externalize drawing, cleanup

1 files changed, 9 insertions, 18 deletions

diff --git a/megapixels/app/processors/face_detector.py b/megapixels/app/processors/face_detector.py
index a805a474..6bf27576 100644
--- a/megapixels/app/processors/face_detector.py
+++ b/megapixels/app/processors/face_detector.py
@@ -65,8 +65,6 @@ class DetectorHaar:
 
 class DetectorDLIBCNN:
   
-
-  dnn_size = (300, 300)
   pyramids = 0
   conf_thresh = 0.85
 
@@ -79,13 +77,10 @@ class DetectorDLIBCNN:
     self.detector = dlib.cnn_face_detection_model_v1(cfg.DIR_MODELS_DLIB_CNN)
     os.environ['CUDA_VISIBLE_DEVICES'] = cuda_visible_devices  # reset
 
-  def detect(self, im, size=None, conf_thresh=None, pyramids=None, largest=False, zone=None):
+  def detect(self, im, conf_thresh=None, pyramids=None, largest=False, zone=None):
     bboxes = []
     conf_thresh = self.conf_thresh if conf_thresh is None else conf_thresh
     pyramids = self.pyramids if pyramids is None else pyramids
-    dnn_size = self.dnn_size if size is None else size
-    # resize image
-    im = im_utils.resize(im, width=dnn_size[0], height=dnn_size[1])
     dim = im.shape[:2][::-1]
     im = im_utils.bgr2rgb(im)  # convert to RGB for dlib
     # run detector
@@ -110,7 +105,6 @@ class DetectorDLIBCNN:
 
 class DetectorDLIBHOG:
 
-  size = (320, 240)
   pyramids = 0
   conf_thresh = 0.85
 
@@ -119,12 +113,9 @@ class DetectorDLIBHOG:
     self.log = logger_utils.Logger.getLogger()
     self.detector = dlib.get_frontal_face_detector()
 
-  def detect(self, im, size=None, conf_thresh=None, pyramids=0, largest=False, zone=False):
+  def detect(self, im, conf_thresh=None, pyramids=0, largest=False, zone=False):
     conf_thresh = self.conf_thresh if conf_thresh is None else conf_thresh
-    dnn_size = self.size if size is None else size
     pyramids = self.pyramids if pyramids is None else pyramids
-    
-    im = im_utils.resize(im, width=dnn_size[0], height=dnn_size[1])
     dim = im.shape[:2][::-1]
     im = im_utils.bgr2rgb(im)  # ?
     hog_results = self.detector.run(im, pyramids)
@@ -153,23 +144,23 @@ class DetectorCVDNN:
   dnn_scale = 1.0  # fixed
   dnn_mean = (104.0, 177.0, 123.0)  # fixed
   dnn_crop = False  # crop or force resize
-  size = (300, 300)
-  conf_thresh = 0.85
+  blob_size = (300, 300)
+  conf_thresh = 0.95
   
   def __init__(self):
-    import dlib
+    self.log = logger_utils.Logger.getLogger()
     fp_prototxt = join(cfg.DIR_MODELS_CAFFE, 'face_detect', 'opencv_face_detector.prototxt')
     fp_model = join(cfg.DIR_MODELS_CAFFE, 'face_detect', 'opencv_face_detector.caffemodel')
     self.net = cv.dnn.readNet(fp_prototxt, fp_model)
     self.net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
     self.net.setPreferableTarget(cv.dnn.DNN_TARGET_CPU)
 
-  def detect(self, im, size=None, conf_thresh=None, largest=False, pyramids=None, zone=False):
+  def detect(self, im, conf_thresh=None, largest=False, pyramids=None, zone=False):
     """Detects faces and returns (list) of (BBox)"""
     conf_thresh = self.conf_thresh if conf_thresh is None else conf_thresh
-    dnn_size = self.size if size is None else size
-    im = cv.resize(im, dnn_size)
-    blob = cv.dnn.blobFromImage(im, self.dnn_scale, dnn_size, self.dnn_mean)
+    im = cv.resize(im, self.blob_size)
+    dim = im.shape[:2][::-1]
+    blob = cv.dnn.blobFromImage(im, self.dnn_scale, dim, self.dnn_mean)
     self.net.setInput(blob)
     net_outputs = self.net.forward()