Any number of channels

lucid/optvis/param/__init__.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ==============================================================================
 
-from lucid.optvis.param.images import image
+from lucid.optvis.param.images import image, grayscale_image_rgb
 from lucid.optvis.param.lowres import lowres_tensor
 from lucid.optvis.param.color import to_valid_rgb
 from lucid.optvis.param.spatial import naive, fft_image, laplacian_pyramid

lucid/optvis/param/color.py

@@ -73,3 +73,4 @@ def to_valid_rgb(t, decorrelate=False, sigmoid=True):
     return tf.nn.sigmoid(t)
   else:
     return constrain_L_inf(2*t-1)/2 + 0.5
+

lucid/optvis/param/images.py

@@ -22,15 +22,23 @@
 from lucid.optvis.param.spatial import pixel_image, fft_image
 
 
-def image(w, h=None, batch=None, sd=None, decorrelate=True, fft=True, alpha=False):
+def image(w, h=None, batch=None, sd=None, decorrelate=True, fft=True, alpha=False, channels=None):
     h = h or w
     batch = batch or 1
-    channels = 4 if alpha else 3
-    shape = [batch, w, h, channels]
+    ch = channels or (4 if alpha else 3)
+    shape = [batch, h, w, ch]
     param_f = fft_image if fft else pixel_image
     t = param_f(shape, sd=sd)
-    rgb = to_valid_rgb(t[..., :3], decorrelate=decorrelate, sigmoid=True)
-    if alpha:
-        a = tf.nn.sigmoid(t[..., 3:])
-        return tf.concat([rgb, a], -1)
-    return rgb
+    if channels:
+        output = tf.nn.sigmoid(t)
+    else:
+        output = to_valid_rgb(t[..., :3], decorrelate=decorrelate, sigmoid=True)
+        if alpha:
+            a = tf.nn.sigmoid(t[..., 3:])
+            return tf.concat([rgb, a], -1)
+    return output
+
+def grayscale_image_rgb(*args, **kwargs):
+  """Takes same arguments as image"""
+  output = image(*args, channels=1, **kwargs)
+  return tf.tile(output, (1,1,1,3))

tests/misc/io/test_reading.py

@@ -10,7 +10,7 @@
 
 path = "./tests/fixtures/string.txt"
 string = u"The quick brown fox jumps over the lazy 🐕"
-io.open(path, 'w').write(string)
+io.open(path, 'w', encoding="utf-8").write(string)
 
 
 def test_read_txt_file():

tests/optvis/test_integration.py

@@ -37,3 +37,34 @@ def test_integration(decorrelate, fft):
     start_image, end_image = rendering
 
     assert (start_image != end_image).any()
+
+def arbitrary_channels_to_rgb(*args, **kwargs):
+        """Arbitrary parametrization for testing"""
+        channels = kwargs.pop('channels', None) or 10
+        full_im = param.image(*args, channels=channels, **kwargs)
+        r = tf.reduce_mean(full_im[...,:channels//3]**2, axis=-1)
+        g = tf.reduce_mean(full_im[...,channels//3:2*channels//3]**2, axis=-1)
+        b = tf.reduce_mean(full_im[...,2*channels//3:]**2, axis=-1)
+        return tf.stack([r,g,b], axis=-1)
+
+@pytest.mark.slow
+def test_integration_any_channels():
+    inceptionv1 = InceptionV1()
+    objectives_f = [objectives.deepdream("mixed4a_pre_relu"), 
+                objectives.channel("mixed4a_pre_relu", 360), 
+                objectives.neuron("mixed3a", 177)]
+    params_f = [lambda: param.grayscale_image_rgb(128),
+                lambda: arbitrary_channels_to_rgb(128, channels=10)]
+    for objective_f in objectives_f:
+        for param_f in params_f:
+            rendering = render.render_vis(
+                inceptionv1,
+                objective_f,
+                param_f,
+                verbose=False,
+                thresholds=(0, 64),
+                use_fixed_seed=True,
+            )
+            start_image, end_image = rendering
+
+            assert (start_image != end_image).any()