Merge branch 'staging' of https://github.com/deepfakes/faceswap into …

…staging

lib/face_filter.py

@@ -164,6 +164,9 @@ def check(self, detected_face):
                 msg = ("Rejecting face as k-nearest neighbors classification is less than "
                        "0.5: {}".format(round(ratio, 2)))
                 retval = False
+            else:
+                msg = None
+                retval = True
         else:
             msg = None
             retval = True

lib/model/masks.py

@@ -127,5 +127,5 @@ def build_mask(self):
         mask = np.zeros(self.face.shape[0:2] + (1, ), dtype=np.float32)
         hull = cv2.convexHull(  # pylint: disable=no-member
             np.array(self.landmarks).reshape((-1, 2)))
-        cv2.fillConvexPoly(mask, hull, 1.0, lineType=cv2.LINE_AA)  # pylint: disable=no-member
+        cv2.fillConvexPoly(mask, hull, 255.0, lineType=cv2.LINE_AA)  # pylint: disable=no-member
         return mask

plugins/convert/_config.py

@@ -118,6 +118,55 @@ def set_defaults(self):
                  "scaling factor proposed in the paper. This method seems to produce more "
                  "consistently aesthetically pleasing results")
 
+        section = "color.manual_balance"
+        self.add_section(title=section,
+                         info="Options for manually altering the balance of colors of the swapped "
+                              "face")
+        self.add_item(
+            section=section, title="colorspace", datatype=str, default="HSV", gui_radio=True,
+            choices=["RGB", "HSV", "LAB", "YCrCb"],
+            info="The colorspace to use for adjustment: The three adjustment sliders will effect "
+                 "the image differently depending on which colorspace is selected:"
+                 "\n\t RGB: Red, Green, Blue. An additive colorspace where colors are obtained by "
+                 "a linear combination of Red, Green, and Blue values. The three channels are "
+                 "correlated by the amount of light hitting the surface. In RGB color space the "
+                 "color information is separated into three channels but the same three channels "
+                 "also encode brightness information."
+                 "\n\t HSV: Hue, Saturation, Value. Hue - Dominant wavelength. Saturation - "
+                 "Purity / shades of color. Value - Intensity. Best thing is that it uses only "
+                 "one channel to describe color (H), making it very intuitive to specify color."
+                 "\n\t LAB: Lightness, A, B. Lightness - Intensity. A - Color range from green to "
+                 "magenta. B - Color range from blue to yellow. The L channel is independent of "
+                 "color information and encodes brightness only. The other two channels encode "
+                 "color."
+                 "\n\t YCrCb: Y – Luminance or Luma component obtained from RGB after gamma "
+                 "correction. Cr - how far is the red component from Luma. Cb - how far is the "
+                 "blue component from Luma. Separates the luminance and chrominance components "
+                 "into different channels.")
+        self.add_item(
+            section=section, title="balance_1", datatype=float, default=0.0, rounding=1,
+            min_max=(-100.0, 100.0),
+            info="Balance of channel 1: "
+                 "\n\tRGB: Red "
+                 "\n\tHSV: Hue "
+                 "\n\tLAB: Lightness "
+                 "\n\tYCrCb: Luma ")
+        self.add_item(
+            section=section, title="balance_2", datatype=float, default=0.0, rounding=1,
+            min_max=(-100.0, 100.0),
+            info="Balance of channel 2: "
+                 "\n\tRGB: Green "
+                 "\n\tHSV: Saturation "
+                 "\n\tLAB: Green > Magenta "
+                 "\n\tYCrCb: Distance of red from Luma")
+        self.add_item(
+            section=section, title="balance_3", datatype=float, default=0.0, rounding=1,
+            min_max=(-100.0, 100.0),
+            info="Balance of channel 3: "
+                 "\n\tRGB: Blue "
+                 "\n\tHSV: Intensity "
+                 "\n\tLAB: Blue > Yellow "
+                 "\n\tYCrCb: Distance of blue from Luma")
         section = "color.match_hist"
         self.add_section(title=section,
                          info="Options for matching the histograms between the source and "

plugins/convert/color/manual_balance.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python3
+""" Manual Balance colour adjustment plugin for faceswap.py converter """
+
+import cv2
+import numpy as np
+from ._base import Adjustment
+
+
+class Color(Adjustment):
+    """ Adjust the mean of the color channels to be the same for the swap and old frame """
+
+    def process(self, old_face, new_face, raw_mask):
+        image = self.convert_colorspace(new_face * 255.0)
+        adjustment = np.array([self.config["balance_1"] / 100.0,
+                               self.config["balance_2"] / 100.0,
+                               self.config["balance_3"] / 100.0]).astype("float32")
+        for idx in range(3):
+            if adjustment[idx] >= 0:
+                image[:, :, idx] = ((1 - image[:, :, idx]) * adjustment[idx]) + image[:, :, idx]
+            else:
+                image[:, :, idx] = image[:, :, idx] * (1 + adjustment[idx])
+
+        image = self.convert_colorspace(image * 255.0, to_bgr=True)
+        return image
+
+    def convert_colorspace(self, new_face, to_bgr=False):
+        """ Convert colorspace based on mode or back to bgr """
+        mode = self.config["colorspace"].lower()
+        colorspace = "YCrCb" if mode == "ycrcb" else mode.upper()
+        conversion = "{}2BGR".format(colorspace) if to_bgr else "BGR2{}".format(colorspace)
+        image = cv2.cvtColor(new_face.astype("uint8"),  # pylint: disable=no-member
+                             getattr(cv2, "COLOR_{}".format(conversion))).astype("float32") / 255.0
+        return image

tools/lib_alignments/media.py

@@ -134,7 +134,7 @@ def check_input_folder(self):
     def valid_extension(filename):
         """ Check whether passed in file has a valid extension """
         extension = os.path.splitext(filename)[1]
-        retval = extension in _image_extensions
+        retval = extension.lower() in _image_extensions
         logger.trace("Filename has valid extension: '%s': %s", filename, retval)
         return retval