change bbox to norm, refine face extractor

1 files changed, 8 insertions, 7 deletions

diff --git a/megapixels/app/processors/face_beauty.py b/megapixels/app/processors/face_beauty.py
index a01c6834..e2d54c98 100644
--- a/megapixels/app/processors/face_beauty.py
+++ b/megapixels/app/processors/face_beauty.py
@@ -1,3 +1,7 @@
+"""
+https://github.com/ustcqidi/BeautyPredict
+"""
+
 import sys
 import os
 from os.path import join
@@ -45,18 +49,15 @@ class FaceBeauty:
     self.model.load_weights(fp_model)
 
 
-  def beauty(self, im, bbox_dim):
+  def beauty(self, im, bbox_norm):
     '''Predicts facial "beauty" score based on SCUT-FBP attractiveness labels
     :param im: (numpy.ndarray) BGR image
     :param bbox_dim: (BBox) dimensioned BBox
     :returns (float) 0.0-1.0 with 1 being most attractive
     '''
-
-    face = bbox_dim.to_xyxy()
-    self.log.debug(f'face: {face}')
-
-    cropped_im = im[face[1]:face[3], face[0]:face[2]]
-
+    dim = im.shape[:2][::-1]
+    roi = bbox_norm.to_dim(dim).to_xyxy()
+    cropped_im = im[roi[1]:roi[3], roi[0]:roi[2]]
     im_resized = cv.resize(cropped_im, (224, 224))  # force size
     im_norm = np.array([(im_resized - 127.5) / 127.5])  # subtract mean