#-*- coding: UTF-8 -*- # Copyright 2022 The Impira Team and the HuggingFace Team. # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import json import base64 from io import BytesIO from PIL import Image import traceback import requests import numpy as np import gradio as gr import pdf2image import fitz import cv2 fitz_tools = fitz.Tools() def pdf2img(stream, pagenos, dpi=300, thread_count=3, height=1600): images = [] cimages = pdf2image.convert_from_bytes( stream, dpi=dpi, thread_count=thread_count, first_page=pagenos[0] + 1, last_page=pagenos[-1] + 1, size=height) for _image in cimages: image = np.array(_image) image = image[..., ::-1] images.append(image) return images class PdfReader(object): """pdf reader""" def __init__(self, stream: bytes, image_height: int = 1600): self.stream = stream self._image_height = image_height self._dpi = 200 self._inpdf = self.load_file(stream) @staticmethod def load_file(stream): """load document""" try: inpdf = fitz.Document(stream=stream, filetype="pdf") except Exception as e: print(f"[PDF_READER]-[Failed to load the file]-[{repr(e)}]") return inpdf @staticmethod def _convert_page_obj_to_image(page_obj, image_height: int = None): """fitz convert pdf to image Args: page_obj ([type]): [description] ratio ([type]): [description] Returns: [type]: [description] """ if image_height: _, page_height = page_obj.rect.x1 - \ page_obj.rect.x0, page_obj.rect.y1 - page_obj.rect.y0 ratio = image_height / page_height else: ratio = 1.0 trans = fitz.Matrix(ratio, ratio) pixmap = page_obj.get_pixmap(matrix=trans, alpha=False) image = cv2.imdecode(np.frombuffer(pixmap.tobytes(), np.uint8), -1) fitz_tools.store_shrink(100) return image def get_page_image(self, pageno): """get page image Args: pageno ([type]): [description] Returns: [type]: [description] """ try: page_obj = self._inpdf[pageno] return self._convert_page_obj_to_image(page_obj, self._image_height) except Exception as e: print(f"[Failed to convert the PDF to images]-[{repr(e)}]") try: return pdf2img(stream=self.stream, pagenos=[pageno], height=self._image_height, dpi=self._dpi)[0] except Exception as e: print(f"[Failed to convert the PDF to images]-[{repr(e)}]") return None examples = [ [ "invoice.jpg", "发票号码是多少?", ], [ "resume.png", "五百丁本次想要担任的是什么职位?", ], [ "custom_declaration_form.png", "在哪个口岸进口?" ], [ "medical_bill_1.png", "票据的具体名称是什么?" ], [ "budget_form.png", "What is the total actual and/or obligated expenses of ECG Center?" ], [ "website_design_guide.jpeg", "Which quality component has the icon of a pen in it?" ], [ "poster.png", "Which gift idea needs a printer?" ], [ "medical_bill_2.png", "患者さんは何でお金を払いますか。" ], [ "receipt.png", "เบอร์โทรร้านอะไรคะ" ], ] prompt_files = { "发票号码是多少?": "invoice.jpg", "五百丁本次想要担任的是什么职位?": "resume.png", "在哪个口岸进口?": "custom_declaration_form.png", "票据的具体名称是什么?": "medical_bill_1.png", "What is the total actual and/or obligated expenses of ECG Center?": "budget_form.png", "Which quality component has the icon of a pen in it?": "website_design_guide.jpeg", "Which gift idea needs a printer?": "poster.png", "患者さんは何でお金を払いますか。": "medical_bill_2.png", "เบอร์โทรร้านอะไรคะ": "receipt.png" } def load_document(path): if path.startswith("http://") or path.startswith("https://"): resp = requests.get(path, allow_redirects=True, stream=True) b = resp.raw else: b = open(path, "rb") if path.endswith(".pdf"): images_list = [] pdfreader = PdfReader(stream=b.read()) for p_no in range(0, pdfreader._inpdf.page_count): img_np = pdfreader.get_page_image(pageno=p_no) images_list.append(img_np) else: image = Image.open(b) images_list = [image.convert("RGB")] return images_list def process_path(path): error = None if path: try: img = load_document(path) return ( path, gr.update(visible=True, value=img), gr.update(visible=True), gr.update(visible=False, value=None), gr.update(visible=False, value=None), None, ) except Exception as e: traceback.print_exc() error = str(e) return ( None, gr.update(visible=False, value=None), gr.update(visible=False), gr.update(visible=False, value=None), gr.update(visible=False, value=None), gr.update(visible=True, value=error) if error is not None else None, None, ) def process_upload(file): if file: return process_path(file.name) else: return ( None, gr.update(visible=False, value=None), gr.update(visible=False), gr.update(visible=False, value=None), gr.update(visible=False, value=None), None, ) def process_prompt(prompt, document, lang="ch"): if not prompt: prompt = "发票号码是多少?" if document is None: return None, None, None access_token = os.environ['token'] url = f"https://aip.baidubce.com/rpc/2.0/nlp-itec/poc/docprompt?access_token={access_token}" r = requests.post(url, json={"doc": document, "prompt": [prompt], "lang": lang}) response = r.json() predictions = response['result'] img_list = response['image'] pages = [Image.open(BytesIO(base64.b64decode(img))) for img in img_list] text_value = predictions[0]['result'][0]['value'] return ( gr.update(visible=True, value=pages), gr.update(visible=True, value=predictions), gr.update( visible=True, value=text_value, ), ) def load_example_document(img, prompt): if