Create app.py

app.py

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+import gradio as gr
+from transformers import BlipProcessor, BlipForConditionalGeneration
+
+model_id = "dblasko/blip-dalle3-img2prompt"
+model = BlipForConditionalGeneration.from_pretrained(model_id)
+processor = BlipProcessor.from_pretrained(model_id)
+
+def generate_caption(image):
+ inputs = processor(images=image, return_tensors="pt")
+ pixel_values = inputs.pixel_values
+
+ generated_ids = model.generate(pixel_values=pixel_values, max_length=50)
+ generated_caption = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+ return generated_caption
+
+# Create a gradio interface with an image input and a textbox output
+demo = gr.Interface(fn=generate_caption, inputs=gr.Image(shape=(224, 224)), outputs=gr.Textbox(label="Generated caption"))
+demo.launch()