diff --git a/.github/workflows/gen_whl_to_pypi_rapidocr_web.yml b/.github/workflows/gen_whl_to_pypi_rapidocr_web.yml deleted file mode 100644 index dd298cc..0000000 --- a/.github/workflows/gen_whl_to_pypi_rapidocr_web.yml +++ /dev/null @@ -1,38 +0,0 @@ -name: Push rapidocr_web to pypi - -on: - push: - branches: [ main ] - paths: - - 'ocrweb/rapidocr_web/**' - - '!ocrweb/rapidocr_web/ocr_web.spec' - - 'docs/doc_whl_rapidocr_web.md' - - 'ocrweb/setup.py' - - '.github/workflows/gen_whl_to_pypi_rapidocr_web.yml' - -jobs: - GenerateWHL_PushPyPi: - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v4 - - - name: Set up Python 3.10 - uses: actions/setup-python@v4 - with: - python-version: '3.10' - architecture: 'x64' - - - name: Run setup.py - run: | - cd ocrweb - pip install -r requirements.txt - - python -m pip install --upgrade pip - python setup.py bdist_wheel "${{ github.event.head_commit.message }}" - - - name: Publish distribution 📦 to PyPI - uses: pypa/gh-action-pypi-publish@v1.5.0 - with: - password: ${{ secrets.RAPIDOCR_OPENVINO }} - packages_dir: ocrweb/dist/ diff --git a/.github/workflows/package_ocrweb.yml b/.github/workflows/package_ocrweb.yml deleted file mode 100644 index 05646e4..0000000 --- a/.github/workflows/package_ocrweb.yml +++ /dev/null @@ -1,158 +0,0 @@ -name: Package ocrweb - -on: - push: - branches: main - paths: - - 'ocrweb/rapidocr_web/ocrweb.py' - - 'ocrweb/rapidocr_web/task.py' - - 'ocrweb/rapidocr_web/static/**' - - 'ocrweb/rapidocr_web/templates/**' - - -env: - package_name: RapidOCRWeb - rapidocr_web_dir: ocrweb/rapidocr_web/ - -jobs: - create_release: - runs-on: ubuntu-latest - outputs: - upload_url: ${{ steps.create_release.outputs.upload_url }} - steps: - - name: get_cur_time - uses: srfrnk/current-time@master - id: get_cur_time - with: - format: YYYY-MM-DD-HH-mm-ss - - name: create_release - id: create_release - uses: marvinpinto/action-automatic-releases@latest - with: - repo_token: ${{ secrets.GITHUB_TOKEN }} - automatic_release_tag: Draft-${{ steps.get_cur_time.outputs.formattedTime }} - prerelease: false - draft: true - - build_windows: - name: build_windows - runs-on: ${{ matrix.os }} - needs: create_release - strategy: - matrix: - os: ['windows-2022', 'windows-2019'] - - steps: - - name: Pull latest code - uses: actions/checkout@v4 - - - name: Set up Python 3.7 - uses: actions/setup-python@v4 - with: - python-version: '3.7' - architecture: 'x64' - - - name: Display Python version - run: python -c "import sys; print(sys.version)" - - - name: Install environments - run: | - pip3 install Pillow pyinstaller Flask>=2.1.0 rapidocr_onnxruntime>=1.2.8 get_pypi_latest_version - - - name: Run pyinstaller - id: run_pyinstaller - shell: bash - run: | - cd ${{ env.rapidocr_web_dir }} - pyinstaller ocrweb.spec - cp -r static templates dist/${{ env.package_name }} - rm dist/${{ env.package_name }}/cv2/opencv_videoio_ffmpe*.dll || echo "未找到opencv_videoio_ffmpeg" - echo "VERSION=$(get_pypi_latest_version rapid_videocr)" >> $GITHUB_OUTPUT - - - name: Concat file path - id: concat_file_path - shell: bash - env: - ZIP_WIN_NAME: ${{ env.package_name }}-${{ steps.run_pyinstaller.outputs.VERSION }}-${{ matrix.os }}-${{ runner.arch }}-no-installer.zip - Win_DIST_DIR: ${{ github.workspace }}\ocrweb\rapidocr_web\dist - run: | - echo "ZIP_NAME=$ZIP_WIN_NAME" >> $GITHUB_OUTPUT - echo "Win_PACKAGE_DIR=$Win_DIST_DIR\${{ env.package_name }}" >> $GITHUB_OUTPUT - echo "Win_ZIP_FULL_PATH=$Win_DIST_DIR\\$ZIP_WIN_NAME" >> $GITHUB_OUTPUT - - - name: Zip package - run: | - powershell Compress-Archive ${{ steps.concat_file_path.outputs.Win_PACKAGE_DIR }} ${{ steps.concat_file_path.outputs.Win_ZIP_FULL_PATH }} - - - name: Upload release asset - id: