Update app.py

app.py

@@ -1,22 +1,18 @@
 import gradio as gr
-from PIL import Image
 from transformers import pipeline
+from PIL import Image
 
 # Initialize the pipeline with the image captioning model
 caption_pipeline = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
 
 def generate_caption(image):
-    # Convert the PIL Image to the format expected by the model
-    image = Image.open(image).convert("RGB")
-    
-    # Use the pipeline to generate a caption
+    # The image is received as a PIL Image, so no need for conversion
     result = caption_pipeline(image)
     caption = result[0]["generated_text"]
-    
     return caption
 
 # Setup the Gradio interface
 interface = gr.Interface(fn=generate_caption,
-                         inputs=gr.inputs.Image(type="pil", label="Upload an Image"),
+                         inputs=gr.inputs.Image(label="Upload an Image", type="pil"),
                          outputs=gr.outputs.Textbox(label="Generated Caption"))
 interface.launch()