| import gradio as gr |
| from transformers import BlipProcessor, BlipForConditionalGeneration |
| from deep_translator import GoogleTranslator |
| from PIL import Image |
|
|
| processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base") |
| model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base") |
|
|
| def caption_image(image): |
| if image is None: |
| return " من فضلك ارفع صورة" |
| |
| inputs = processor(image, return_tensors="pt") |
| output = model.generate(**inputs, max_new_tokens=50) |
| caption_en = processor.decode(output[0], skip_special_tokens=True) |
| caption_ar = GoogleTranslator(source='en', target='ar').translate(caption_en) |
| |
| return f"** الوصف:** {caption_ar}" |
|
|
| demo = gr.Interface( |
| fn=caption_image, |
| inputs=gr.Image(label="ارفع الصوره التي تريد وصفها", type="pil"), |
| outputs=gr.Markdown(label="الوصف"), |
| title="مولّد أوصاف الصور", |
| |
| ) |
|
|
| demo.launch() |
