| import gradio as gr
|
| from transformers import AutoModelForCausalLM, AutoTokenizer, AutoProcessor
|
| from PIL import Image
|
| import torch
|
|
|
|
|
| model_id = "Qwen/Qwen-VL-Chat"
|
| processor = AutoProcessor.from_pretrained(model_id)
|
| model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", trust_remote_code=True).eval()
|
| tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
|
|
|
| def recognize_handwriting(img):
|
| prompt = "<|im_start|>user\nWhat is written in the image?\n<|im_end|>\n<|im_start|>assistant\n"
|
| inputs = processor(text=prompt, images=img, return_tensors="pt").to(model.device)
|
| outputs = model.generate(**inputs, max_new_tokens=128)
|
| result = processor.batch_decode(outputs, skip_special_tokens=True)[0]
|
| return result
|
|
|
| gr.Interface(fn=recognize_handwriting,
|
| inputs=gr.Image(type="pil"),
|
| outputs="text",
|
| title="Handwriting Recognition with Qwen-VL").launch()
|
|
|
