Create app.py

app.py

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+import gradio as gr
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from PIL import Image
+import torch
+
+# Load model and processor
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+
+# Function to generate captions
+def generate_caption(image):
+    image = Image.open(image).convert("RGB")
+    inputs = processor(image, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    caption = processor.decode(outputs[0], skip_special_tokens=True)
+    return caption
+
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=generate_caption,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="AI Image Caption Generator",
+    description="Upload an image and get an AI-generated caption.",
+)
+
+# Run app
+iface.launch()