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wissemkarous
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Parent(s):
1c32def
scripts
Browse files- .gitattributes +1 -0
- extract_lip_coordinates.py +56 -0
- shape_predictor_68_face_landmarks_GTX.dat +3 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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shape_predictor_68_face_landmarks_GTX.dat filter=lfs diff=lfs merge=lfs -text
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extract_lip_coordinates.py
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import cv2
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import dlib
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import glob
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import numpy as np
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import torch
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import streamlit as st
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detector = dlib.get_frontal_face_detector()
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predictor = dlib.shape_predictor("scripts/shape_predictor_68_face_landmarks_GTX.dat")
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def extract_lip_coordinates(detector, predictor, img_path):
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image = cv2.imread(img_path)
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image = cv2.resize(image, (600, 500))
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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rects = detector(gray)
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retries = 3
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while retries > 0:
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try:
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assert len(rects) == 1
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break
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except AssertionError as e:
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retries -= 1
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for rect in rects:
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# apply the shape predictor to the face ROI
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shape = predictor(gray, rect)
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x = []
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y = []
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for n in range(48, 68):
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x.append(shape.part(n).x)
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y.append(shape.part(n).y)
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return [x, y]
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@st.cache_data(show_spinner=False, persist=True)
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def generate_lip_coordinates(frame_images_directory):
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frames = glob.glob(frame_images_directory + "/*.jpg")
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frames.sort()
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img = cv2.imread(frames[0])
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height, width, layers = img.shape
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coords = []
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for frame in frames:
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x_coords, y_coords = extract_lip_coordinates(detector, predictor, frame)
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normalized_coords = []
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for x, y in zip(x_coords, y_coords):
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normalized_x = x / width
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normalized_y = y / height
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normalized_coords.append((normalized_x, normalized_y))
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coords.append(normalized_coords)
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coords_array = np.array(coords, dtype=np.float32)
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coords_array = torch.from_numpy(coords_array)
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return coords_array
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shape_predictor_68_face_landmarks_GTX.dat
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version https://git-lfs.github.com/spec/v1
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oid sha256:249a69a1d5f2d7c714a92934d35367d46eb52dc308d46717e82d49e8386b3b80
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size 66435981
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