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.gitattributes

@@ -33,3 +33,10 @@ 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
+GazeTracking/aayfryxljh.mp4 filter=lfs diff=lfs merge=lfs -text
+GazeTracking/adadagaze_tracked_output.avi filter=lfs diff=lfs merge=lfs -text
+GazeTracking/fake_gaze_tracked_output.avi filter=lfs diff=lfs merge=lfs -text
+GazeTracking/fake.mp4 filter=lfs diff=lfs merge=lfs -text
+GazeTracking/gaze_tracked_output.avi filter=lfs diff=lfs merge=lfs -text
+GazeTracking/gaze_tracking/trained_models/shape_predictor_68_face_landmarks.dat filter=lfs diff=lfs merge=lfs -text
+GazeTracking/real.mp4 filter=lfs diff=lfs merge=lfs -text

GazeTracking/.gitignore

@@ -0,0 +1,104 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/

GazeTracking/Blinks_pupil.py

@@ -0,0 +1,33 @@
+import csv
+
+def analyze_gaze_data(csv_file):
+    inconsistent_data = []
+    irregular_blinks = []
+
+    with open(csv_file, 'r') as csvfile:
+        csv_reader = csv.reader(csvfile)
+        next(csv_reader)  # Skip header row
+
+        for row in csv_reader:
+            frame_count, gaze_direction, left_pupil, right_pupil = row
+            
+            # Check for inconsistencies in eye movement with pupil coordinates
+            if gaze_direction != "Blinking":
+                if left_pupil == "(None, None)" or right_pupil == "(None, None)":
+                    inconsistent_data.append(frame_count)
+            
+            # Check for irregular blinks
+            if gaze_direction == "Blinking":
+                irregular_blinks.append(frame_count)
+    
+    return inconsistent_data, irregular_blinks
+
+def main():
+    csv_file = 'fake_gaze_data.csv'
+    inconsistent_data, irregular_blinks = analyze_gaze_data(csv_file)
+
+    print("Inconsistent eye movement with pupil coordinates detected in frames:", inconsistent_data)
+    print("Irregular blinks detected in frames:", irregular_blinks)
+
+if __name__ == "__main__":
+    main()

GazeTracking/Dockerfile

@@ -0,0 +1,13 @@
+FROM ubuntu:18.04
+RUN apt-get update
+RUN apt install -y python3
+RUN apt install -y python3-pip
+RUN apt install -y cmake
+RUN apt install -y libsm6
+RUN apt install -y libxext6
+RUN apt install -y libxrender1
+RUN apt install -y libfontconfig1
+RUN pip3 install --upgrade pip
+COPY .  /home/GazeTracking
+WORKDIR /home/GazeTracking
+RUN pip3 install -r requirements.txt

GazeTracking/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2019 Antoine Lamé
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