upload-release-asset-windows - uses: actions/upload-release-asset@v1 - env: - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} - with: - upload_url: ${{ needs.create_release.outputs.upload_url }} - asset_path: ${{ steps.concat_file_path.outputs.Win_ZIP_FULL_PATH }} - asset_name: ${{ steps.concat_file_path.outputs.ZIP_NAME }} - asset_content_type: application/zip - - build_linux: - name: build_linux - runs-on: ${{ matrix.os }} - needs: create_release - strategy: - matrix: - os: ['ubuntu-20.04', 'ubuntu-22.04', 'macos-13', 'macos-12', 'macos-11'] - - steps: - - name: Pull latest code - uses: actions/checkout@v4 - - - name: Set up Python 3.7 - uses: actions/setup-python@v4 - with: - python-version: '3.7' - architecture: 'x64' - - - name: Display Python version - run: python -c "import sys; print(sys.version)" - - - name: Install environments - run: | - pip3 install Pillow pyinstaller Flask>=2.1.0 rapidocr_onnxruntime>=1.2.8 get_pypi_latest_version - - - name: Run pyinstaller - id: run_pyinstaller - shell: bash - run: | - cd ocrweb/rapidocr_web/ - pyinstaller ocrweb.spec - cp -r static templates dist/${{ env.package_name }} - rm dist/${{ env.package_name }}/cv2/opencv_videoio_ffmpe*.dll || echo "未找到opencv_videoio_ffmpeg" - echo "VERSION=$(get_pypi_latest_version rapid_videocr)" >> $GITHUB_OUTPUT - - - name: Concat file path - id: concat_file_path - env: - ZIP_NAME: ${{ env.package_name }}-${{ steps.run_pyinstaller.outputs.VERSION }}-${{ matrix.os }}-${{ runner.arch }}-no-installer.zip - Linux_DIST_DIR: ${{ github.workspace }}/ocrweb/rapidocr_web/dist - run: | - echo "ZIP_NAME=$ZIP_NAME" >> $GITHUB_OUTPUT - echo "Linux_PACKAGE_DIR=$Linux_DIST_DIR/${{ env.package_name }}" >> $GITHUB_OUTPUT - echo "Linux_ZIP_FULL_PATH=$Linux_DIST_DIR/$ZIP_NAME" >> $GITHUB_OUTPUT - echo "Linux_DIST_DIR=$Linux_DIST_DIR" >> $GITHUB_OUTPUT - - - name: Zip package - run: | - cd ${{ steps.concat_file_path.outputs.Linux_DIST_DIR }} - zip -r ${{ steps.concat_file_path.outputs.ZIP_NAME }} ${{ env.package_name }} - - - name: Upload release asset - id: upload-release-asset-linux-macOS - uses: actions/upload-release-asset@v1 - env: - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} - with: - upload_url: ${{ needs.create_release.outputs.upload_url }} - asset_path: ${{ steps.concat_file_path.outputs.Linux_ZIP_FULL_PATH }} - asset_name: ${{ steps.concat_file_path.outputs.ZIP_NAME }} - asset_content_type: application/zip diff --git a/docs/doc_whl_rapidocr_web.md b/docs/doc_whl_rapidocr_web.md deleted file mode 100644 index d0a5b02..0000000 --- a/docs/doc_whl_rapidocr_web.md +++ /dev/null @@ -1 +0,0 @@ -### See [Documentation](https://rapidai.github.io/RapidOCRDocs/install_usage/rapidocr_web/rapidocr_web/) diff --git a/ocrweb/README.md b/ocrweb/README.md index 7fdd128..0429265 100755 --- a/ocrweb/README.md +++ b/ocrweb/README.md @@ -1 +1 @@ -### See [Documentation](https://rapidai.github.io/RapidOCRDocs/main/install_usage/rapidocr_web/usage/) +See [RapidOCRWeb](https://github.com/RapidAI/RapidOCRWeb) for details. diff --git a/ocrweb/rapidocr_web/__init__.py b/ocrweb/rapidocr_web/__init__.py deleted file mode 100644 index d071b07..0000000 --- a/ocrweb/rapidocr_web/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com \ No newline at end of file diff --git a/ocrweb/rapidocr_web/ocrweb.py b/ocrweb/rapidocr_web/ocrweb.py deleted file mode 100644 index afc669d..0000000 --- a/ocrweb/rapidocr_web/ocrweb.py +++ /dev/null @@ -1,47 +0,0 @@ -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com -import argparse -from pathlib import Path -from wsgiref.simple_server import make_server - -from flask import Flask, render_template, request - -try: - from rapidocr_web.task import OCRWebUtils -except: - from task import OCRWebUtils - -root_dir = Path(__file__).resolve().parent - -app = Flask(__name__, template_folder="templates") -app.config["MAX_CONTENT_LENGTH"] = 3 * 1024 * 1024 -processor = OCRWebUtils() - - -@app.route("/") -def index(): - return render_template("index.html") - - -@app.route("/ocr", methods=["POST"]) -def ocr(): - if request.method == "POST": - img_str = request.get_json().get("file", None) - ocr_res = processor(img_str) - return ocr_res - - -def main(): - parser = argparse.ArgumentParser("rapidocr_web") - parser.add_argument("-ip", "--ip", type=str, default="0.0.0.0", help="IP Address") - parser.add_argument("-p", "--port", type=int, default=9003, help="IP port") - args = parser.parse_args() - - print(f"Successfully launched and visit http://{args.ip}:{args.port} to view.") - server = make_server(args.ip, args.port, app) - server.serve_forever() - - -if __name__ == "__main__": - main() diff --git a/ocrweb/rapidocr_web/ocrweb.spec b/ocrweb/rapidocr_web/ocrweb.spec deleted file mode 100644 index 482bb61..0000000 --- a/ocrweb/rapidocr_web/ocrweb.spec +++ /dev/null @@ -1,72 +0,0 @@ -# -*- mode: python ; coding: utf-8 -*- -from pathlib import Path - -import rapidocr_onnxruntime - -block_cipher = None - -package_name = 'rapidocr_onnxruntime' -install_dir = Path(rapidocr_onnxruntime.__file__).resolve().parent - -onnx_paths = list(install_dir.rglob('*.onnx')) -yaml_paths = list(install_dir.rglob('*.yaml')) - -onnx_add_data = [(str(v.parent), f'{package_name}/{v.parent.name}') - for v in onnx_paths] - -yaml_add_data = [] -for v in yaml_paths: - if package_name == v.parent.name: - yaml_add_data.append((str(v.parent / '*.yaml'), package_name)) - else: - yaml_add_data.append( - (str(v.parent / '*.yaml'), f'{package_name}/{v.parent.name}')) - -add_data = list(set(yaml_add_data + onnx_add_data)) - - -a = Analysis( - ['ocrweb.py'], - pathex=[], - binaries=[], - datas=add_data, - hiddenimports=[], - hookspath=[], - hooksconfig={}, - runtime_hooks=[], - excludes=[], - win_no_prefer_redirects=False, - win_private_assemblies=False, - cipher=block_cipher, - noarchive=False, -) -pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) - -exe = EXE( - pyz, - a.scripts, - [], - exclude_binaries=True, - name='RapidOCRWeb', - debug=False, - bootloader_ignore_signals=False, - strip=False, - upx=True, - console=True, - disable_windowed_traceback=False, - argv_emulation=False, - target_arch=None, - codesign_identity=None, - entitlements_file=None, - icon=['./static/css/favicon.ico'], -) -coll = COLLECT( - exe, - a.binaries, - a.zipfiles, - a.datas, - strip=False, - upx=True, - upx_exclude=[], - name='RapidOCRWeb', -) diff --git a/ocrweb/rapidocr_web/static/css/favicon.ico b/ocrweb/rapidocr_web/static/css/favicon.ico deleted file mode 100644 index b30495c..0000000 Binary files a/ocrweb/rapidocr_web/static/css/favicon.ico and /dev/null differ diff --git a/ocrweb/rapidocr_web/static/css/main.css b/ocrweb/rapidocr_web/static/css/main.css deleted file mode 100644 index a1d5f28..0000000 --- a/ocrweb/rapidocr_web/static/css/main.css +++ /dev/null @@ -1,99 +0,0 @@ -body{ - background-color:#ebedef; - min-height: 100%; - margin: 0; -} -.btn-gen { - /* position: absolute;top:540px; left: 500px; */ - background-color: #00a1d6; - text-align: center; - border-radius: 18px; - margin-top: 5px; - font-size: 15px; - padding: 5px 10px; - height: 20px; - width: 120px; - text-transform: uppercase; - color: #fff; - border:none; -} -.btn-gen:hover, -.btn-gen:focus { - border-color: #23AAEE; - background-color: #23AAEE; - color: white; - cursor: pointer; -} -.area{ - text-align: center; - height: auto; - margin: auto; -} -.leftarea{ - float: left; - width: 50%; - height: