Update app.py

app.py

@@ -2,15 +2,33 @@ import os
 import gradio as gr
 from transformers import pipeline
 
-pipe = pipeline("image-to-text",
-                model="./models/Salesforce/blip-image-captioning-base")
+# Initialize the pipeline with the image-to-text model
+model_path = "Salesforce/blip-image-captioning-base"
+if not os.path.exists(model_path):
+    raise FileNotFoundError(f"Model path {model_path} does not exist. Please provide a valid path.")
+
+# Initialize the image-to-text pipeline with the specified model
+pipe = pipeline("image-to-text", model=model_path)
 
 def launch(input):
+    """
+    Function to generate image caption.
+
+    Args:
+    input (PIL.Image): Input image for captioning.
+
+    Returns:
+    str: Generated caption for the input image.
+    """
     out = pipe(input)
     return out[0]['generated_text']
 
-iface = gr.Interface(launch,
-                     inputs=gr.Image(type='pil'),
-                     outputs="text")
+# Create a Gradio interface for the image-to-text pipeline
+iface = gr.Interface(
+    fn=launch,             # Function to generate captions
+    inputs=gr.Image(type='pil'),  # Input type: Image (PIL format)
+    outputs="text"         # Output type: Text
+)
 
-iface.launch()
+# Launch the Gradio interface
+iface.launch()