from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
import numpy as np
#import time
import tkinter as tk
import cv2
from PIL import ImageTk, Image


def detect_and_predict_mask(frame, faceNet, maskNet):
	(h, w) = frame.shape[:2]
	blob = cv2.dnn.blobFromImage(frame, 1.0, (300, 300),
		(104.0, 177.0, 123.0))

	faceNet.setInput(blob)
	detections = faceNet.forward()

	faces = []
	locs = []
	preds = []

	for i in range(0, detections.shape[2]):
		confidence = detections[0, 0, i, 2]

		if confidence > 0.5:
			box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
			(startX, startY, endX, endY) = box.astype("int")

			(startX, startY) = (max(0, startX), max(0, startY))
			(endX, endY) = (min(w - 1, endX), min(h - 1, endY))

			face = frame[startY:endY, startX:endX]
			face = cv2.cvtColor(face, cv2.COLOR_BGR2RGB)
			face = cv2.resize(face, (224, 224))
			face = img_to_array(face)
			face = preprocess_input(face)

			faces.append(face)
			locs.append((startX, startY, endX, endY))

	if len(faces) > 0:
		faces = np.array(faces, dtype="float32")
		preds = maskNet.predict(faces, batch_size=32)

	return (locs, preds)


faceNet = cv2.dnn.readNet('NN/deploy.prototxt', 'NN/face_neuralnet.caffemodel')

maskNet = load_model('NN/mask_neuralnet.model')

window = tk.Tk()
window.wm_title("FAMOS - Face Mask Monitoring System")

app = tk.Frame(window, bg="white")
app.grid()
lmain = tk.Label(app)
lmain.grid()

cap = cv2.VideoCapture(0)

def video_stream():
	#time.sleep(1.0)
	_,frame = cap.read()

	(locs, preds) = detect_and_predict_mask(frame, faceNet, maskNet)

	for (box, pred) in zip(locs, preds):
		(startX, startY, endX, endY) = box
		(mask, withoutMask) = pred

		label = "Mask" if mask > withoutMask else "No Mask"
		color = (0, 255, 0) if label == "Mask" else (0, 0, 255)

		label = "{}: {:.2f}%".format(label, max(mask, withoutMask) * 100)

		cv2.putText(frame, label, (startX, startY - 10),
			cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2)
		cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)

	
	cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
	img = Image.fromarray(cv2image)
	imgtk = ImageTk.PhotoImage(image=img)
	lmain.imgtk = imgtk
	lmain.configure(image=imgtk)
	lmain.after(1, video_stream)

video_stream()
window.mainloop()