auto; - position: relative; -} - -.rightarea{ - float: left; - width: 50%; - height: auto; -} -.table{ - width: auto; - height: auto; - margin: 0 auto; - -} -.span_title{ - width: 98%; - height: 36px; - margin-top: 4px; - line-height: 32px; - background-color: #00a1d6; - border: 1px solid #00a1d6; - border-radius: 20px; - color: #fff; - display: inline-block; - text-align: center; - font-size: 22px; - transition: .3s; - box-sizing: border-box; -} -.uplodNote{ - font-size: 10px; - color:#A1A1A1; -} - -a{ - text-decoration:none; -} - -/* wrapper */ -.leftarea>#wrapper { - position: absolute; top: 45px; left:0px; - width: 98%; - height: 100%; - background: - linear-gradient(#1a98ca, 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-rapidocr_onnxruntime>=1.3.0,<=2.0.0 -get_pypi_latest_version -wheel diff --git a/ocrweb/setup.py b/ocrweb/setup.py deleted file mode 100644 index 5921701..0000000 --- a/ocrweb/setup.py +++ /dev/null @@ -1,73 +0,0 @@ -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com -import sys -from pathlib import Path - -import setuptools -from get_pypi_latest_version import GetPyPiLatestVersion - - -def get_readme(): - root_dir = Path(__file__).resolve().parent.parent - readme_path = str(root_dir / "docs" / "doc_whl_rapidocr_web.md") - with open(readme_path, "r", encoding="utf-8") as f: - readme = f.read() - return readme - - -MODULE_NAME = "rapidocr_web" - -obtainer = GetPyPiLatestVersion() -latest_version = obtainer(MODULE_NAME) -VERSION_NUM = obtainer.version_add_one(latest_version, add_patch=True) - -# 优先提取commit message中的语义化版本号，如无，则自动加1 -if len(sys.argv) > 2: - match_str = " ".join(sys.argv[2:]) - matched_versions = obtainer.extract_version(match_str) - if matched_versions: - VERSION_NUM = matched_versions -sys.argv = sys.argv[:2] - -setuptools.setup( - name=MODULE_NAME, - version=VERSION_NUM, - platforms="Any", - description="A cross platform OCR Library based on OnnxRuntime.", - long_description=get_readme(), - long_description_content_type="text/markdown", - author="SWHL", - author_email="liekkaskono@163.com", - url="https://github.com/RapidAI/RapidOCR", - download_url="https://github.com/RapidAI/RapidOCR.git", - license="Apache-2.0", - include_package_data=True, - install_requires=["requests", "Flask>=2.1.0", "rapidocr_onnxruntime"], - packages=[ - MODULE_NAME, - f"{MODULE_NAME}.static.css", - f"{MODULE_NAME}.static.js", - f"{MODULE_NAME}.templates", - ], - package_data={"": ["*.ico", "*.css", "*.js", "*.html"]}, - keywords=[ - "ocr,text_detection,text_recognition,db,onnxruntime,paddleocr,openvino,rapidocr" - ], - classifiers=[ - "Programming Language :: Python :: 3.6", - "Programming Language :: Python :: 3.7", - "Programming Language :: Python :: 3.8", - "Programming Language :: Python :: 3.9", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Programming Language :: Python :: 3.13", - ], - python_requires=">=3.6", - entry_points={ - "console_scripts": [ - f"{MODULE_NAME}={MODULE_NAME}.ocrweb:main", - ], - }, -) diff --git a/ocrweb_multi/README.md b/ocrweb_multi/README.md deleted file mode 100644 index 4ca1050..0000000 --- a/ocrweb_multi/README.md +++ /dev/null @@ -1 +0,0 @@ -### See [Documentation](https://rapidai.github.io/RapidOCRDocs/main/install_usage/rapidocr_web/ocrweb_multi/) diff --git a/ocrweb_multi/assets/ocr_web_multi.jpg b/ocrweb_multi/assets/ocr_web_multi.jpg deleted file mode 100644 index 016de79..0000000 Binary files a/ocrweb_multi/assets/ocr_web_multi.jpg and /dev/null differ diff --git a/ocrweb_multi/build.py b/ocrweb_multi/build.py deleted file mode 100644 index 5b09f91..0000000 --- a/ocrweb_multi/build.py +++ /dev/null @@ -1,21 +0,0 @@ -import os -import shutil - -print("Compile ocrweb") -os.system("pyinstaller -y main.spec") - -print("Compile wrapper") -os.system("windres .