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| import torch | |
| import re | |
| import gradio as gr | |
| from PIL import Image | |
| from transformers import DonutProcessor, VisionEncoderDecoderModel | |
| def demo_process(input_img): | |
| # input_img = Image.fromarray(input_img) | |
| processor = DonutProcessor.from_pretrained("thinkersloop/donut-demo") | |
| pretrained_model = VisionEncoderDecoderModel.from_pretrained("thinkersloop/donut-demo") | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| pretrained_model.to(device) | |
| pixel_values = processor(input_img, return_tensors="pt").pixel_values | |
| task_prompt = "<s_cord-v2>" | |
| decoder_input_ids = processor.tokenizer(task_prompt, add_special_tokens=False, return_tensors="pt")["input_ids"] | |
| outputs = pretrained_model.generate(pixel_values.to(device), | |
| decoder_input_ids=decoder_input_ids.to(device), | |
| max_length=pretrained_model.decoder.config.max_position_embeddings, | |
| early_stopping=True, | |
| pad_token_id=processor.tokenizer.pad_token_id, | |
| eos_token_id=processor.tokenizer.eos_token_id, | |
| use_cache=True, | |
| num_beams=1, | |
| bad_words_ids=[[processor.tokenizer.unk_token_id]], | |
| return_dict_in_generate=True, | |
| output_scores=True,) | |
| sequence = processor.batch_decode(outputs.sequences)[0] | |
| sequence = sequence.replace(processor.tokenizer.eos_token, "").replace(processor.tokenizer.pad_token, "") | |
| sequence = re.sub(r"<.*?>", "", sequence, count=1).strip() | |
| return processor.token2json(sequence) | |
| # task_prompt = f"<s_cord-v2>" | |
| image = Image.open("./sample_1.jpg") | |
| image.save("cord_sample_1.png") | |
| image = Image.open("./sample_2.jpg") | |
| image.save("cord_sample_2.png") | |
| image = Image.open("./sample_3.jpg") | |
| image.save("cord_sample_3.png") | |
| demo = gr.Interface( | |
| fn=demo_process, | |
| inputs= gr.inputs.Image(type="pil"), | |
| outputs="json", | |
| title=f"Transformers demo for `cord-v2` task", | |
| description="""This model is trained with 66 driver's license images of CORD dataset. <br>""", | |
| # examples=[["cord_sample_1.png"], ["cord_sample_2.png"], ["cord_sample_3.png"]], | |
| cache_examples=False, | |
| ) | |
| demo.launch() |