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import gradio as gr | |
from transformers import AutoModel, AutoProcessor | |
from PIL import Image | |
import torch | |
import numpy as np | |
model_name_or_path = "lyttt/VLV_captioner" | |
model = AutoModel.from_pretrained(model_name_or_path, revision="master", trust_remote_code=True,low_cpu_mem_usage=False) | |
def greet(image): | |
if image.dtype != np.uint8: | |
image = (np.clip(image, 0, 1) * 255).astype(np.uint8) | |
image = Image.fromarray(image, mode='RGB') | |
with torch.no_grad(): | |
outputs = model([image]).generated_text[0] | |
return output | |
demo = gr.Interface(fn=greet, inputs="image", outputs="text") | |
demo.launch() |