import torch,sys
from PIL import Image
from transformers import BlipProcessor, BlipForConditionalGeneration
processor = BlipProcessor.from_pretrained("norwoodsystems/image-caption")
model = BlipForConditionalGeneration.from_pretrained("norwoodsystems/image-caption",    use_safetensors=True)
image_path = sys.argv[1]
raw_image = Image.open(image_path).convert('RGB')
inputs = processor(images=raw_image, return_tensors="pt")
with torch.no_grad():
    generated_ids =  model.generate(**inputs, do_sample=True, top_p=0.9, temperature=1.0)


description = processor.decode(generated_ids[0], skip_special_tokens=True)
print("Description:", description)