+        if npy_img.dtype in [np.float32, np.float64]:
+            out[:,:,0] = npy_img*255
+            out[:,:,1] = out[:,:,0]
+            out[:,:,2] = out[:,:,0]
+        else:
+            out[:,:,0] = npy_img
+            out[:,:,1] = npy_img
+            out[:,:,2] = npy_img
+
+    elif len(npy_img.shape) == 3:
+        if npy_img.shape[2] == 3 or npy_img.shape[2] == 4:
+            if npy_img.dtype in [np.float32, np.float64]:
+                out[:,:,:3] = (npy_img[:,:,:3])*255
+            else:
+                out[:,:,:3] = npy_img[:,:,:3]
+        else:
+            raise ValueError('Image must have 1, 3, or 4 channels')
+
+    else:
+        raise ValueError('Image must have 2 or 3 dimensions')
+
+    return out

scikits/image/io/wxpython_plugin.py

@@ -0,0 +1,53 @@
+import numpy as np
+import plugin
+from _plugin_util import prepare_for_display
+
+try:
+    import wx
+except ImportError:
+    pass
+else:
+
+    # idea shamelessly taken from here:
+    # http://wiki.wxpython.org/WorkingWithImages
+
+    class ImagePanel(wx.Panel):
+        def __init__(self, parent, id):
+            wx.Panel.__init__(self, parent, id)
+            self.bitmap = None
+            self.Bind(wx.EVT_PAINT, self.OnPaint)
+
+        def display(self, npy_img):
+            self.bitmap = self.get_bitmap(npy_img)
+            self.Refresh(True)
+
+        def OnPaint(self, evt):
+            dc = wx.PaintDC(self)
+            if self.bitmap:
+                dc.DrawBitmap(self.bitmap, 0, 0)
+
+        def get_bitmap(self, npy_img):
+            width = npy_img.shape[1]
+            height = npy_img.shape[0]
+            wx_img = wx.EmptyImage(width, height)
+            wx_img.SetData(npy_img.data)
+            return wx.BitmapFromImage(wx_img)
+
+
+    class ImageFrame(wx.Frame):
+        def __init__(self, img):
+            self.img = img
+            width = img.shape[1]
+            height = img.shape[0]
+            wx.Frame.__init__(self, None, -1, 'wx', wx.DefaultPosition,
+                                wx.Size(width, height))
+
+            self.iPanel = ImagePanel(self, -1)
+            self.iPanel.display(self.img)
+
+    def wx_imshow(img):
+        f = ImageFrame(prepare_for_display(img))
+        f.CenterOnScreen()
+        f.Show()
+
+    plugin.register('wx', show=wx_imshow)