GazeTracking/Location_eye_csv.py

@@ -0,0 +1,87 @@
+import csv
+import cv2
+from gaze_tracking import GazeTracking
+
+# Replace 'video.mp4' with the path to your video file
+video_path = 'real.mp4'
+
+# Create a video capture object
+cap = cv2.VideoCapture(video_path)
+
+# Check if video opened successfully
+if not cap.isOpened():
+    print("Error opening video!")
+    exit()
+
+# Define output filename (change extension if needed)
+output_filename = "fake_gaze_tracked_output.avi"
+
+# Define video writer settings (adjust as needed)
+fourcc = cv2.VideoWriter_fourcc(*'XVID')
+out = cv2.VideoWriter(output_filename, fourcc, 20.0, (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))))
+
+gaze = GazeTracking()
+
+frame_count = 0
+
+while True:
+    # Read a frame from the video
+    ret, frame = cap.read()
+
+    # Check if frame is read correctly
+    if not ret:
+        print("No frame captured from video. Exiting...")
+        break
+
+    # Open CSV file for appending gaze data
+    with open('fake_gaze_data.csv', 'a', newline='') as csvfile:
+        csv_writer = csv.writer(csvfile)
+
+        # Send the frame to GazeTracking for analysis
+        gaze.refresh(frame)
+
+        # Get the annotated frame with gaze information
+        annotated_frame = gaze.annotated_frame()
+
+        text = ""
+
+        if gaze.is_blinking():
+            text = "Blinking"
+        elif gaze.is_right():
+            text = "Looking right"
+        elif gaze.is_left():
+            text = "Looking left"
+        elif gaze.is_center():
+            text = "Looking center"
+
+        # Add text overlay on the frame
+        cv2.putText(annotated_frame, text, (90, 60), cv2.FONT_HERSHEY_DUPLEX, 1.6, (147, 58, 31), 2)
+
+        # Get pupil coordinates
+        left_pupil = gaze.pupil_left_coords()
+        right_pupil = gaze.pupil_right_coords()
+
+        # Add pupil coordinates overlay
+        cv2.putText(annotated_frame, "Left pupil:  " + str(left_pupil), (90, 130), cv2.FONT_HERSHEY_DUPLEX, 0.9, (147, 58, 31), 1)
+        cv2.putText(annotated_frame, "Right pupil: " + str(right_pupil), (90, 165), cv2.FONT_HERSHEY_DUPLEX, 0.9, (147, 58, 31), 1)
+
+        # Update frame count
+        frame_count += 1
+
+        # Write gaze data to CSV file
+        csv_writer.writerow([frame_count, text, left_pupil, right_pupil])
+
+        # Display the frame
+        cv2.imshow("Demo", annotated_frame)
+
+        # Write the annotated frame to the output video
+        out.write(annotated_frame)
+
+        # Exit on 'Esc' key press
+        if cv2.waitKey(1) == 27:
+            break
+
+# Release resources
+cap.release()
+out.release()
+cv2.destroyAllWindows()