img is not None: document = prompt_files[prompt] preview, answer, answer_text = process_prompt(prompt, document) return document, prompt, preview, gr.update(visible=True), answer, answer_text else: return None, None, None, gr.update(visible=False), None, None def read_content(file_path: str) -> str: """read the content of target file """ with open(file_path, 'r', encoding='utf-8') as f: content = f.read() return content CSS = """ #prompt input { font-size: 16px; } #url-textbox { padding: 0 !important; } #short-upload-box .w-full { min-height: 10rem !important; } /* I think something like this can be used to re-shape * the table */ /* .gr-samples-table tr { display: inline; } .gr-samples-table .p-2 { width: 100px; } */ #select-a-file { width: 100%; } #file-clear { padding-top: 2px !important; padding-bottom: 2px !important; padding-left: 8px !important; padding-right: 8px !important; margin-top: 10px; } .gradio-container .gr-button-primary { background: linear-gradient(180deg, #CDF9BE 0%, #AFF497 100%); border: 1px solid #B0DCCC; border-radius: 8px; color: #1B8700; } .gradio-container.dark button#submit-button { background: linear-gradient(180deg, #CDF9BE 0%, #AFF497 100%); border: 1px solid #B0DCCC; border-radius: 8px; color: #1B8700 } table.gr-samples-table tr td { border: none; outline: none; } table.gr-samples-table tr td:first-of-type { width: 0%; } div#short-upload-box div.absolute { display: none !important; } gradio-app > div > div > div > div.w-full > div, .gradio-app > div > div > div > div.w-full > div { gap: 0px 2%; } gradio-app div div div div.w-full, .gradio-app div div div div.w-full { gap: 0px; } gradio-app h2, .gradio-app h2 { padding-top: 10px; } #answer { overflow-y: scroll; color: white; background: #666; border-color: #666; font-size: 20px; font-weight: bold; } #answer span { color: white; } #answer textarea { color:white; background: #777; border-color: #777; font-size: 18px; } #url-error input { color: red; } """ with gr.Blocks(css=CSS) as demo: gr.HTML(read_content("header.html")) gr.Markdown( f" ⚡DocPrompt⚡ is a Document Prompt Engine Powered by Baidu Wenxin Document Intelligence. 🚀\n" f" To use it, simply upload an image or PDF, type the prompt, and click 'submit', or " f" click one of the examples to load them." ) document = gr.Variable() example_prompt = gr.Textbox(visible=False) example_image = gr.Image(visible=False) with gr.Row(equal_height=True): with gr.Column(): with gr.Row(): gr.Markdown("## 1. Select a file", elem_id="select-a-file") img_clear_button = gr.Button( "Clear", variant="secondary", elem_id="file-clear", visible=False ) image = gr.Gallery(visible=False) with gr.Row(equal_height=True): with gr.Column(): with gr.Row(): url = gr.Textbox( show_label=False, placeholder="URL", lines=1, max_lines=1, elem_id="url-textbox", ) submit = gr.Button("Get") url_error = gr.Textbox( visible=False, elem_id="url-error", max_lines=1, interactive=False, label="Error", ) gr.Markdown("— or —") upload = gr.File(label=None, interactive=True, elem_id="short-upload-box") gr.Examples( examples=examples, inputs=[example_image, example_prompt], ) with gr.Column() as col: gr.Markdown("## 2. Make a request") prompt = gr.Textbox( label="Prompt", placeholder="发票号码是多少?", lines=1, max_lines=1, ) ocr_lang = gr.Radio( choices=["ch", "en"], value="ch", label="OCR Language", ) with gr.Row(): clear_button = gr.Button("Clear", variant="secondary") submit_button = gr.Button( "Submit", variant="primary", elem_id="submit-button" ) with gr.Column(): output_text = gr.Textbox( label="Top Answer", visible=False, elem_id="answer" ) output = gr.JSON(label="Output", visible=False) for cb in [img_clear_button, clear_button]: cb.click( lambda _: ( gr.update(visible=False, value=None), None, gr.update(visible=False, value=None), gr.update(visible=False, value=None), gr.update(visible=False), None, None, None, gr.update(visible=False, value=None), None, ), inputs=clear_button, outputs=[ image, document, output, output_text, img_clear_button, example_image, upload, url, url_error, prompt, ], ) upload.change( fn=process_upload, inputs=[upload], outputs=[document, image, img_clear_button, output, output_text, url_error], ) submit.click( fn=process_path, inputs=[url], outputs=[document, image, img_clear_button, output, output_text, url_error], ) prompt.submit( fn=process_prompt, inputs=[prompt, document], outputs=[image, output, output_text], ) submit_button.click( fn=process_prompt, inputs=[prompt, document, ocr_lang], outputs=[image, output, output_text], ) ocr_lang.change( fn=process_prompt, inputs=[prompt, document, ocr_lang], outputs=[image, output, output_text], ) example_image.change( fn=load_example_document, inputs=[example_image, example_prompt], outputs=[document, prompt, image, img_clear_button, output, output_text], ) gr.Image('./paddlenlp-preview.jpeg') gr.Markdown("[![Stargazers repo roster for @PaddlePaddle/PaddleNLP](https://reporoster.com/stars/PaddlePaddle/PaddleNLP)](https://github.com/PaddlePaddle/PaddleNLP)") gr.HTML(read_content("footer.html")) if __name__ == "__main__": demo.launch(enable_queue=False)