\wrapper.rc -O coff -o wrapper.res") -os.system("gcc .\wrapper.c wrapper.res -o dist/ocrweb.exe") - -print("Copy config.yaml") -shutil.copy2("config.yaml", "dist/config.yaml") - -print("Copy models") -shutil.copytree("models", "dist/models", dirs_exist_ok=True) -os.remove("dist/models/.gitkeep") - -print("Pack to ocrweb.zip") -shutil.make_archive("ocrweb", "zip", "dist") - -print("Done") diff --git a/ocrweb_multi/config.yaml b/ocrweb_multi/config.yaml deleted file mode 100644 index e50b302..0000000 --- a/ocrweb_multi/config.yaml +++ /dev/null @@ -1,104 +0,0 @@ -server: - host: 127.0.0.1 - port: 8001 - # OCR接口Token, 为null时将跳过Token验证 - token: null - -global: - use_cuda: false - verbose: false - cuda_provider: - device_id: 0 - arena_extend_strategy: kNextPowerOfTwo - cudnn_conv_algo_search: EXHAUSTIVE - do_copy_in_default_stream: true - -# 模型配置 -models: - # 位置检测模型 - detect: - det_en: - path: models/en_PP-OCRv3_det_infer.onnx - config: &detectConfig - pre_process: - - class: DetResizeForTest - limit_side_len: 736 - limit_type: min - - class: NormalizeImage - std: [0.229, 0.224, 0.225] - mean: [0.485, 0.456, 0.406] - # 1 / 255 - scale: 0.00392156862745098 - order: hwc - - class: ToCHWImage - - class: KeepKeys - keep_keys: ["image", "shape"] - post_process: - thresh: 0.3 - box_thresh: 0.5 - max_candidates: 1000 - unclip_ratio: 1.6 - use_dilation: true - det_ch: - path: models/ch_PP-OCRv3_det_infer.onnx - config: *detectConfig - det_ml: - path: models/ch_PP-OCRv3_det_infer.onnx - config: *detectConfig - # 方向检测模型 - classify: - cls_ml: - path: models/ch_ppocr_mobile_v2.0_cls_infer.meta.onnx - config: - batch_size: 8 - score_thresh: 0.9 - # 文字识别模型 - recognize: - rec_ch: - path: models/ch_PP-OCRv3_rec_infer.meta.onnx - config: &recognizeConfig - batch_size: 8 - rec_cht: - path: models/chinese_cht_PP-OCRv3_rec_infer.meta.onnx - config: *recognizeConfig - rec_en: - path: models/en_PP-OCRv3_rec_infer.meta.onnx - config: *recognizeConfig - rec_ja: - path: models/japan_PP-OCRv3_rec_infer.meta.onnx - config: *recognizeConfig - -# 多语言配置 -languages: - ch: - name: 中文 - models: - detect: det_ch - classify: cls_ml - recognize: rec_ch - config: &languageConfig - text_score: 0.5 - use_angle_cls: true - verbose: false - min_height: 30 - cht: - name: 繁体中文 - models: - detect: det_ch - classify: cls_ml - recognize: rec_cht - config: *languageConfig - ja: - name: 日文 - models: - detect: det_ch - classify: cls_ml - recognize: rec_ja - config: *languageConfig - en: - name: 英文 - models: - detect: det_en - classify: cls_ml - recognize: rec_en - config: *languageConfig diff --git a/ocrweb_multi/main.py b/ocrweb_multi/main.py deleted file mode 100644 index 270f2a4..0000000 --- a/ocrweb_multi/main.py +++ /dev/null @@ -1,79 +0,0 @@ -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com -import logging -import cv2 -import numpy as np -from flask import Flask, send_file, request, make_response -from waitress import serve - - -from rapidocr.main import detect_recognize -from utils.config import conf -from utils.utils import tojson, parse_bool - -app = Flask(__name__) -log = logging.getLogger("app") -# 设置上传文件大小 -app.config["MAX_CONTENT_LENGTH"] = 3 * 1024 * 1024 - - -@app.route("/") -def index(): - return send_file("static/index.html") - - -def json_response(data, status=200): - return make_response(tojson(data), status, {"content-type": "application/json"}) - - -@app.route("/lang") -def get_languages(): - """返回可用语言列表""" - data = [ - {"code": key, "name": val["name"]} for key, val in conf["languages"].items() - ] - result = {"msg": "OK", "data": data} - log.info("Send langs: %s", data) - return