Nepjune commited on
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17646ed
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1 Parent(s): dedb4e9

Update app.py

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Files changed (1) hide show
  1. app.py +9 -16
app.py CHANGED
@@ -1,29 +1,22 @@
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  import gradio as gr
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  from transformers import BlipProcessor, BlipForConditionalGeneration
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- from gtts import gTTS
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- import IPython.display as ipd
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  model_id = "dblasko/blip-dalle3-img2prompt"
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  model = BlipForConditionalGeneration.from_pretrained(model_id)
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  processor = BlipProcessor.from_pretrained(model_id)
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  def generate_caption(image):
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- inputs = processor(images=image, return_tensors="pt")
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- pixel_values = inputs.pixel_values
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- generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
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- generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True, temperature=0.8, top_k=40, top_p=0.9)[0]
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- # Convert text to speech and save as audio file
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- tts = gTTS(text=generated_caption, lang='en')
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- tts.save("generated_audio.mp3")
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- return generated_caption, "generated_audio.mp3"
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- def play_audio(audio_path):
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- # Display an audio player
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- return ipd.Audio(audio_path)
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- # Create a Gradio interface with an image input, a textbox output, and an audio player
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- demo = gr.Interface(fn=generate_caption, inputs=gr.Image(), outputs=[gr.Textbox(label="Generated caption"), gr.Audio(player=True, label="Play Audio")])
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- demo.launch()
 
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  import gradio as gr
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  from transformers import BlipProcessor, BlipForConditionalGeneration
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+
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+
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  model_id = "dblasko/blip-dalle3-img2prompt"
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  model = BlipForConditionalGeneration.from_pretrained(model_id)
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  processor = BlipProcessor.from_pretrained(model_id)
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  def generate_caption(image):
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+ inputs = processor(images=image, return_tensors="pt")
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+ pixel_values = inputs.pixel_values
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+ generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
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+ generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True, temperature=0.8, top_k=40, top_p=0.9)[0]
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+ return generated_caption
 
 
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+ # Create a Gradio interface with an image input and a textbox output
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+ demo = gr.Interface(fn=generate_caption, inputs=gr.Image(), outputs=gr.Textbox(label="Generated caption"))