Update app.py

app.py

@@ -1,34 +1,6 @@
 # Importing the requirements
 import gradio as gr
-from transformers import BlipProcessor, BlipForQuestionAnswering
-
-# Load the model and processor
-processor = BlipProcessor.from_pretrained("Salesforce/blip-vqa-base")
-model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base")
-
-
-# Function to answer the question
-def answer_question(image, text):
-    """
-    Generates an answer to a given question based on the provided image and text.
-
-    Args:
-        image (str): The path to the image file.
-        text (str): The question text.
-
-    Returns:
-        str: The generated answer to the question.
-    """
-
-    # Process the inputs and generate the ids
-    inputs = processor(images=image, text=text, return_tensors="pt")
-    generated_ids = model.generate(**inputs, max_length=50)
-
-    # Decode the generated IDs
-    generated_answer = processor.batch_decode(generated_ids, skip_special_tokens=True)
-
-    # Return the generated answer
-    return generated_answer[0]
+from model import answer_question
 
 
 # Image and text inputs for the interface
@@ -40,14 +12,14 @@ answer = gr.Textbox(label="Predicted answer")
 
 # Examples for the interface
 examples = [
-    ["cat.jpg", "How many cats are there?"],
-    ["dog.jpg", "What color is the dog?"],
-    ["bird.jpg", "What is the bird doing?"],
+    ["images/cat.jpg", "How many cats are there?"],
+    ["images/dog.jpg", "What color is the dog?"],
+    ["images/bird.jpg", "What is the bird doing?"],
 ]
 
 # Title, description, and article for the interface
 title = "Visual Question Answering"
-description = "Gradio Demo for the Salesforce BLIP VQA model. This model can answer questions about images in natural language. To use it, upload your photo, type a question, click 'submit', or click one of the examples to load them. Read more at the links below."
+description = "Gradio Demo for the Salesforce BLIP VQA model. This model can answer questions about images in natural language. To use it, simply upload your image and type a question and click 'submit', or click one of the examples to load them. Read more at the links below."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2201.12086' target='_blank'>BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation</a> | <a href='https://huggingface.co/Salesforce/blip-vqa-base' target='_blank'>Model Page</a></p>"