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Update app.py
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app.py
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#
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# https://learn.deeplearning.ai/courses/open-source-models-hugging-face/lesson/
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#
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from transformers import
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model =
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from transformers import AutoProcessor
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processor = AutoProcessor.from_pretrained("Salesforce/blip-
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from PIL import Image
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import gradio as gr
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def
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output = processor.decode(
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return output
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gr.close_all()
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app = gr.Interface(fn=
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inputs=[gr.Image(label="
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app.launch()
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gr.close_all()
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# Visual question answering from
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# https://learn.deeplearning.ai/courses/open-source-models-hugging-face/lesson/13/multimodal-visual-question-answering
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#
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from transformers import BlipForQuestionAnswering
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model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base")
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from transformers import AutoProcessor
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processor = AutoProcessor.from_pretrained("Salesforce/blip-vqa-base")
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from PIL import Image
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import gradio as gr
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def answering(image, question):
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inputs = processor(image, question, return_tensors="pt")
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out = model.generate(**inputs)
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output = processor.decode(out[0], skip_special_tokens=True)
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return output
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gr.close_all()
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app = gr.Interface(fn=answering,
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inputs=[gr.Image(label="Picture here", type="pil"),
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gr.Textbox(label="Question about picture here")],
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outputs=[gr.Textbox(label="Answer"),],
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title="Harza's application for answering questions about picture'",
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description="Harza's miracle application that can answer questions about given picuture!'",
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allow_flagging="never")
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app.launch()
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gr.close_all()
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