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aligners/differentiable_face_aligner/dfa/__init__.py

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+from .models.retinaface import RetinaFace
+from .utils.model_utils import load_model
+from .config import cfg_mnet, cfg_re50
+from .layers.functions.prior_box import PriorBox
+from .preprocessor import Preprocessor
+
+def get_landmark_predictor(network='mobile0.25', use_aggregator=True, input_size=160):
+
+    cfg = None
+    if network == "mobile0.25":
+        cfg = cfg_mnet
+    elif network == "resnet50":
+        cfg = cfg_re50
+    net = RetinaFace(cfg=cfg, phase = 'test', use_aggregator=use_aggregator)
+    priorbox = PriorBox(image_size=(input_size, input_size),
+                        min_sizes=[[64, 80], [96, 112], [128, 144]],
+                        steps=[8, 16, 32],
+                        clip=False,
+                        variances=[0.1, 0.2],)
+
+    # aligner = Aligner(net, priorbox, input_size, output_size=output_size)
+    # return aligner
+    return net, priorbox
+
+
+def get_preprocessor(output_size=160, padding=0.0, padding_val='zero'):
+    return Preprocessor(output_size=output_size, padding=padding, padding_val=padding_val)