hey, it works

facematcher.py

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+#!/usr/bin/env python3
+import cv2
+import numpy as np
+import face_recognition
+import os
+import sys
+import time
+
+def match(path, cap):
+    face = face_recognition.load_image_file(path)
+    faceencs = face_recognition.face_encodings(face)
+    if len(faceencs) == 0:
+        print("Oh noes, bad face!")
+        exit(1)
+    faceenc = faceencs[0]
+
+    matching = False
+
+    while not matching:
+        ret, frame = cap.read()
+        if cv2.mean(frame)[0] < 30:
+            continue
+
+        scale = 0.25
+        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2RGB)
+        small_rgb_frame = cv2.resize(rgb_frame, (0, 0), fx=scale, fy=scale)
+
+        framelocs = face_recognition.face_locations(small_rgb_frame)
+        frameencs = face_recognition.face_encodings(small_rgb_frame, framelocs)
+
+        # Loop through each face in this frame of video
+        for (top, right, bottom, left), frameenc in zip(framelocs, frameencs):
+            # See if the face is a match for the known face(s)
+            dist = face_recognition.face_distance([faceenc], frameenc)[0]
+            print("Distance: "+str(dist))
+
+            cv2.rectangle(
+                rgb_frame,
+                (int(left / scale), int(top / scale)),
+                (int(right / scale), int(bottom / scale)),
+                (0, 0, 255), 2)
+
+            # If a match was found in known_face_encodings, just use the first one.
+            if dist <= 0.35:
+                matching = True
+
+        cv2.imshow("frame", rgb_frame)
+
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    # When everything done, release the capture
+    cap.release()
+    cv2.destroyAllWindows()
+
+    if matching:
+        print("Matches")
+        exit(0)
+    else:
+        exit(1)
+
+def record(path, cap):
+    def draw_face_rec(name, frame):
+        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2RGB)
+        framelocs = face_recognition.face_locations(rgb_frame)
+        frameencs = face_recognition.face_encodings(rgb_frame, framelocs)
+        for (top, right, bottom, left), frameenc in zip(framelocs, frameencs):
+            cv2.rectangle(rgb_frame, (left, top), (right, bottom), (0, 0, 255), 2)
+
+        cv2.imshow(name, rgb_frame)
+
+    while True:
+        ret, frame = cap.read()
+        if cv2.mean(frame)[0] < 30:
+            continue
+
+        cv2.imshow("frame", frame)
+
+        key = cv2.waitKey(1) & 0xFF
+        if key == ord('q'):
+            break
+        elif key == ord('\r'):
+            cv2.imshow("frame", frame)
+            cv2.waitKey(1)
+            draw_face_rec("frame", frame)
+            while True:
+                key = cv2.waitKey(0) & 0xFF
+                if key == ord('\r'):
+                    cv2.imwrite(path, frame)
+                    return
+                elif key == 27: # esc
+                    break
+
+
+def usage(argv0):
+    print("Usage: "+argv0+" match <path> [cam ID]")
+    print("       "+argv0+" record <path> [cam ID]")
+
+if len(sys.argv) < 2:
+    usage(sys.argv[0])
+    exit(1)
+
+if sys.argv[1] == "match":
+    if len(sys.argv) == 3:
+        capid = 2
+    elif len(sys.argv) == 4:
+        capid = int(sys.argv[3])
+    else:
+        usage(sys.argv[0])
+        exit(1)
+    match(sys.argv[2], cv2.VideoCapture(capid))
+elif sys.argv[1] == "record":
+    if len(sys.argv) == 3:
+        capid = 2
+    elif len(sys.argv) == 4:
+        capid = int(sys.argv[3])
+    else:
+        usage(sys.argv[0])
+        exit(1)
+    record(sys.argv[2], cv2.VideoCapture(capid))
+else:
+    usage(sys.argv[0])
+    exit(1)