add files

.gitattributes

@@ -32,3 +32,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+.psd filter=lfs diff=lfs merge=lfs -text
+.jpeg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.psd filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,8 +1,8 @@
 ---
-title: Uie Test
-emoji: 📚
-colorFrom: blue
-colorTo: blue
+title: UIE Test
+emoji: 📄
+colorFrom: gray
+colorTo: pink
 sdk: gradio
 sdk_version: 3.14.0
 app_file: app.py

app.py

@@ -0,0 +1,448 @@
+#-*- 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 cv2
+
+from paddlenlp import Taskflow
+from paddlenlp.utils.doc_parser import DocParser
+
+doc_parser = DocParser()
+task_instance = Taskflow("information_extraction", model="uie-x-base", schema="")
+
+examples = [
+    [
+        "invoice.jpeg",
+        "名称;纳税人识别号;开票日期",
+    ],
+    [
+        "custom.jpeg",
+        "收发货人;进口口岸;进口日期;运输方式;征免性质;境内目的地;运输工具名称;包装种类;件数;合同协议号"
+    ],
+    [
+        "resume.png",
+        "职位;年龄;学校|时间;学校|专业",
+    ],
+]
+
+example_files = {
+    "Name;Title;Web Link;Email;Address": "business_card.png",
+    "Name;DOB;ISS;EXP": "license.jpeg",
+    "职位;年龄;学校|时间;学校|专业": "resume.png",
+    "收发货人;进口口岸;进口日期;运输方式;征免性质;境内目的地;运输工具名称;包装种类;件数;合同协议号": "custom.jpeg",
+    "名称;纳税人识别号;开票日期": "invoice.jpeg",
+}
+
+lang_map = {
+    "resume.png": "ch",
+    "custom.jpeg": "ch",
+    "business_card.png": "en",
+    "invoice.jpeg": "ch",
+    "license.jpeg": "en",
+}
+
+def dbc2sbc(s):
+    rs = ""
+    for char in s:
+        code = ord(char)
+        if code == 0x3000:
+            code = 0x0020
+        else:
+            code -= 0xfee0
+        if not (0x0021 <= code and code <= 0x7e):
+            rs += char
+            continue
+        rs += chr(code)
+    return rs
+
+
+def process_path(path):
+    error = None
+    if path:
+        try:
+            images_list = [doc_parser.read_image(path)]
+            return (
+                path,
+                gr.update(visible=True, value=images_list),
+                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 BGR2RGB(img):
+    pilimg = img.copy()
+    pilimg[:, :, 0] = img[:, :, 2]
+    pilimg[:, :, 2] = img[:, :, 0]
+    return pilimg
+
+
+def np2base64(image_np):
+    image_np = BGR2RGB(image_np)
+    image = cv2.imencode('.jpg', image_np)[1]
+    base64_str = str(base64.b64encode(image))[2:-1]
+    return base64_str
+
+
+def get_schema(schema_str):
+    def _is_ch(s):
+        for ch in s:
+            if "\u4e00" <= ch <= "\u9fff":
+                return True
+        return False
+    schema_lang = "ch" if _is_ch(schema_str) else "en"
+    schema = schema_str.split(";")
+    schema_list = []
+    for s in schema:
+        cand = s.split("|")
+        if len(cand) == 1:
+            schema_list.append(cand[0])
+        else:
+            subject = cand[0]
+            relations = cand[1:]
+            added = False
+            for a in schema_list:
+                if isinstance(a, dict):
+                    if subject in a.keys():
+                        a[subject].extend(relations)
+                        added = True
+                        break
+            if not added:
+                a = {subject: relations}
+                schema_list.append(a)
+    return schema_list, schema_lang
+
+
+def run_taskflow(document, schema, argument):
+    task_instance.set_schema(schema)
+    # task_instance.set_argument(argument)
+    return task_instance({'doc': document})
+
+
+def process_doc(document, schema, ocr_lang, layout_analysis):
+    if not schema:
+        schema = '时间;组织机构;人物'
+    if document is None:
+        return None, None
+
+    schema, schema_lang = get_schema(dbc2sbc(schema))
+    argument = {
+        "ocr_lang": ocr_lang,
+        "schema_lang": schema_lang,
+        "layout_analysis": layout_analysis
+    }
+    prediction = run_taskflow(document, schema, argument)[0]
+
+    img_show = doc_parser.write_image_with_results(
+        document,
+        result=prediction,
+        return_image=True)
+    img_list = [img_show]
+
+    return (
+        gr.update(visible=True, value=img_list),
+        gr.update(visible=True, value=prediction),
+    )
+
+
+def load_example_document(img, schema, ocr_lang, layout_analysis):
+    if img is not None:
+        document = example_files[schema]
+        choice = lang_map[document].split("-")
+        ocr_lang = choice[0]
+        layout_analysis = False if len(choice) == 1 else True
+        preview, answer = process_doc(document, schema, ocr_lang, layout_analysis)
+        return document, schema, preview, gr.update(visible=True), answer
+    else:
+        return None, None, None, gr.update(visible=False), 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(
+        "**UIE-X 🧾 🎓** is a universal information extraction engine which supports both document and text inputs. It is powered by BAIDU and released on PaddleNLP. "
+        "Our extraction target(schema) can be set in natural language without limitation, and it also supports most extraction tasks. "
+        "The model performs well on zero-shot and few-shot settings. Moreover, on PaddleNLP, we provide a comprehensive and easy-to-use fine-tuning customization workflow." 
+        "For more details, please visit the [GitHub](https://github.com/PaddlePaddle/PaddleNLP/tree/develop/applications/information_extraction)"
+    )
+
+    document = gr.Variable()
+    is_text = gr.Variable()
+    example_schema = 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. 选择文件 / 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_schema],
+            )
+
+        with gr.Column():
+            gr.Markdown("## 2. 信息抽取 / Information extraction ℹ️ ")
+            gr.Markdown("### 👉 设置schema")
+            gr.Markdown("实体抽取：实体类别之间以';'分割，例如 **人物；组织机构**")
+            gr.Markdown("关系抽取：需配置主体和关系类别，中间以'|'分割，例如 **人物|出生时间；人物|邮箱**")
+            gr.Markdown("### 👉 Set a schema")
+            gr.Markdown("Entity extraction: entity label should be separated by ';', e.g. **Person;Organization**")
+            gr.Markdown("Relation extraction: set the subject and relation type, separated by '|', e.g. **Person|Date;Person|Email**")
+            gr.Markdown("### 💪 模型定制 / Model customization")
+            gr.Markdown("我们建议通过[数据标注+微调](https://github.com/PaddlePaddle/PaddleNLP/tree/develop/applications/information_extraction/document)的流程进一步增强模型在特定场景的效果")
+            gr.Markdown("We recommend to further improve the extraction performance in specific domain through the process of [data annotation & fine-tuning](https://github.com/PaddlePaddle/PaddleNLP/tree/develop/applications/information_extraction/document)")
+
+            schema = gr.Textbox(
+                label="Schema",
+                placeholder="e.g. Name|Company;Name|Position;Email;Phone Number",
+                lines=1,
+                max_lines=1,
+            )
+
+            ocr_lang = gr.Radio(
+                choices=["ch", "en"],
+                value="en",
+                label="OCR语言 / OCR Language (Please choose ch for Chinese images.)",
+            )
+
+            layout_analysis = gr.Radio(
+                choices=["yes", "no"],
+                value="no",
+                label="版面分析 / Layout analysis (Better extraction for multi-line text)",
+            )
+
+            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 = 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),
+                None,
+                None,
+                None,
+                gr.update(visible=False, value=None),
+                None,
+            ),
+            inputs=clear_button,
+            outputs=[
+                image,
+                document,
+                output,
+                img_clear_button,
+                example_image,
+                upload,
+                url,
+                url_error,
+                schema,
+            ],
+        )
+
+    upload.change(
+        fn=process_upload,
+        inputs=[upload],
+        outputs=[document, image, img_clear_button, output, url_error],
+    )
+    submit.click(
+        fn=process_path,
+        inputs=[url],
+        outputs=[document, image, img_clear_button, output, url_error],
+    )
+
+    schema.submit(
+        fn=process_doc,
+        inputs=[document, schema, ocr_lang, layout_analysis],
+        outputs=[image, output],
+    )
+
+    submit_button.click(
+        fn=process_doc,
+        inputs=[document, schema, ocr_lang, layout_analysis],
+        outputs=[image, output],
+    )
+
+    example_image.change(
+        fn=load_example_document,
+        inputs=[example_image, example_schema, ocr_lang, layout_analysis],
+        outputs=[document, schema, image, img_clear_button, output],
+    )
+
+    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)

