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1 files changed, 60 insertions, 0 deletions

diff --git a/megapixels/app/processors/face_landmarks.py b/megapixels/app/processors/face_landmarks.py
new file mode 100644
index 00000000..dfcb9ee8
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+++ b/megapixels/app/processors/face_landmarks.py
@@ -0,0 +1,60 @@
+import os
+from os.path import join
+from pathlib import Path
+
+import cv2 as cv
+import numpy as np
+import imutils
+from app.utils import im_utils, logger_utils
+from app.models.bbox import BBox
+from app.settings import app_cfg as cfg
+from app.settings import types
+from app.models.bbox import BBox
+
+class LandmarksDLIB:
+
+  def __init__(self):
+    # init dlib
+    import dlib
+    self.log = logger_utils.Logger.getLogger()
+    self.predictor = dlib.shape_predictor(cfg.DIR_MODELS_DLIB_68PT)
+
+  def landmarks(self, im, bbox):
+    # Draw high-confidence faces
+    dim = im.shape[:2][::-1]
+    bbox = bbox.to_dlib()
+    im_gray = cv.cvtColor(im, cv.COLOR_BGR2GRAY)
+    landmarks = [[p.x, p.y] for p in self.predictor(im_gray, bbox).parts()]
+    return landmarks
+
+
+class LandmarksMTCNN:
+  
+  # https://github.com/ipazc/mtcnn
+  # pip install mtcnn
+
+  dnn_size = (400, 400)
+
+  def __init__(self, size=(400,400)):
+    from mtcnn.mtcnn import MTCNN
+    self.detector = MTCNN()
+
+  def detect(self, im, opt_size=None, opt_conf_thresh=None, opt_pyramids=None):
+    '''Detects face using MTCNN and returns (list) of BBox
+    :param im: (numpy.ndarray) image
+    :returns list of BBox
+    '''
+    rois = []
+    dnn_size = self.dnn_size if opt_size is None else opt_size
+    im = im_utils.resize(im, width=dnn_size[0], height=dnn_size[1])
+    dim = im.shape[:2][::-1]
+    
+    # run MTCNN
+    dets = self.detector.detect_faces(im)
+
+    for det in dets:
+      rect = det['box']
+      keypoints = det['keypoints']  # not using here. see 'face_landmarks.py'
+      bbox = BBox.from_xywh_dim(*rect, dim)
+      rois.append(bbox)
+    return rois
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