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from transformers import AutoProcessor, AutoModelForVision2Seq | |
from PIL import Image | |
from os import path | |
from torchvision.transforms import ToTensor | |
model_id = "microsoft/kosmos-2-patch14-224" | |
model = AutoModelForVision2Seq.from_pretrained(model_id) | |
processor = AutoProcessor.from_pretrained(model_id) | |
def single_image_classification(image, prompt="", max_new_tokens=30): | |
inputs = processor(text=prompt, images=image, return_tensors="pt") | |
generated_ids = model.generate( | |
pixel_values=inputs["pixel_values"], | |
input_ids=inputs["input_ids"], | |
attention_mask=inputs["attention_mask"], | |
image_embeds=None, | |
image_embeds_position_mask=inputs["image_embeds_position_mask"], | |
use_cache=True, | |
max_new_tokens=max_new_tokens, | |
) | |
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
print("GENERATED:", generated_text) | |
processed_text = processor.post_process_generation(generated_text, cleanup_and_extract=False) | |
print("PROCESSED:", processed_text) | |
return processed_text |