Create app.py

app.py

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+import torch
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from gtts import gTTS
+import tempfile
+import gradio as gr
+
+# Load the image captioning model
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+
+def generate_description(image):
+    """Generates a textual description of the given image using a pre-trained BLIP model."""
+    inputs = processor(image, return_tensors="pt").to(model.device)
+    output = model.generate(**inputs)
+    description = processor.decode(output[0], skip_special_tokens=True)
+    return description
+
+def text_to_speech(text):
+    """Converts text to speech using gTTS and returns the audio file path."""
+    tts = gTTS(text=text, lang='en')
+    temp_audio = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
+    tts.save(temp_audio.name)
+    return temp_audio.name
+
+def process_image(image):
+    """Processes the uploaded image to generate description and return audio file."""
+    description = generate_description(image)
+    return description
+
+def get_audio(description):
+    """Generates the audio file for the given description."""
+    return text_to_speech(description)
+
+# Build Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Description and Audio Transcript App")
+    gr.Markdown("Upload an image to get an AI-generated description. Click the button to hear the description.")
+    
+    with gr.Row():
+        image_input = gr.Image(type="pil")
+        text_output = gr.Textbox(label="Generated Description")
+    
+    generate_btn = gr.Button("Generate Description")
+    audio_btn = gr.Button("Click here for an audio transcript")
+    audio_output = gr.Audio()
+    
+    generate_btn.click(process_image, inputs=[image_input], outputs=[text_output])
+    audio_btn.click(get_audio, inputs=[text_output], outputs=[audio_output])
+    
+# Launch the Gradio app
+demo.launch()