json_response(result) - - -@app.route("/ocr", methods=["POST", "GET"]) -def ocr(): - """执行文字识别""" - if conf["server"].get("token"): - if request.values.get("token") != conf["server"]["token"]: - return json_response({"msg": "invalid token"}, status=403) - - lang = request.values.get("lang") or "ch" - detect = parse_bool(request.values.get("detect") or "true") - classify = parse_bool(request.values.get("classify") or "true") - - image_file = request.files.get("image") - if not image_file: - return json_response({"msg": "no image"}, 400) - nparr = np.frombuffer(image_file.stream.read(), np.uint8) - image = cv2.imdecode(nparr, cv2.IMREAD_COLOR) - log.info( - "Input: image %s, lang=%s, detect=%s, classify=%s", - image.shape, - lang, - detect, - classify, - ) - if image.ndim == 2: - image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) - result = detect_recognize(image, lang=lang, detect=detect, classify=classify) - log.info("OCR Done %s %s", result["ts"], len(result["results"])) - return json_response({"msg": "OK", "data": result}) - - -if __name__ == "__main__": - logging.basicConfig(level="INFO") - logging.getLogger("waitress").setLevel(logging.INFO) - if parse_bool(conf.get("debug", "0")): - # Debug - app.run(host=conf["server"]["host"], port=conf["server"]["port"], debug=True) - else: - # Deploy with waitress - serve(app, host=conf["server"]["host"], port=conf["server"]["port"]) diff --git a/ocrweb_multi/main.spec b/ocrweb_multi/main.spec deleted file mode 100644 index 8cd613c..0000000 --- a/ocrweb_multi/main.spec +++ /dev/null @@ -1,52 +0,0 @@ -# -*- mode: python ; coding: utf-8 -*- - - -block_cipher = None - - -a = Analysis( - ['main.py'], - pathex=[], - binaries=[], - datas=[ - ('static', 'static'), - ], - hiddenimports=[], - hookspath=[], - hooksconfig={}, - runtime_hooks=[], - excludes=[], - win_no_prefer_redirects=False, - win_private_assemblies=False, - cipher=block_cipher, - noarchive=False, -) -pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) - -exe = EXE( - pyz, - a.scripts, - [], - exclude_binaries=True, - name='main', - debug=False, - bootloader_ignore_signals=False, - strip=False, - upx=True, - console=True, - disable_windowed_traceback=False, - argv_emulation=False, - target_arch=None, - codesign_identity=None, - entitlements_file=None, -) -coll = COLLECT( - exe, - a.binaries, - a.zipfiles, - a.datas, - strip=False, - upx=True, - upx_exclude=[], - name='ocrweb', -) diff --git a/ocrweb_multi/models/.gitkeep b/ocrweb_multi/models/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/ocrweb_multi/rapidocr/__init__.py b/ocrweb_multi/rapidocr/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/ocrweb_multi/rapidocr/classify.py b/ocrweb_multi/rapidocr/classify.py deleted file mode 100644 index 5a3e4c4..0000000 --- a/ocrweb_multi/rapidocr/classify.py +++ /dev/null @@ -1,122 +0,0 @@ -# Copyright (c) 2020 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 copy -import math -import json -from typing import List - -import cv2 -import numpy as np -from utils.utils import OrtInferSession - - -class ClsPostProcess: - """Convert between text-label and text-index""" - - def __init__(self, label_list): - super(ClsPostProcess, self).