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from flask import Flask, request, jsonify
from transformers import pipeline, BlipForConditionalGeneration, BlipProcessor
import torchaudio
from torchaudio.transforms import Resample
import torch
from torch.nn.utils.parametrizations import weight_norm
from io import BytesIO
from PIL import Image
from flask_cors import CORS
# ย้าย cache ไปที่ตำแหน่งที่ถูกต้อง
# utils.move_cache()
app = Flask(__name__)
CORS(app)
# Initialize TTS model from Hugging Face
tts_model_name = "suno/bark"
tts = pipeline(task="text-to-speech", model=tts_model_name)
# Initialize Blip model for image captioning
model_id = "dblasko/blip-dalle3-img2prompt"
blip_model = BlipForConditionalGeneration.from_pretrained(model_id)
blip_processor = BlipProcessor.from_pretrained(model_id)
def generate_caption(file):
# Generate caption from image using Blip model
inputs = blip_processor(files=file, return_tensors="pt")
pixel_values = inputs.pixel_values
generated_ids = blip_model.generate(pixel_values=pixel_values, max_length=50)
generated_caption = blip_processor.batch_decode(generated_ids, skip_special_tokens=True, temperature=0.8, top_k=40, top_p=0.9)[0]
# Use TTS model to convert generated caption to audio
audio_output = tts(generated_caption)
audio_path = "generated_audio_resampled.wav"
torchaudio.save(audio_path, torch.tensor(audio_output[0]), audio_output["sampling_rate"])
return generated_caption, audio_path
@app.route('/upload', methods=['POST'])
def upload_image():
if 'file' not in request.files:
return jsonify({'error': 'No image provided'}), 400
image_file = request.files['file']
generated_caption, audio_path = generate_caption(image_file)
return jsonify({'generated_caption': generated_caption, 'audio_url': audio_path}), 200
if __name__ == '__main__':
app.run(port=5000, debug=True)
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