import tkinter as tk
from tkinter import *
import cv2
from PIL import Image, ImageTk
import os
import numpy as np

import numpy as np
import cv2
from tensorflow.keras.models import Sequential 
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D
from tensorflow.keras.optimizers import Adam
from keras.layers import MaxPooling2D
from keras.preprocessing.image import ImageDataGenerator

emotion_model = Sequential()

emotion_model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(48,48,1)))
emotion_model.add(Conv2D(64, kernel_size=(3, 3), activation='relu'))
emotion_model.add(MaxPooling2D(pool_size=(2, 2)))
emotion_model.add(Dropout(0.25))

emotion_model.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))
emotion_model.add(MaxPooling2D(pool_size=(2, 2)))
emotion_model.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))
emotion_model.add(MaxPooling2D(pool_size=(2, 2)))
emotion_model.add(Dropout(0.25))

emotion_model.add(Flatten())
emotion_model.add(Dense(1024, activation='relu'))
emotion_model.add(Dropout(0.5))
emotion_model.add(Dense(7, activation='softmax'))
emotion_model.load_weights('emotion_model.h5')

cv2.ocl.setUseOpenCL(False)

emotion_dict = {0: "   Angry   ", 1: "Disgusted", 2: "  Fearful  ", 3: "   Happy   ", 4: "  Neutral  ", 5: "    Sad    ", 6: "Surprised"}


emoji_dist={0:"./emojis/angry.png",1:"./emojis/disgusted.png",2:"./emojis/fearful.png",3:"./emojis/happy.png",4:"./emojis/neutral.png",5:"./emojis/sad.png",6:"./emojis/surpriced.png"}

global last_frame1                                    
last_frame1 = np.zeros((480, 640, 3), dtype=np.uint8)
global cap1
global show_text
show_text=[3]
def show_vid():
    global cap1
    cap1 = cv2.VideoCapture(0)                                 
    if not cap1.isOpened():                             
        print("cant open the camera1")
    flag1, frame1 = cap1.read()
    frame1 = cv2.resize(frame1,(600,500))
    bounding_box = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
    gray_frame = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
    num_faces = bounding_box.detectMultiScale(gray_frame,scaleFactor=1.3, minNeighbors=5)
    for (x, y, w, h) in num_faces:
        cv2.rectangle(frame1, (x, y-50), (x+w, y+h+10), (255, 0, 0), 2)
        roi_gray_frame = gray_frame[y:y + h, x:x + w]
        cropped_img = np.expand_dims(np.expand_dims(cv2.resize(roi_gray_frame, (48, 48)), -1), 0)
        prediction = emotion_model.predict(cropped_img)
        maxindex = int(np.argmax(prediction))
        cv2.putText(frame1, emotion_dict[maxindex], (x+20, y-60), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
        show_text[0]=maxindex
    if flag1 is None:
        print ("Major error!")
    elif flag1:
        global last_frame1
        last_frame1 = frame1.copy()
        pic = cv2.cvtColor(last_frame1, cv2.COLOR_BGR2RGB)     
        img = Image.fromarray(pic)
        imgtk = ImageTk.PhotoImage(image=img)
        lmain.imgtk = imgtk
        lmain.configure(image=imgtk)
        lmain.after(10, show_vid)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        exit()


def show_vid2():
    frame2=cv2.imread(emoji_dist[show_text[0]])
    pic2=cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)
    img2=Image.fromarray(frame2)
    imgtk2=ImageTk.PhotoImage(image=img2)
    lmain2.imgtk2=imgtk2
    lmain3.configure(text=emotion_dict[show_text[0]],font=('arial',45,'bold'))
    
    lmain2.configure(image=imgtk2)
    lmain2.after(10, show_vid2)

if __name__ == '__main__':
    root=tk.Tk()   
    img = ImageTk.PhotoImage(Image.open("logo.png"))
    heading = Label(root,image=img,bg='black')
    
    heading.pack() 
    heading2=Label(root,text="Photo to Emoji",pady=20, font=('arial',45,'bold'),bg='black',fg='#CDCDCD')                                 
    
    heading2.pack()
    lmain = tk.Label(master=root,padx=50,bd=10)
    lmain2 = tk.Label(master=root,bd=10)

    lmain3=tk.Label(master=root,bd=10,fg="#CDCDCD",bg='black')
    lmain.pack(side=LEFT)
    lmain.place(x=50,y=250)
    lmain3.pack()
    lmain3.place(x=960,y=250)
    lmain2.pack(side=RIGHT)
    lmain2.place(x=900,y=350)
    root.title("Photo To Emoji")            
    root.geometry("1400x900+100+10") 
    root['bg']='black'
    exitbutton = Button(root, text='Quit',fg="red",command=root.destroy,font=('arial',25,'bold')).pack(side = BOTTOM)
    show_vid()
    show_vid2()
    root.mainloop()