chore: created vision package

- fixed dynamic version

cereja_ai/__init__.py

@@ -1,5 +1,4 @@
-# TODO: fix dynamic version for toml.
-# from cereja.utils import get_version_pep440_compliant
+from cereja.utils import get_version_pep440_compliant
 
-VERSION = "0.0.1.final.0"
-__version__ = VERSION[:5]
+VERSION = "0.0.2.final.0"
+__version__ = get_version_pep440_compliant(VERSION)

cereja_ai/vision/_base.py

@@ -0,0 +1,3 @@
+class HumanAction:
+    def __int__(self):
+        pass

cereja_ai/vision/utils.py

@@ -0,0 +1,141 @@
+import calango
+import numpy as np
+import cv2
+
+__all__ = ['VideoKeypointsExtractor']
+MAPED_FACE_LANDMARKS = [398, 384, 385, 386, 387, 388, 466, 362, 382, 381, 380, 374, 373, 390, 249]  # left eye
+MAPED_FACE_LANDMARKS += [246, 7, 161, 160, 159, 158, 157, 173, 163, 144, 145, 153, 154, 155]  # right eye
+
+
+def _mediapipe_generator(draw=False):
+    import mediapipe as mp
+    import cv2
+    mp_drawing = mp.solutions.drawing_utils
+    mp_drawing_styles = mp.solutions.drawing_styles
+    mp_holistic = mp.solutions.holistic
+    with mp_holistic.Holistic(
+            min_detection_confidence=0.5,
+            min_tracking_confidence=0.5) as holistic:
+        while True:
+            image = yield
+            if image is None:
+                break
+            image.flags.writeable = False
+            image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+            results = holistic.process(image)
+            # Draw landmark annotation on the image.
+            image.flags.writeable = True
+            image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+
+            if results.pose_landmarks:
+                pose = [(i.x, i.y, i.z) for i in results.pose_landmarks.landmark]
+                # if draw:
+                #     mp_drawing.draw_landmarks(
+                #             image,
+                #             results.pose_landmarks,
+                #             mp_holistic.POSE_CONNECTIONS)
+            else:
+                pose = [[0.0, 0.0, 0.0]] * 33
+
+            if results.left_hand_landmarks:
+                left_hand = [(i.x, i.y, i.z) for i in results.left_hand_landmarks.landmark]
+                if draw:
+                    mp_drawing.draw_landmarks(
+                            image,
+                            results.left_hand_landmarks,
+                            mp_holistic.HAND_CONNECTIONS,
+                            landmark_drawing_spec=None,
+                            connection_drawing_spec=mp_drawing_styles
+                            .get_default_hand_connections_style())
+            else:
+                left_hand = [[0.0, 0.0, 0.0]] * 21
+
+            if results.right_hand_landmarks:
+                right_hand = [(i.x, i.y, i.z) for i in results.right_hand_landmarks.landmark]
+                if draw:
+                    mp_drawing.draw_landmarks(
+                            image,
+                            results.right_hand_landmarks,
+                            mp_holistic.HAND_CONNECTIONS,
+                            landmark_drawing_spec=None,
+                            connection_drawing_spec=mp_drawing_styles
+                            .get_default_hand_connections_style())
+            else:
+                right_hand = [[0.0, 0.0, 0.0]] * 21
+
+            if results.face_landmarks:
+                face_data = [[i.x, i.y, i.z] for indx, i in enumerate(results.face_landmarks.landmark) if
+                             indx in MAPED_FACE_LANDMARKS]
+                if draw:
+                    mp_drawing.draw_landmarks(
+                            image,
+                            results.face_landmarks,
+                            mp_holistic.FACEMESH_CONTOURS,
+                            landmark_drawing_spec=None,
+                            connection_drawing_spec=mp_drawing_styles
+                            .get_default_face_mesh_contours_style())
+            else:
+                face_data = [[0.0, 0.0, 0.0]] * 14
+            yield image, [face_data, pose, left_hand, right_hand]
+
+
+class VideoKeypointsExtractor:
+    def __init__(self, *args, draw=False):
+        self._stopped = False
+        self._extractor = _mediapipe_generator(draw=draw)
+        self._video = calango.Video(*args, fps=None)
+
+    @property
+    def is_extracting(self):
+        return self._video.is_opened
+
+    def _extract_all(self, show=False, text_bottom=None) -> np.ndarray:
+        self._stopped = False
+        # keypoints = []
+        try:
+            while self._video.is_opened:
+                next(self._extractor)
+                image = self._video.next_frame
+                if image is None:
+                    self._extractor.send(None)
+                    break
+                image, kpts = self._extractor.send(image.flip())
+
+                if show:
+                    cv2.imshow("Video", image if text_bottom is None else calango.Image(image).write_text(text_bottom))
+                    if self._video.is_break_view:
+                        self._video.stop()
+                # keypoints.append(kpts)
+                yield kpts
+        except StopIteration:
+            self._stop()
+        except Exception as err:
+            self._stop()
+            raise Exception(f"error during capture: {err}")
+        self._stop()
+        # return np.array(keypoints)
+
+    def extract_all(self, show=False):
+        face_data = []
+        pose_data = []
+        hand_l_data = []
+        hand_r_data = []
+        for face, pose, hl, hr in self._extract_all(show=show):
+            face_data.append(face)
+            pose_data.append(pose)
+            hand_l_data.append(hl)
+            hand_r_data.append(hr)
+        return face_data, pose_data, hand_l_data, hand_r_data
+
+    def _stop(self):
+        if not self._stopped:
+            try:
+                next(self._extractor)
+                self._extractor.send(None)
+            except:
+                pass
+            cv2.destroyAllWindows()
+            self._stopped = True
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self._stop()

pyproject.toml

@@ -1,5 +1,5 @@
 [build-system]
-requires = ["setuptools>=61.0"]
+requires = ["setuptools>=61.0", "cereja==1.8.4"]
 build-backend = "setuptools.build_meta"
 
 [tool.setuptools]

requirements.txt

@@ -1,5 +1,6 @@
 cereja==1.8.4
 tensorflow
-calango~=2.2.5
+numpy
+calango~=2.2.6
 mediapipe
 opencv-python~=4.7.0.72