Detect, Recognize, Crop Faces from Video and Save Them as Images

face_recognizer.py

#----------------------------------------------
#--- Author         : Ahmet Ozlu
#--- Mail           : ahmetozlu93@gmail.com
#--- Date           : 21st September 2017
#----------------------------------------------

import face_recognition
import cv2
import os
import create_csv

# Open the input movie file
input_movie = cv2.VideoCapture("tbbt.mp4")
length = int(input_movie.get(cv2.CAP_PROP_FRAME_COUNT))

# Load some sample pictures and learn how to recognize them.
lmm_image = face_recognition.load_image_file("sheldon.jpg")
lmm_face_encoding = face_recognition.face_encodings(lmm_image)[0]

al_image = face_recognition.load_image_file("penny.jpg")
al_face_encoding = face_recognition.face_encodings(al_image)[0]

known_faces = [
    lmm_face_encoding,
    al_face_encoding
]

# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
frame_number = 0

current_path = os.getcwd()

counter = 0
counter1 = 0

while True:
    # Grab a single frame of video
    ret, frame = input_movie.read()
    frame_number += 1

    # Quit when the input video file ends
    if not ret:
        break

    # Find all the faces and face encodings in the current frame of video
    face_locations = face_recognition.face_locations(frame)
    face_encodings = face_recognition.face_encodings(frame, face_locations)

    face_names = []
    for face_encoding in face_encodings:
        # See if the face is a match for the known face(s)
        match = face_recognition.compare_faces(known_faces, face_encoding, tolerance=0.50)

        # If you had more than 2 faces, you could make this logic a lot prettier
        # but I kept it simple for the demo
        name = None
        if match[0]:
            name = "Sheldon Cooper"
        elif match[1]:
            name = "Penny"

        face_names.append(name)

    # Label the results
    for (top, right, bottom, left), name in zip(face_locations, face_names):
        if not name:
            continue

        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

	crop_img = frame[top:bottom, left:right]
	if(name == "Sheldon Cooper"):
	    cv2.imwrite(current_path + "/face_database/Sheldon/" + "sheldon"+str(counter)+".png",crop_img)
	    counter = counter + 1
	elif(name == "Penny"):
	    cv2.imwrite(current_path + "/face_database/Penny/" + "penny"+str(counter1)+".png",crop_img)
	    counter1 = counter1 + 1

    # Write the resulting image to the output video file
    print("Writing frame {} / {}".format(frame_number, length))

# All done!
input_movie.release()
cv2.destroyAllWindows()
create_csv.CreateCsv(current_path + "/face_database/")

Hey , I want to crop human detected frame from live video I have already done human detection
https://github.com/ambakick/Person-Detection-and-Tracking
This is link of human detection...
but don't know how to crop detected frames of video and save it in video format...
please suggest me something...