GazeTracking/README.md

@@ -0,0 +1,172 @@
+# Gaze Tracking
+
+![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)
+![Open Source Love](https://badges.frapsoft.com/os/v1/open-source.svg?v=103)
+![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
+[![GitHub stars](https://img.shields.io/github/stars/antoinelame/GazeTracking.svg?style=social)](https://github.com/antoinelame/GazeTracking/stargazers)
+
+This is a Python (2 and 3) library that provides a **webcam-based eye tracking system**. It gives you the exact position of the pupils and the gaze direction, in real time.
+
+[![Demo](https://i.imgur.com/WNqgQkO.gif)](https://youtu.be/YEZMk1P0-yw)
+
+_🚀 Quick note: I'm looking for job opportunities as a software developer, for exciting projects in ambitious companies. Anywhere in the world. Send me an email!_
+
+## Installation
+
+Clone this project:
+
+```shell
+git clone https://github.com/antoinelame/GazeTracking.git
+```
+
+### For Pip install
+Install these dependencies (NumPy, OpenCV, Dlib):
+
+```shell
+pip install -r requirements.txt
+```
+
+> The Dlib library has four primary prerequisites: Boost, Boost.Python, CMake and X11/XQuartx. If you doesn't have them, you can [read this article](https://www.pyimagesearch.com/2017/03/27/how-to-install-dlib/) to know how to easily install them.
+
+
+### For Anaconda install
+Install these dependencies (NumPy, OpenCV, Dlib):
+
+```shell
+conda env create --file environment.yml
+#After creating environment, activate it
+conda activate GazeTracking
+```
+
+
+### Verify Installation
+
+Run the demo:
+
+```shell
+python example.py
+```
+
+## Simple Demo
+
+```python
+import cv2
+from gaze_tracking import GazeTracking
+
+gaze = GazeTracking()
+webcam = cv2.VideoCapture(0)
+
+while True:
+    _, frame = webcam.read()
+    gaze.refresh(frame)
+
+    new_frame = gaze.annotated_frame()
+    text = ""
+
+    if gaze.is_right():
+        text = "Looking right"
+    elif gaze.is_left():
+        text = "Looking left"
+    elif gaze.is_center():
+        text = "Looking center"
+
+    cv2.putText(new_frame, text, (60, 60), cv2.FONT_HERSHEY_DUPLEX, 2, (255, 0, 0), 2)
+    cv2.imshow("Demo", new_frame)
+
+    if cv2.waitKey(1) == 27:
+        break
+```
+
+## Documentation
+
+In the following examples, `gaze` refers to an instance of the `GazeTracking` class.
+
+### Refresh the frame
+
+```python
+gaze.refresh(frame)
+```
+
+Pass the frame to analyze (numpy.ndarray). If you want to work with a video stream, you need to put this instruction in a loop, like the example above.
+
+### Position of the left pupil
+
+```python
+gaze.pupil_left_coords()
+```
+
+Returns the coordinates (x,y) of the left pupil.
+
+### Position of the right pupil
+
+```python
+gaze.pupil_right_coords()
+```
+
+Returns the coordinates (x,y) of the right pupil.
+
+### Looking to the left
+
+```python
+gaze.is_left()
+```
+
+Returns `True` if the user is looking to the left.
+
+### Looking to the right
+
+```python
+gaze.is_right()
+```
+
+Returns `True` if the user is looking to the right.
+
+### Looking at the center
+
+```python
+gaze.is_center()
+```
+
+Returns `True` if the user is looking at the center.
+
+### Horizontal direction of the gaze
+
+```python
+ratio = gaze.horizontal_ratio()
+```
+
+Returns a number between 0.0 and 1.0 that indicates the horizontal direction of the gaze. The extreme right is 0.0, the center is 0.5 and the extreme left is 1.0.
+
+### Vertical direction of the gaze
+
+```python
+ratio = gaze.vertical_ratio()
+```
+
+Returns a number between 0.0 and 1.0 that indicates the vertical direction of the gaze. The extreme top is 0.0, the center is 0.5 and the extreme bottom is 1.0.
+
+### Blinking
+
+```python
+gaze.is_blinking()
+```
+
+Returns `True` if the user's eyes are closed.
+
+### Webcam frame
+
+```python
+frame = gaze.annotated_frame()
+```
+
+Returns the main frame with pupils highlighted.
+
+## You want to help?
+
+Your suggestions, bugs reports and pull requests are welcome and appreciated. You can also starring ⭐️ the project!
+
+If the detection of your pupils is not completely optimal, you can send me a video sample of you looking in different directions. I would use it to improve the algorithm.
+
+## Licensing
+
+This project is released by Antoine Lamé under the terms of the MIT Open Source License. View LICENSE for more information.

GazeTracking/aayfryxljh.mp4

@@ -0,0 +1,3 @@
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+oid sha256:da7683e58ebd3684b21ea4815bf9bd3484ffebebe47484489da7c1df5e356f82
+size 10114027

GazeTracking/adadagaze_tracked_output.avi

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+version https://git-lfs.github.com/spec/v1
+oid sha256:395f80cdccab9c1398f05227990d3e995a104b4ee15be30a63a16ecdc5d8710c
+size 9030194

GazeTracking/build_and_run.sh

@@ -0,0 +1,12 @@
+IMAGE_NAME=gaze-tracking
+
+# allow root access to x server
+xhost local:root
+# build and run docker image
+([ "$(docker images -q ${IMAGE_NAME})" == "" ] && docker build -t ${IMAGE_NAME} . ) 
+([ "$(docker images -q ${IMAGE_NAME})" != "" ] && \
+docker run --rm --device /dev/video0 \
+	-e DISPLAY=${DISPLAY} \
+	-v /tmp/.X11-unix:/tmp/.X11-unix \
+	--env="QT_X11_NO_MITSHM=1" \
+	-it ${IMAGE_NAME} bash)

