Create ap.py

ap.py

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+import gradio as gr
+from PIL import Image
+from transformers.utils import logging
+from transformers import BlipForConditionalGeneration, AutoProcessor
+
+logging.set_verbosity_error()
+
+model = BlipForConditionalGeneration.from_pretrained("./models/Salesforce/blip-image-captioning-base")
+processor = AutoProcessor.from_pretrained("./models/Salesforce/blip-image-captioning-base")
+
+def caption_image(image):
+    inputs = processor(image, return_tensors="pt")
+    out = model.generate(**inputs)
+    caption = processor.decode(out[0], skip_special_tokens=True)
+    return caption
+
+image_input = gr.inputs.Image()
+caption_output = gr.outputs.Textbox()
+
+gr.Interface(caption_image, image_input, caption_output).launch()