MVP Done.

Added face detection, text, smoothing of detected rectangle so it's not shaking. Refactoring needed

Author: dehobitto

Python/face_detector/main.py

@@ -1,30 +1,76 @@
-import numpy as np
 import cv2 as cv
-
+import sys
 
 def get_camera(camera_source_idx : int) -> cv.VideoCapture:
     cap = cv.VideoCapture(camera_source_idx)
 
     if not cap.isOpened():
         print("Cannot open camera")
-        exit()
+        sys.exit()
 
     return cap
 
+def process_frame(frame):
+    detect_faces(frame)
+    return frame
+
+TEXT_MARGIN = 5
+last_face = (0, 0)
+last_face_w, last_face_h = (100, 100)
+
+def smooth(last_pos, cur_pos, alpha=0.2, threshold=2):
+    dx = cur_pos[0] - last_pos[0]
+    dy = cur_pos[1] - last_pos[1]
+
+    if abs(dx) < threshold:
+        cur_pos = (last_pos[0], cur_pos[1])
+    if abs(dy) < threshold:
+        cur_pos = (cur_pos[0], last_pos[1])
+
+    x = int(alpha * cur_pos[0] + (1 - alpha) * last_pos[0])
+    y = int(alpha * cur_pos[1] + (1 - alpha) * last_pos[1])
+    return x, y
 
 
+def detect_faces(frame):
+    global last_face
+    global last_face_w, last_face_h
+    frame_gray = cv.cvtColor(src=frame, code=cv.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(image=frame_gray, scaleFactor=1.2, minNeighbors=7)
+
+    for (x, y, w, h) in faces:
+        x, y = smooth(last_face, (x,y))
+        w, h = smooth((last_face_w, last_face_h), (w, h))
+        frame = cv.rectangle(
+            img=frame,
+            pt1=(x, y), pt2=(x + w, y + h),
+            color=(255, 0, 0), thickness=2)
+        add_text(frame, "Face", (x + w + TEXT_MARGIN, y - TEXT_MARGIN), h / 200)
+        last_face = (x, y)
+        last_face_w, last_face_h = w, h
+
+def add_text(frame, text, point, font_scale = 1, font_face = cv.FONT_HERSHEY_DUPLEX, color = (255, 0, 0), thickness = 1):
+    cv.putText(frame, text, point, font_face, font_scale, color, thickness)
+    return frame
+
+# TODO: List all cameras let him choose
 def main():
-    #TODO: List all cameras let him choose
+    global face_cascade
+
+    face_cascade = cv.CascadeClassifier(cv.data.haarcascades + "haarcascade_frontalface_default.xml")
     cap = get_camera(0)
 
+    # Main loop
     while True:
         res, frame = cap.read()
+        frame = process_frame(frame)
 
         if not res:
             print("Cannot read frame")
             break
 
         cv.imshow('frame', frame)
+
         if cv.waitKey(1) & 0xFF == ord('q'):
             break