File size: 3,032 Bytes
51ef5ad | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | 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() |