feat: switch to objects

src/environment.py

@@ -0,0 +1,125 @@
+import logging
+
+import cv2
+import mediapipe as mp
+import pygame as pg
+
+from parts.eye import Eye
+
+
+class Environment:
+    def __init__(self, camera: cv2.VideoCapture) -> None:
+        # store reference to webcam
+        self.cam = camera
+
+        # mediapipe stuff
+        self.mp_drawing = mp.solutions.drawing_utils  # type: ignore
+        self.mp_drawing_styles = mp.solutions.drawing_styles  # type: ignore
+        self.mp_face_mesh = mp.solutions.face_mesh  # type: ignore
+
+        # init pygame
+        pg.init()
+
+        # get screen size from webcam
+        self.screen_width = camera.get(3)
+        self.screen_height = camera.get(4)
+
+        # create screen
+        self.screen: pg.Surface = pg.display.set_mode(
+            (self.screen_width, self.screen_height),
+            pg.DOUBLEBUF | pg.HWSURFACE,
+        )  # type: ignore
+        pg.display.set_caption("Projet APP")
+
+        # create body parts
+        self.body_parts = {
+            "left_eye": Eye(False),
+            "right_eye": Eye(True),
+        }
+
+    def start(self) -> None:
+        while self.cam.isOpened():
+            # read webcam
+            success, self.frame = self.cam.read()
+            if not success:
+                logging.debug("Ignoring empty camera frame.")
+                continue
+
+            # stop if q is pressed (opencv)
+            if cv2.waitKey(5) & 0xFF == ord("q"):
+                break
+
+            # quit the game
+            if any(
+                [event.type == pg.KEYDOWN and event.key == pg.K_q for event in pg.event.get()],
+            ):
+                break
+
+            # detect keypoints on frame
+            self.detect_keypoints()
+
+            # draw keypoints on top of fram
+            self.draw_keypoints()
+
+            # draw avatar
+            self.draw_avatar()
+
+    def detect_keypoints(self) -> None:
+        with self.mp_face_mesh.FaceMesh(
+            max_num_faces=1,
+            refine_landmarks=True,
+            min_detection_confidence=0.5,
+            min_tracking_confidence=0.5,
+        ) as face_mesh:
+
+            # perf, mark image as not writeable to pass by reference
+            self.frame.flags.writeable = False
+
+            # convert the BGR image to RGB before processing
+            self.frame = cv2.cvtColor(self.frame, cv2.COLOR_BGR2RGB)
+
+            # process the image to detect keypoints
+            self.results = face_mesh.process(self.frame)
+
+            # re-enable writeable flag
+            self.frame.flags.writeable = True
+
+            # convert the image back to BGR format
+            self.frame = cv2.cvtColor(self.frame, cv2.COLOR_RGB2BGR)
+
+    def draw_keypoints(self) -> None:
+        # draw the face mesh annotations on the image.
+        if self.results.multi_face_landmarks:
+            for face_landmarks in self.results.multi_face_landmarks:
+                self.mp_drawing.draw_landmarks(
+                    image=self.frame,
+                    landmark_list=face_landmarks,
+                    connections=self.mp_face_mesh.FACEMESH_TESSELATION,
+                    landmark_drawing_spec=None,
+                    connection_drawing_spec=self.mp_drawing_styles.get_default_face_mesh_tesselation_style(),
+                )
+                self.mp_drawing.draw_landmarks(
+                    image=self.frame,
+                    landmark_list=face_landmarks,
+                    connections=self.mp_face_mesh.FACEMESH_CONTOURS,
+                    landmark_drawing_spec=None,
+                    connection_drawing_spec=self.mp_drawing_styles.get_default_face_mesh_contours_style(),
+                )
+                self.mp_drawing.draw_landmarks(
+                    image=self.frame,
+                    landmark_list=face_landmarks,
+                    connections=self.mp_face_mesh.FACEMESH_IRISES,
+                    landmark_drawing_spec=None,
+                    connection_drawing_spec=self.mp_drawing_styles.get_default_face_mesh_iris_connections_style(),
+                )
+
+        # flip the image horizontally for a selfie-view display
+        cv2.imshow("MediaPipe Face Mesh", cv2.flip(self.frame, 1))
+
+    def draw_avatar(self) -> None:
+        self.screen.fill(pg.Color("green"))
+
+        for part in self.body_parts.values():
+            part.draw(self.screen)
+
+        pg.display.flip()

src/main.py

@@ -1,67 +1,20 @@
 import logging
 
 import cv2
-import mediapipe as mp
+
+from environment import Environment
 
 
 def main() -> None:
     """Main function."""
-    mp_drawing = mp.solutions.drawing_utils  # type: ignore
-    mp_drawing_styles = mp.solutions.drawing_styles  # type: ignore
-    mp_face_mesh = mp.solutions.face_mesh  # type: ignore
-
     # open webcam
     cap = cv2.VideoCapture(0)
 
-    with mp_face_mesh.FaceMesh(
+    # create env
-        max_num_faces=2, refine_landmarks=True, min_detection_confidence=0.5, min_tracking_confidence=0.5
+    env = Environment(cap)
-    ) as face_mesh:
 
-        while cap.isOpened():
+    # start env
-
+    env.start()
-            # read webcam
-            success, image = cap.read()
-            if not success:
-                print("Ignoring empty camera frame.")
-                # If loading a video, use 'break' instead of 'continue'
-                continue
-
-            # to improve performance, optionally mark the image as not writeable to pass by reference.
-            image.flags.writeable = False
-            image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-            results = face_mesh.process(image)
-
-            # draw the face mesh annotations on the image.
-            image.flags.writeable = True
-            image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
-            if results.multi_face_landmarks:
-                for face_landmarks in results.multi_face_landmarks:
-                    mp_drawing.draw_landmarks(
-                        image=image,
-                        landmark_list=face_landmarks,
-                        connections=mp_face_mesh.FACEMESH_TESSELATION,
-                        landmark_drawing_spec=None,
-                        connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_tesselation_style(),
-                    )
-                    mp_drawing.draw_landmarks(
-                        image=image,
-                        landmark_list=face_landmarks,
-                        connections=mp_face_mesh.FACEMESH_CONTOURS,
-                        landmark_drawing_spec=None,
-                        connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_contours_style(),
-                    )
-                    mp_drawing.draw_landmarks(
-                        image=image,
-                        landmark_list=face_landmarks,
-                        connections=mp_face_mesh.FACEMESH_IRISES,
-                        landmark_drawing_spec=None,
-                        connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_iris_connections_style(),
-                    )
-
-            # flip the image horizontally for a selfie-view display.
-            cv2.imshow("MediaPipe Face Mesh", cv2.flip(image, 1))
-            if cv2.waitKey(5) & 0xFF == 27:
-                break
 
     # close webcam
     cap.release()