zhd36
49 lines
1.6 KiB
Python
Executable File
49 lines
1.6 KiB
Python
Executable File
import argparse
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from openai import OpenAI
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from transformers.utils.versions import require_version
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from PIL import Image
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from dots_ocr.utils import dict_promptmode_to_prompt
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from dots_ocr.model.inference import inference_with_vllm
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parser = argparse.ArgumentParser()
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parser.add_argument("--ip", type=str, default="localhost")
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parser.add_argument("--port", type=str, default="8000")
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parser.add_argument("--model_name", type=str, default="rednote-hilab/dots.ocr")
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parser.add_argument("--image_path", type=str, default="demo/demo_image1.jpg")
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parser.add_argument("--prompt_mode", type=str, default="prompt_layout_all_en",help=(
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"Choose a task prompt: "
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"prompt_layout_all_en=full document layout+OCR to JSON/MD; "
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"prompt_layout_only_en=layout detection only; "
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"prompt_grounding_ocr=OCR within a given bbox; "
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"prompt_web_parsing=parse webpage screenshot layout into JSON; "
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"prompt_scene_spotting=detect+recognize scene text (OCR boxes+texts); "
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"prompt_image_to_svg=generate SVG code to reconstruct the image.")
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)
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args = parser.parse_args()
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require_version("openai>=1.5.0", "To fix: pip install openai>=1.5.0")
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def main():
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addr = f"http://{args.ip}:{args.port}/v1"
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image_path = args.image_path
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prompt = dict_promptmode_to_prompt[args.prompt_mode]
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image = Image.open(image_path)
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response = inference_with_vllm(
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image,
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prompt,
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ip=args.ip,
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port=args.port,
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temperature=0.1,
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top_p=0.9,
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model_name=args.model_name,
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)
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print(f"response: {response}")
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if __name__ == "__main__":
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main()
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