GazeTracking/environment.yml

@@ -0,0 +1,9 @@
+name: GazeTracking
+channels:
+  - conda-forge
+  - anaconda
+  - defaults
+dependencies:
+  - numpy == 1.16.1
+  - opencv == 3.4.*
+  - dlib == 19.17.*

GazeTracking/example.py

@@ -0,0 +1,74 @@
+import cv2
+from gaze_tracking import GazeTracking
+
+# Replace 'video.mp4' with the path to your video file
+video_path = 'apvzjkvnwn.mp4'
+
+# Create a video capture object
+cap = cv2.VideoCapture(video_path)
+
+# Check if video opened successfully
+if not cap.isOpened():
+    print("Error opening video!")
+    exit()
+
+# Define output filename (change extension if needed)
+output_filename = "gaze_tracked_output.avi"
+
+# Define video writer settings (adjust as needed)
+fourcc = cv2.VideoWriter_fourcc(*'XVID')
+out = cv2.VideoWriter(output_filename, fourcc, 20.0, (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))))
+
+gaze = GazeTracking()
+
+while True:
+    # Read a frame from the video
+    ret, frame = cap.read()
+
+    # Check if frame is read correctly
+    if not ret:
+        print("No frame captured from video. Exiting...")
+        break
+
+    # Send the frame to GazeTracking for analysis
+    gaze.refresh(frame)
+
+    # Get the annotated frame with gaze information
+    annotated_frame = gaze.annotated_frame()
+
+    text = ""
+    
+    if gaze.is_blinking():
+        text = "Blinking"
+    elif gaze.is_right():
+        text = "Looking right"
+    elif gaze.is_left():
+        text = "Looking left"
+    elif gaze.is_center():
+        text = "Looking center"
+
+    # Add text overlay on the frame
+    cv2.putText(annotated_frame, text, (90, 60), cv2.FONT_HERSHEY_DUPLEX, 1.6, (147, 58, 31), 2)
+
+    # Get pupil coordinates
+    left_pupil = gaze.pupil_left_coords()
+    right_pupil = gaze.pupil_right_coords()
+
+    # Add pupil coordinates overlay
+    cv2.putText(annotated_frame, "Left pupil:  " + str(left_pupil), (90, 130), cv2.FONT_HERSHEY_DUPLEX, 0.9, (147, 58, 31), 1)
+    cv2.putText(annotated_frame, "Right pupil: " + str(right_pupil), (90, 165), cv2.FONT_HERSHEY_DUPLEX, 0.9, (147, 58, 31), 1)
+
+    # Display the frame
+    cv2.imshow("Demo", annotated_frame)
+
+    # Write the annotated frame to the output video
+    out.write(annotated_frame)
+
+    # Exit on 'Esc' key press
+    if cv2.waitKey(1) == 27:
+        break
+
+# Release resources
+cap.release()
+out.release()
+cv2.destroyAllWindows()

GazeTracking/fake.mp4

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+oid sha256:e0c586c4e632586efde54be8fd4219c89ac5d585edceafdcb1e8f2654eee6224
+size 4110523

GazeTracking/fake_gaze_data.csv

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+281,Looking center,"(1019, 395)","(1109, 398)"
+282,Looking center,"(1016, 394)","(1107, 397)"
+283,Looking center,"(1015, 393)","(1105, 397)"
+284,Looking center,"(1014, 390)","(1104, 393)"
+285,Looking center,"(1013, 387)","(1102, 390)"
+286,Looking center,"(1011, 385)","(1100, 387)"
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+289,Looking center,"(1009, 375)","(1100, 377)"
+290,Looking center,"(1011, 374)","(1101, 376)"
+291,Blinking,"(1014, 372)","(1104, 376)"
+292,Blinking,"(1018, 370)","(1107, 373)"
+293,Looking center,"(1022, 370)","(1112, 373)"
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+296,Looking center,"(1035, 372)","(1126, 380)"
+297,Looking center,"(1039, 375)","(1131, 384)"
+298,Looking center,"(1042, 379)","(1135, 389)"
+299,Looking center,"(1044, 386)","(1138, 396)"
+300,Looking center,"(1045, 393)","(1140, 403)"