footer.html

@@ -0,0 +1,4 @@
+<div class="footer">
+    <p>Model by <a href="https://github.com/PaddlePaddle/PaddleNLP" style="text-decoration: underline;" target="_blank">PaddleNLP</a> - Gradio Demo by 🤗 Hugging Face
+    </p>
+</div>

header.html

@@ -0,0 +1,28 @@
+<div style="text-align: center; max-width: 650px; margin: 0 auto;">
+    <div
+      style="
+        display: inline-flex;
+        gap: 0.8rem;
+        font-size: 1.75rem;
+        margin-bottom: 10px;
+        margin-left: 220px;
+        justify-content: center;
+      "
+    >
+    <a href="https://github.com/PaddlePaddle/PaddleNLP"><img src="https://user-images.githubusercontent.com/1371212/175816733-8ec25eb0-9af3-4380-9218-27c154518258.png" alt="PaddleNLP" width="60%"></a>
+    </div> 
+    <div
+      style="
+        display: inline-flex;
+        align-items: center;
+        gap: 0.8rem;
+        font-size: 1.75rem;
+        margin-bottom: 10px;
+        justify-content: center;
+      ">
+    <a href="https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/ernie-layout"><h1 style="font-weight: 900; align-items: center; margin-bottom: 7px;">
+      UIE-X
+    </h1></a>
+    </div> 
+    <a href="https://github.com/PaddlePaddle/PaddleNLP"><img src="https://user-images.githubusercontent.com/40840292/207606629-22da5e22-68e5-47a6-aafd-87d3d7447793.png" width="100%"></a>
+  </div>

requirements.txt

@@ -0,0 +1,5 @@
+numpy
+opencv-python
+paddlenlp
+paddlepaddle
+requests