overlay webcam frame in the preview scripts

preview_image.py

@@ -4,9 +4,10 @@
 
 from src.svg.model import Model
 from src.tracking.tracking import Tracking
+from src.utils import overlay_webcam
 
 if __name__ == "__main__":
-    with open("models/normal.svg", "r") as model_file:
+    with open("models/face.svg", "r") as model_file:
         tracking = Tracking()
         model = Model(model_file.read())
         tracking.set_model(model)
@@ -26,8 +27,10 @@
         image_bytes = resvg_python.svg_to_png(model.tostring())
         image_decoded = cv2.imdecode(np.array(bytearray(image_bytes)), cv2.IMREAD_COLOR)
 
+        final_image = overlay_webcam(frame, image_decoded)
+
         while True:
-            cv2.imshow("rein", image_decoded)
+            cv2.imshow("rein", final_image)
 
             if cv2.waitKey(1) & 0xFF == ord("q"):
                 cv2.destroyAllWindows()

preview_webcam.py

@@ -4,15 +4,15 @@
 
 from src.svg.model import Model
 from src.tracking.tracking import Tracking
+from src.utils import overlay_webcam
 
 if __name__ == "__main__":
-    tracking = Tracking()
-
-    vid = cv2.VideoCapture(0)
-
     with open("models/face.svg", "r") as model_file:
+        tracking = Tracking()
+        vid = cv2.VideoCapture(0)
         model = Model(model_file.read())
         tracking.set_model(model)
+
         while True:
             ret, frame = vid.read()
 
@@ -25,7 +25,9 @@
                 np.array(bytearray(image_bytes)), cv2.IMREAD_COLOR
             )
 
-            cv2.imshow("rein", image_decoded)
+            final_image = overlay_webcam(frame, image_decoded)
+
+            cv2.imshow("rein", final_image)
 
             if cv2.waitKey(1) & 0xFF == ord("q"):
                 vid.release()

src/tracking/tracking.py

@@ -26,11 +26,8 @@ def _origin(bbox, px, py):
 class Tracking:
     def __init__(self):
         options = FaceLandmarkerOptions(
-            base_options=BaseOptions(
-                model_asset_path="./face_landmarker.task", delegate="CPU"
-            ),
+            base_options=BaseOptions(model_asset_path="./face_landmarker.task"),
             output_face_blendshapes=True,
-            output_facial_transformation_matrixes=True,
             num_faces=1,
             running_mode=VisionRunningMode.LIVE_STREAM,
             result_callback=self.__process_callback__,
@@ -157,16 +154,8 @@ def _get(indices):
         )
 
     def __get_mouth_size__(self):
-        # x0, x1 = self._getn_face([61, 291])
-        # y0, y1 = self._getn_face([0, 17])
-
-        # w = x1[0] - x0[0]
-        # h = y1[1] - y0[1]
-        # print((w, h))
         w = 1.0 - self.__face_blendshape["mouthPucker"]
         h = self.__face_blendshape["jawOpen"] / 2
-
-        print((w, h))
         return self.__filter__("mouth-0", w), self.__filter__("mouth-1", h)
 
     def __get_iris_diff__(self):

src/utils.py

@@ -0,0 +1,33 @@
+import cv2
+import numpy as np
+
+
+def resize_image(image: np.ndarray, width=240):
+    if image.shape[1] == width:
+        return image
+
+    aspect_ratio = float(image.shape[0]) / float(image.shape[1])
+
+    height = round(width * aspect_ratio)
+
+    resized_image = cv2.resize(image, (width, height))
+    # brightened_image = cv2.convertScaleAbs(
+    #     resized_image, alpha=1, beta=brightness
+    # )
+    # return brightened_image
+    return resized_image
+
+
+def overlay_webcam(webcam_image, output_image, x=5, y=5):
+    webcam_image = resize_image(webcam_image)
+    # if img.ndim == 3 and img.shape[2] == 4:
+    #     img = img[..., :3]
+    start_x = x
+    start_y = y
+
+    output_image[
+        start_y : start_y + webcam_image.shape[0],
+        start_x : start_x + webcam_image.shape[1],
+    ] = webcam_image
+
+    return output_image