FER/sever.py

import socket
import os 
import torch 
from threading import Timer
import pyttsx3
import speech_recognition as sr
from detectfaces import fer
from models.PosterV2_7cls import pyramid_trans_expr2
from main import RecorderMeter1, RecorderMeter  # noqa: F401 
import time

script_dir = os.path.dirname(os.path.abspath(__file__))

# Construct the full path to the model file
model_path = os.path.join(script_dir,"models","checkpoints","raf-db-model_best.pth")

# Determine the available device for model execution
if torch.backends.mps.is_available():
    device = "mps"
elif torch.cuda.is_available():
    device = "cuda"
else:
    device = "cpu"

# Initialize the model with specified image size and number of classes
model = pyramid_trans_expr2(img_size=224, num_classes=7)

# Wrap the model with DataParallel for potential multi-GPU usage
model = torch.nn.DataParallel(model)

# Move the model to the chosen device
model = model.to(device)
fer(model_path=model_path, device=device, model=model)

s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind(('', 5001))
s.listen(5)
print("Bot is Running")

def handle_client(clientsocket):
    r = sr.Recognizer()
    m = sr.Microphone()

    try:
        while True:
            prompt = ''
            print("Speak now:")
            sent = False
            with m as source:
                audio = r.listen(source)

            try:
                prompt = r.recognize_google(audio)
                print("Tadbot Thinks you said:", prompt)
                sent = True
            except sr.UnknownValueError:
                print("Tadbot could not understand audio. Try Again")
            except sr.RequestError as e:
                print(f"Could not request results from Google Speech Recognition service: {e}")

            if sent:
                print("please Wait!")
                try:
                    clientsocket.send(bytes(prompt, 'utf-8'))
                    response = clientsocket.recv(1024).decode("utf-8")
                    engine = pyttsx3.init('espeak')
                    voices = engine.getProperty('voices')
                    engine.setProperty('voice', voices[26].id)
                    engine.setProperty('rate', 145)
                    engine.say(response)
                    engine.runAndWait()
                    print("TADBot:", response)
                except (socket.error, ConnectionResetError) as e:
                    print(f"Connection error: {e}")
                    break  # Exit loop if connection breaks
                time.sleep(60)  # Wait for 60 seconds before listening again

    finally:
        clientsocket.close()
        print("Connection Closed")


while True:
    try:
        clientsocket, address = s.accept()
        print(f"Accepted connection from {address}")
        handle_client(clientsocket) #Handle each client in a separate function
    except KeyboardInterrupt:
        print("Server shutting down...")
        break
    except Exception as e:
        print(f"An error occurred: {e}")

s.close()