scripts

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+shape_predictor_68_face_landmarks_GTX.dat filter=lfs diff=lfs merge=lfs -text

extract_lip_coordinates.py

@@ -0,0 +1,56 @@
+import cv2
+import dlib
+import glob
+import numpy as np
+import torch
+import streamlit as st
+
+detector = dlib.get_frontal_face_detector()
+predictor = dlib.shape_predictor("scripts/shape_predictor_68_face_landmarks_GTX.dat")
+
+
+def extract_lip_coordinates(detector, predictor, img_path):
+    image = cv2.imread(img_path)
+    image = cv2.resize(image, (600, 500))
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    rects = detector(gray)
+    retries = 3
+    while retries > 0:
+        try:
+            assert len(rects) == 1
+            break
+        except AssertionError as e:
+            retries -= 1
+
+    for rect in rects:
+        # apply the shape predictor to the face ROI
+        shape = predictor(gray, rect)
+        x = []
+        y = []
+        for n in range(48, 68):
+            x.append(shape.part(n).x)
+            y.append(shape.part(n).y)
+    return [x, y]
+
+
+@st.cache_data(show_spinner=False, persist=True)
+def generate_lip_coordinates(frame_images_directory):
+    frames = glob.glob(frame_images_directory + "/*.jpg")
+    frames.sort()
+
+    img = cv2.imread(frames[0])
+    height, width, layers = img.shape
+
+    coords = []
+    for frame in frames:
+        x_coords, y_coords = extract_lip_coordinates(detector, predictor, frame)
+        normalized_coords = []
+        for x, y in zip(x_coords, y_coords):
+            normalized_x = x / width
+            normalized_y = y / height
+            normalized_coords.append((normalized_x, normalized_y))
+        coords.append(normalized_coords)
+    coords_array = np.array(coords, dtype=np.float32)
+    coords_array = torch.from_numpy(coords_array)
+    return coords_array

shape_predictor_68_face_landmarks_GTX.dat

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:249a69a1d5f2d7c714a92934d35367d46eb52dc308d46717e82d49e8386b3b80
+size 66435981