add-grayscale-equalized

remotecv/detectors/__init__.py

@@ -49,8 +49,17 @@ def get_min_size_for(self, size):
     def get_features(self, image):
         img = self.get_np_img(image)
 
+        return self.get_faces(img, image.size)
+
+    def get_grayscale_equalized_features(self, image):
+        img = self.get_np_img(image)
+        img_equalized = cv2.equalizeHist(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY))
+
+        return self.get_faces(img_equalized, image.size)
+
+    def get_faces(self, image, image_size):
         faces = self.__class__.cascade.detectMultiScale(
-            img, 1.2, 4, minSize=self.get_min_size_for(image.size)
+            image, 1.2, 4, minSize=self.get_min_size_for(image_size)
         )
         faces_scaled = []
 

remotecv/detectors/face_grayscale_equalized_detector/__init__.py

@@ -0,0 +1,30 @@
+# -*- coding: utf-8 -*-
+
+# thumbor imaging service
+# https://github.com/globocom/thumbor/wiki
+
+# Licensed under the MIT license:
+# http://www.opensource.org/licenses/mit-license
+# Copyright (c) 2022 globo.com <thumbor@g.globo>
+
+from remotecv.detectors import CascadeLoaderDetector
+
+HAIR_OFFSET = 0.12
+
+
+class FaceGrayscaleEqualizedDetector(CascadeLoaderDetector):
+    def __init__(self):
+        self.load_cascade_file(__file__, "haarcascade_frontalface_default.xml")
+
+    def __add_hair_offset(self, top, height):
+        return max(0, top - height * HAIR_OFFSET)
+
+    def detect(self, image):
+        features = self.get_grayscale_equalized_features(image)
+        points = []
+        if features:
+            for (left, top, width, height), _neighbors in features:
+                top = self.__add_hair_offset(top, height)
+                points.append([left, top, width, height])
+
+        return points