GazeTracking/gaze_tracked_output.avi

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+version https://git-lfs.github.com/spec/v1
+oid sha256:395f80cdccab9c1398f05227990d3e995a104b4ee15be30a63a16ecdc5d8710c
+size 9030194

GazeTracking/gaze_tracking/__init__.py

@@ -0,0 +1 @@
+from .gaze_tracking import GazeTracking

GazeTracking/gaze_tracking/calibration.py

@@ -0,0 +1,77 @@
+from __future__ import division
+import cv2
+from .pupil import Pupil
+
+
+class Calibration(object):
+    """
+    This class calibrates the pupil detection algorithm by finding the
+    best binarization threshold value for the person and the webcam.
+    """
+
+    def __init__(self):
+        self.nb_frames = 20
+        self.thresholds_left = []
+        self.thresholds_right = []
+
+    def is_complete(self):
+        """Returns true if the calibration is completed"""
+        return len(self.thresholds_left) >= self.nb_frames and len(self.thresholds_right) >= self.nb_frames
+
+    def threshold(self, side):
+        """Returns the threshold value for the given eye.
+
+        Argument:
+            side: Indicates whether it's the left eye (0) or the right eye (1)
+        """
+        if side == 0:
+            return int(sum(self.thresholds_left) / len(self.thresholds_left))
+        elif side == 1:
+            return int(sum(self.thresholds_right) / len(self.thresholds_right))
+
+    @staticmethod
+    def iris_size(frame):
+        """Returns the percentage of space that the iris takes up on
+        the surface of the eye.
+
+        Argument:
+            frame (numpy.ndarray): Binarized iris frame
+        """
+        frame = frame[5:-5, 5:-5]
+        height, width = frame.shape[:2]
+        nb_pixels = height * width
+        nb_blacks = nb_pixels - cv2.countNonZero(frame)
+        return nb_blacks / nb_pixels
+
+    @staticmethod
+    def find_best_threshold(eye_frame):
+        """Calculates the optimal threshold to binarize the
+        frame for the given eye.
+
+        Argument:
+            eye_frame (numpy.ndarray): Frame of the eye to be analyzed
+        """
+        average_iris_size = 0.48
+        trials = {}
+
+        for threshold in range(5, 100, 5):
+            iris_frame = Pupil.image_processing(eye_frame, threshold)
+            trials[threshold] = Calibration.iris_size(iris_frame)
+
+        best_threshold, iris_size = min(trials.items(), key=(lambda p: abs(p[1] - average_iris_size)))
+        return best_threshold
+
+    def evaluate(self, eye_frame, side):
+        """Improves calibration by taking into consideration the
+        given image.
+
+        Arguments:
+            eye_frame (numpy.ndarray): Frame of the eye
+            side: Indicates whether it's the left eye (0) or the right eye (1)
+        """
+        threshold = self.find_best_threshold(eye_frame)
+
+        if side == 0:
+            self.thresholds_left.append(threshold)
+        elif side == 1:
+            self.thresholds_right.append(threshold)

