| from PIL import Image | |
| import gradio as gr | |
| import requests | |
| from transformers import AutoProcessor, BlipForQuestionAnswering | |
| model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base") | |
| processor = AutoProcessor.from_pretrained("Salesforce/blip-vqa-base") | |
| def generate_answer(text, image): | |
| text = text | |
| inputs = processor(images=image, text=text, return_tensors="pt") | |
| outputs = model.generate(**inputs) | |
| return processor.decode(outputs[0], skip_special_tokens=True) | |
| text_input = gr.Textbox(lines=5, label="Enter text") | |
| image_input = gr.Image(type="pil", label="Upload Image") | |
| iface = gr.Interface( | |
| fn=generate_answer, | |
| inputs=[text_input, image_input], | |
| outputs="text", | |
| title="DD360-Bot-Multimodal", | |
| description="Enter text and upload an image" | |
| ) | |
| iface.launch() | |