drone.py

import cv2
import time
from PIL import Image
import face_recognition
import os
import numpy as np
import sys
from config import ip_address
from config import number_of_times_to_upsample
from config import num_jitters
from config import tolerance

subjects = []
status = []
face_encoding_list = []

def colour_f(status1):
    if status1=="vip":
        return (0,255,0)
    if status1=="blacklisted":
        return (0,0,255)
    else :
        return (255,255,255)

def draw_rectangle2(img, rect,colour):
    (x, y, w, h) = rect
    cv2.rectangle(img, (x, y), (w, h), colour, 2)

def draw_text(img, text, x, y):
    cv2.putText(img, text, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)

def prepare_training_data(data_folder_path):
    global subjects
    global status

    dirs = os.listdir(data_folder_path)

    faces = []

    labels = []

    for dir_name in dirs:

        if not dir_name.startswith("s"):
            continue;

        label = int(dir_name.replace("s", ""))

        subject_dir_path = data_folder_path + "/" + dir_name

        subject_images_names = os.listdir(subject_dir_path)

        for image_name in subject_images_names:

            if image_name.startswith("."):
                continue;

            if image_name == "name.txt":
                name_path = subject_dir_path + "/" + image_name
                with open(name_path,'r+') as name:
                    content = name.read()
                    content = content.lower()
                    subjects.append(content)

            elif image_name == "status.txt":
                name_path = subject_dir_path + "/" + image_name
                with open(name_path,'r+') as name:
                    content = name.read()
                    content = content.lower()
                    status.append(content)

            else :
                image_path = subject_dir_path + "/" + image_name
                image = face_recognition.load_image_file(image_path)

                # make sure to resize on fixed amount
                # cv2.imshow("Training on image...", cv2.resize(image, (400, 500)))
                print("Faces Scanned: ", len(faces) + 1)
                cv2.waitKey(100)

                faces.append(image)
                labels.append(label)
    cv2.destroyAllWindows()
    cv2.waitKey(1)
    cv2.destroyAllWindows()

    return faces

faces = prepare_training_data("train-images")



def show_result(frame):
    global faces
    global subjects
    global status
    global face_encoding_list
    face_locations = face_recognition.face_locations(frame,number_of_times_to_upsample=number_of_times_to_upsample)
    try:
        for face in faces:
            face_encoding = face_recognition.face_encodings(face,num_jitters=num_jitters)[0]
            face_encoding_list.append(face_encoding)
    except IndexError:
        print("I wasn't able to locate any faces in at least one of the images. Check the image files. Aborting...")
        quit()
    print("I found {} face(s) in this photograph.".format(len(face_locations)))
    img = frame.copy()
    for face_location in face_locations:

        # Print the location of each face in this image
        top, right, bottom, left = face_location
        print("A face is located at pixel location Top: {}, Left: {}, Bottom: {}, Right: {}".format(top, left, bottom, right))

        # You can access the actual face itself like this:
        face_image = frame[top:bottom, left:right]
        face_encoding1 = face_recognition.face_encodings(face_image,num_jitters=num_jitters)
        if len(face_encoding1) > 0 :
            face_encoding = face_encoding1[0]
            results = face_recognition.compare_faces(face_encoding_list, face_encoding, tolerance = tolerance)
            if True in results:
                index1 = results.index(True)
                colour_2 = colour_f(status[index1])
                draw_rectangle2(img, (left,top,right,bottom),colour_2)
                draw_text(img,subjects[index1] , left, top-5)

                print(subjects[index1])
                print(status[index1])
            else :
                print("not found")
                draw_rectangle2(img, (left,top,right,bottom),(255,255,255))
                draw_text(img,"No Match" ,left, top-5)
        else:
            draw_rectangle2(img, (left,top,right,bottom),(255,255,255))
            draw_text(img,"Error 1" ,left, top-5)

    save(frame,"before")
    save(img,"after")
    cv2.imshow("face_detected",img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()



vid = cv2.VideoCapture()
vid.open(ip_address)

while True:
    check , frame = vid.read()
    cv2.imshow("face detect",frame)

    key = cv2.waitKey(1)
    if key == ord('q'):
        break
    if key == ord('c'):
        show_result(frame)


vid.release()
cv2.destroyAllWindows()