Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from PIL import Image
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+def generate_caption(image):
+    # Now directly using the PIL Image object
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    caption = processor.decode(outputs[0], skip_special_tokens=True)
+    return caption
+def caption_image(image):
+    """
+    Takes a PIL Image input and returns a caption.
+    """
+    try:
+        caption = generate_caption(image)
+        return caption
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+iface = gr.Interface(
+    fn=caption_image,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Image Captioning with BLIP",
+    description="Upload an image to generate a caption."
+)
+iface.launch()