GazeTracking/gaze_tracking/eye.py

@@ -0,0 +1,119 @@
+import math
+import numpy as np
+import cv2
+from .pupil import Pupil
+
+
+class Eye(object):
+    """
+    This class creates a new frame to isolate the eye and
+    initiates the pupil detection.
+    """
+
+    LEFT_EYE_POINTS = [36, 37, 38, 39, 40, 41]
+    RIGHT_EYE_POINTS = [42, 43, 44, 45, 46, 47]
+
+    def __init__(self, original_frame, landmarks, side, calibration):
+        self.frame = None
+        self.origin = None
+        self.center = None
+        self.pupil = None
+        self.landmark_points = None
+
+        self._analyze(original_frame, landmarks, side, calibration)
+
+    @staticmethod
+    def _middle_point(p1, p2):
+        """Returns the middle point (x,y) between two points
+
+        Arguments:
+            p1 (dlib.point): First point
+            p2 (dlib.point): Second point
+        """
+        x = int((p1.x + p2.x) / 2)
+        y = int((p1.y + p2.y) / 2)
+        return (x, y)
+
+    def _isolate(self, frame, landmarks, points):
+        """Isolate an eye, to have a frame without other part of the face.
+
+        Arguments:
+            frame (numpy.ndarray): Frame containing the face
+            landmarks (dlib.full_object_detection): Facial landmarks for the face region
+            points (list): Points of an eye (from the 68 Multi-PIE landmarks)
+        """
+        region = np.array([(landmarks.part(point).x, landmarks.part(point).y) for point in points])
+        region = region.astype(np.int32)
+        self.landmark_points = region
+
+        # Applying a mask to get only the eye
+        height, width = frame.shape[:2]
+        black_frame = np.zeros((height, width), np.uint8)
+        mask = np.full((height, width), 255, np.uint8)
+        cv2.fillPoly(mask, [region], (0, 0, 0))
+        eye = cv2.bitwise_not(black_frame, frame.copy(), mask=mask)
+
+        # Cropping on the eye
+        margin = 5
+        min_x = np.min(region[:, 0]) - margin
+        max_x = np.max(region[:, 0]) + margin
+        min_y = np.min(region[:, 1]) - margin
+        max_y = np.max(region[:, 1]) + margin
+
+        self.frame = eye[min_y:max_y, min_x:max_x]
+        self.origin = (min_x, min_y)
+
+        height, width = self.frame.shape[:2]
+        self.center = (width / 2, height / 2)
+
+    def _blinking_ratio(self, landmarks, points):
+        """Calculates a ratio that can indicate whether an eye is closed or not.
+        It's the division of the width of the eye, by its height.
+
+        Arguments:
+            landmarks (dlib.full_object_detection): Facial landmarks for the face region
+            points (list): Points of an eye (from the 68 Multi-PIE landmarks)
+
+        Returns:
+            The computed ratio
+        """
+        left = (landmarks.part(points[0]).x, landmarks.part(points[0]).y)
+        right = (landmarks.part(points[3]).x, landmarks.part(points[3]).y)
+        top = self._middle_point(landmarks.part(points[1]), landmarks.part(points[2]))
+        bottom = self._middle_point(landmarks.part(points[5]), landmarks.part(points[4]))
+
+        eye_width = math.hypot((left[0] - right[0]), (left[1] - right[1]))
+        eye_height = math.hypot((top[0] - bottom[0]), (top[1] - bottom[1]))
+
+        try:
+            ratio = eye_width / eye_height
+        except ZeroDivisionError:
+            ratio = None
+
+        return ratio
+
+    def _analyze(self, original_frame, landmarks, side, calibration):
+        """Detects and isolates the eye in a new frame, sends data to the calibration
+        and initializes Pupil object.
+
+        Arguments:
+            original_frame (numpy.ndarray): Frame passed by the user
+            landmarks (dlib.full_object_detection): Facial landmarks for the face region
+            side: Indicates whether it's the left eye (0) or the right eye (1)
+            calibration (calibration.Calibration): Manages the binarization threshold value
+        """
+        if side == 0:
+            points = self.LEFT_EYE_POINTS
+        elif side == 1:
+            points = self.RIGHT_EYE_POINTS
+        else:
+            return
+
+        self.blinking = self._blinking_ratio(landmarks, points)
+        self._isolate(original_frame, landmarks, points)
+
+        if not calibration.is_complete():
+            calibration.evaluate(self.frame, side)
+
+        threshold = calibration.threshold(side)
+        self.pupil = Pupil(self.frame, threshold)

