app.py

import torch
import gradio as gr
from PIL  import Image
import scipy.io.wavfile as wavfile

# Use a pipeline as a high-level helper
from transformers import pipeline

# from phonemizer.backend.espeak.wrapper import EspeakWrapper

# _ESPEAK_LIBRARY = '/opt/homebrew/Cellar/espeak/1.48.04_1/lib/libespeak.1.1.48.dylib'  #use the Path to the library.
# EspeakWrapper.set_library(_ESPEAK_LIBRARY)

device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')

narrator = pipeline("text-to-speech", model="kakao-enterprise/vits-ljs")

# tts_model_path = "./Model/models--kakao-enterprise--vits-ljs/snapshots/3bcb8321394f671bd948ebf0d086d694dda95464"

# narrator = pipeline("text-to-speech", model=tts_model_path) 

# Load the pretrained weights
caption_image = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large", device=device)

# model_path = "./Model/models--Salesforce--blip-image-captioning-large/snapshots/2227ac38c9f16105cb0412e7cab4759978a8fd90"

# Load the pretrained weights
# caption_image = pipeline("image-to-text", model=model_path, device=device)

# define the function to generate audio from text
def generate_audio(text):

    # generate the narrated text
    narrated_text = narrator(text)

    # save the audio to WAV file
    wavfile.write("output.wav", rate=narrated_text["sampling_rate"],
                  data=narrated_text["audio"][0])
    
    # Return the path to the saved output WAV file
    return "output.wav"


def caption_my_image(pil_image):

    semantics = caption_image(pil_image)[0]["generated_text"]
    audio = generate_audio(semantics)

    return audio


gr.close_all()

demo = gr.Interface(fn=caption_my_image, 
                      inputs=[gr.Image(label="Select Image", type="pil")],
                      outputs=[gr.Audio(label="Generated Audio")],
                      title="@IT AI Enthusiast (https://www.youtube.com/@itaienthusiast/) - Project 8: Image Captioning with AI",
                      description="THIS APPLICATION WILL BE USED TO CAPTION IMAGES WITH THE HELP OF AI")

demo.launch()