add age, gender, emotion stubs

1 files changed, 11 insertions, 17 deletions

diff --git a/megapixels/commands/demo/face_beauty.py b/megapixels/commands/demo/face_beauty.py
index b1612f7c..d31c5cee 100644
--- a/megapixels/commands/demo/face_beauty.py
+++ b/megapixels/commands/demo/face_beauty.py
@@ -1,6 +1,3 @@
-"""
-"""
-
 import click
 
 from app.settings import types
@@ -51,25 +48,23 @@ def cli(ctx, opt_fp_in, opt_fp_out, opt_gpu, opt_size, opt_force, opt_display):
   # load image
 
   im = cv.imread(opt_fp_in)
-  # im = cv.cvtColor(im, cv.COLOR_BGR2RGB)
-  if im.shape[0] > 1280:
-    new_shape = (1280, im.shape[1] * 1280 / im.shape[0])
-  elif im.shape[1] > 1280:
-    new_shape = (im.shape[0] * 1280 / im.shape[1], 1280)
-  elif im.shape[0] < 640 or im.shape[1] < 640:
-    new_shape = (im.shape[0] * 2, im.shape[1] * 2)
-  else:
-    new_shape = im.shape[0:2]
+  im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1])
 
-  im_resized = cv.resize(im, (int(new_shape[1]), int(new_shape[0])))
 
-  #im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1])
+  # TODO fix Keras CPU/GPU device selection issue
+  # NB: GPU visibility issues with dlib/keras
+  # Wrap this with cuda toggle and run before init dlib GPU
+
+  device_cur = os.getenv('CUDA_VISIBLE_DEVICES', '')
+  os.environ['CUDA_VISIBLE_DEVICES'] = ''
+  beauty_predictor = face_beauty.FaceBeauty()
+  os.environ['CUDA_VISIBLE_DEVICES'] = device_cur
 
 
   # ----------------------------------------------------------------------------
   # detect face
 
-  face_detector = face_detector.DetectorDLIBCNN()  # -1 for CPU
+  face_detector = face_detector.DetectorDLIBCNN(gpu=opt_gpu)  # -1 for CPU
   bboxes = face_detector.detect(im_resized, largest=True)
   bbox = bboxes[0]
   dim = im_resized.shape[:2][::-1]
@@ -82,8 +77,7 @@ def cli(ctx, opt_fp_in, opt_fp_out, opt_gpu, opt_size, opt_force, opt_display):
 
   # ----------------------------------------------------------------------------
   # beauty
-  
-  beauty_predictor = face_beauty.FaceBeauty()
+
   beauty_score = beauty_predictor.beauty(im_resized, bbox_dim)