GazeTracking/gaze_tracking/gaze_tracking.py

@@ -0,0 +1,133 @@
+from __future__ import division
+import os
+import cv2
+import dlib
+from .eye import Eye
+from .calibration import Calibration
+
+
+class GazeTracking(object):
+    """
+    This class tracks the user's gaze.
+    It provides useful information like the position of the eyes
+    and pupils and allows to know if the eyes are open or closed
+    """
+
+    def __init__(self):
+        self.frame = None
+        self.eye_left = None
+        self.eye_right = None
+        self.calibration = Calibration()
+
+        # _face_detector is used to detect faces
+        self._face_detector = dlib.get_frontal_face_detector()
+
+        # _predictor is used to get facial landmarks of a given face
+        cwd = os.path.abspath(os.path.dirname(__file__))
+        model_path = os.path.abspath(os.path.join(cwd, "trained_models/shape_predictor_68_face_landmarks.dat"))
+        self._predictor = dlib.shape_predictor(model_path)
+
+    @property
+    def pupils_located(self):
+        """Check that the pupils have been located"""
+        try:
+            int(self.eye_left.pupil.x)
+            int(self.eye_left.pupil.y)
+            int(self.eye_right.pupil.x)
+            int(self.eye_right.pupil.y)
+            return True
+        except Exception:
+            return False
+
+    def _analyze(self):
+        """Detects the face and initialize Eye objects"""
+        frame = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
+        faces = self._face_detector(frame)
+
+        try:
+            landmarks = self._predictor(frame, faces[0])
+            self.eye_left = Eye(frame, landmarks, 0, self.calibration)
+            self.eye_right = Eye(frame, landmarks, 1, self.calibration)
+
+        except IndexError:
+            self.eye_left = None
+            self.eye_right = None
+
+    def refresh(self, frame):
+        """Refreshes the frame and analyzes it.
+
+        Arguments:
+            frame (numpy.ndarray): The frame to analyze
+        """
+        self.frame = frame
+        self._analyze()
+
+    def pupil_left_coords(self):
+        """Returns the coordinates of the left pupil"""
+        if self.pupils_located:
+            x = self.eye_left.origin[0] + self.eye_left.pupil.x
+            y = self.eye_left.origin[1] + self.eye_left.pupil.y
+            return (x, y)
+
+    def pupil_right_coords(self):
+        """Returns the coordinates of the right pupil"""
+        if self.pupils_located:
+            x = self.eye_right.origin[0] + self.eye_right.pupil.x
+            y = self.eye_right.origin[1] + self.eye_right.pupil.y
+            return (x, y)
+
+    def horizontal_ratio(self):
+        """Returns a number between 0.0 and 1.0 that indicates the
+        horizontal direction of the gaze. The extreme right is 0.0,
+        the center is 0.5 and the extreme left is 1.0
+        """
+        if self.pupils_located:
+            pupil_left = self.eye_left.pupil.x / (self.eye_left.center[0] * 2 - 10)
+            pupil_right = self.eye_right.pupil.x / (self.eye_right.center[0] * 2 - 10)
+            return (pupil_left + pupil_right) / 2
+
+    def vertical_ratio(self):
+        """Returns a number between 0.0 and 1.0 that indicates the
+        vertical direction of the gaze. The extreme top is 0.0,
+        the center is 0.5 and the extreme bottom is 1.0
+        """
+        if self.pupils_located:
+            pupil_left = self.eye_left.pupil.y / (self.eye_left.center[1] * 2 - 10)
+            pupil_right = self.eye_right.pupil.y / (self.eye_right.center[1] * 2 - 10)
+            return (pupil_left + pupil_right) / 2
+
+    def is_right(self):
+        """Returns true if the user is looking to the right"""
+        if self.pupils_located:
+            return self.horizontal_ratio() <= 0.35
+
+    def is_left(self):
+        """Returns true if the user is looking to the left"""
+        if self.pupils_located:
+            return self.horizontal_ratio() >= 0.65
+
+    def is_center(self):
+        """Returns true if the user is looking to the center"""
+        if self.pupils_located:
+            return self.is_right() is not True and self.is_left() is not True
+
+    def is_blinking(self):
+        """Returns true if the user closes his eyes"""
+        if self.pupils_located:
+            blinking_ratio = (self.eye_left.blinking + self.eye_right.blinking) / 2
+            return blinking_ratio > 3.8
+
+    def annotated_frame(self):
+        """Returns the main frame with pupils highlighted"""
+        frame = self.frame.copy()
+
+        if self.pupils_located:
+            color = (0, 255, 0)
+            x_left, y_left = self.pupil_left_coords()
+            x_right, y_right = self.pupil_right_coords()
+            cv2.line(frame, (x_left - 5, y_left), (x_left + 5, y_left), color)
+            cv2.line(frame, (x_left, y_left - 5), (x_left, y_left + 5), color)
+            cv2.line(frame, (x_right - 5, y_right), (x_right + 5, y_right), color)
+            cv2.line(frame, (x_right, y_right - 5), (x_right, y_right + 5), color)
+
+        return frame

