Update app.py

app.py

@@ -77,39 +77,6 @@ def get_dlib_face_detector(predictor_path: str = "shape_predictor_68_face_landma
     return detect_face_landmarks
 
 
-def display_facial_landmarks(
-    img: Image, 
-    landmarks: List[np.ndarray],
-    fig_size=[15, 15]
-):
-    plot_style = dict(
-        marker='o',
-        markersize=4,
-        linestyle='-',
-        lw=2
-    )
-    pred_type = collections.namedtuple('prediction_type', ['slice', 'color'])
-    pred_types = {
-        'face': pred_type(slice(0, 17), (0.682, 0.780, 0.909, 0.5)),
-        'eyebrow1': pred_type(slice(17, 22), (1.0, 0.498, 0.055, 0.4)),
-        'eyebrow2': pred_type(slice(22, 27), (1.0, 0.498, 0.055, 0.4)),
-        'nose': pred_type(slice(27, 31), (0.345, 0.239, 0.443, 0.4)),
-        'nostril': pred_type(slice(31, 36), (0.345, 0.239, 0.443, 0.4)),
-        'eye1': pred_type(slice(36, 42), (0.596, 0.875, 0.541, 0.3)),
-        'eye2': pred_type(slice(42, 48), (0.596, 0.875, 0.541, 0.3)),
-        'lips': pred_type(slice(48, 60), (0.596, 0.875, 0.541, 0.3)),
-        'teeth': pred_type(slice(60, 68), (0.596, 0.875, 0.541, 0.4))
-    }
-
-
-    for face in landmarks:
-        for pred_type in pred_types.values():
-            ax.plot(
-                face[pred_type.slice, 0],
-                face[pred_type.slice, 1],
-                color=pred_type.color, **plot_style
-            )
-
 import PIL.Image
 import PIL.ImageFile
 import numpy as np
@@ -203,7 +170,6 @@ def inference(image):
   face_detector = get_dlib_face_detector()
   landmarks = face_detector(img)
   
-  display_facial_landmarks(img, landmarks, fig_size=[5, 5])
   
   for landmark in landmarks:
       face = align_and_crop_face(img, landmark, expand=1.3)