GazeTracking/gaze_tracking/pupil.py

@@ -0,0 +1,54 @@
+import numpy as np
+import cv2
+
+
+class Pupil(object):
+    """
+    This class detects the iris of an eye and estimates
+    the position of the pupil
+    """
+
+    def __init__(self, eye_frame, threshold):
+        self.iris_frame = None
+        self.threshold = threshold
+        self.x = None
+        self.y = None
+
+        self.detect_iris(eye_frame)
+
+    @staticmethod
+    def image_processing(eye_frame, threshold):
+        """Performs operations on the eye frame to isolate the iris
+
+        Arguments:
+            eye_frame (numpy.ndarray): Frame containing an eye and nothing else
+            threshold (int): Threshold value used to binarize the eye frame
+
+        Returns:
+            A frame with a single element representing the iris
+        """
+        kernel = np.ones((3, 3), np.uint8)
+        new_frame = cv2.bilateralFilter(eye_frame, 10, 15, 15)
+        new_frame = cv2.erode(new_frame, kernel, iterations=3)
+        new_frame = cv2.threshold(new_frame, threshold, 255, cv2.THRESH_BINARY)[1]
+
+        return new_frame
+
+    def detect_iris(self, eye_frame):
+        """Detects the iris and estimates the position of the iris by
+        calculating the centroid.
+
+        Arguments:
+            eye_frame (numpy.ndarray): Frame containing an eye and nothing else
+        """
+        self.iris_frame = self.image_processing(eye_frame, self.threshold)
+
+        contours, _ = cv2.findContours(self.iris_frame, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)[-2:]
+        contours = sorted(contours, key=cv2.contourArea)
+
+        try:
+            moments = cv2.moments(contours[-2])
+            self.x = int(moments['m10'] / moments['m00'])
+            self.y = int(moments['m01'] / moments['m00'])
+        except (IndexError, ZeroDivisionError):
+            pass

GazeTracking/gaze_tracking/trained_models/shape_predictor_68_face_landmarks.dat

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbdc2cb80eb9aa7a758672cbfdda32ba6300efe9b6e6c7a299ff7e736b11b92f
+size 99693937

GazeTracking/real.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c1d5eb63db59e8cf3bbe1b4b8cc9e31c3c4087f29288e9a3ab4a4e9d0c60080d
+size 4480223

GazeTracking/requirements.txt

@@ -0,0 +1,3 @@
+numpy == 1.22.0
+opencv_python == 4.2.0.32
+dlib == 19.16.0