__init__() - self.label_list = label_list - - def __call__(self, preds, label=None): - pred_idxs = preds.argmax(axis=1) - decode_out = [ - (self.label_list[idx], preds[i, idx]) for i, idx in enumerate(pred_idxs) - ] - if label is None: - return decode_out - - label = [(self.label_list[idx], 1.0) for idx in label] - return decode_out, label - - -class TextClassifier: - def __init__(self, path, config): - self.cls_batch_num = config["batch_size"] - self.cls_thresh = config["score_thresh"] - - session_instance = OrtInferSession(path) - self.session = session_instance.session - metamap = self.session.get_modelmeta().custom_metadata_map - - self.cls_image_shape = json.loads(metamap["shape"]) - - labels = json.loads(metamap["labels"]) - self.postprocess_op = ClsPostProcess(labels) - self.input_name = session_instance.get_input_name() - - def resize_norm_img(self, img): - img_c, img_h, img_w = self.cls_image_shape - h, w = img.shape[:2] - ratio = w / float(h) - if math.ceil(img_h * ratio) > img_w: - resized_w = img_w - else: - resized_w = int(math.ceil(img_h * ratio)) - - resized_image = cv2.resize(img, (resized_w, img_h)) - resized_image = resized_image.astype("float32") - if img_c == 1: - resized_image = resized_image / 255 - resized_image = resized_image[np.newaxis, :] - else: - resized_image = resized_image.transpose((2, 0, 1)) / 255 - - resized_image -= 0.5 - resized_image /= 0.5 - padding_im = np.zeros((img_c, img_h, img_w), dtype=np.float32) - padding_im[:, :, :resized_w] = resized_image - return padding_im - - def __call__(self, img_list: List[np.ndarray]): - if isinstance(img_list, np.ndarray): - img_list = [img_list] - - img_list = copy.deepcopy(img_list) - - # Calculate the aspect ratio of all text bars - width_list = [img.shape[1] / float(img.shape[0]) for img in img_list] - - # Sorting can speed up the cls process - indices = np.argsort(np.array(width_list)) - - img_num = len(img_list) - cls_res = [["", 0.0]] * img_num - batch_num = self.cls_batch_num - for beg_img_no in range(0, img_num, batch_num): - end_img_no = min(img_num, beg_img_no + batch_num) - max_wh_ratio = 0 - for ino in range(beg_img_no, end_img_no): - h, w = img_list[indices[ino]].shape[0:2] - wh_ratio = w * 1.0 / h - max_wh_ratio = max(max_wh_ratio, wh_ratio) - - norm_img_batch = [] - for ino in range(beg_img_no, end_img_no): - norm_img = self.resize_norm_img(img_list[indices[ino]]) - norm_img = norm_img[np.newaxis, :] - norm_img_batch.append(norm_img) - norm_img_batch = np.concatenate(norm_img_batch).astype(np.float32) - - onnx_inputs = {self.input_name: norm_img_batch} - prob_out = self.session.run(None, onnx_inputs)[0] - cls_result = self.postprocess_op(prob_out) - - for rno in range(len(cls_result)): - label, score = cls_result[rno] - cls_res[indices[beg_img_no + rno]] = [label, score] - if label == "180" and score > self.cls_thresh: - img_list[indices[beg_img_no + rno]] = cv2.rotate( - img_list[indices[beg_img_no + rno]], 1 - ) - return img_list, cls_res diff --git a/ocrweb_multi/rapidocr/detect.py b/ocrweb_multi/rapidocr/detect.py deleted file mode 100644 index a6810ac..0000000 --- a/ocrweb_multi/rapidocr/detect.py +++ /dev/null @@ -1,99 +0,0 @@ -# Copyright (c) 2020 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. -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com - -import numpy as np - -from utils.utils import OrtInferSession -from .detect_process import DBPostProcess, create_operators, transform - - -class TextDetector: - def __init__(self, path, config): - self.preprocess_op = create_operators(config["pre_process"]) - self.postprocess_op = DBPostProcess(**config["post_process"]) - - session_instance = OrtInferSession(path) - self.session = session_instance.session - self.input_name = session_instance.get_input_name() - - def __call__(self, img): - if img is None: - raise ValueError("img is None") - - ori_im_shape = img.shape[:2] - - data = {"image": img} - data = transform(data, self.preprocess_op) - img, shape_list = data - if img is None: - return None, 0 - - img = np.expand_dims(img, axis=0).astype(np.float32) - shape_list = np.expand_dims(shape_list, axis=0) - - preds = self.session.run(None, {self.input_name: img}) - - post_result = self.postprocess_op(preds[0], shape_list) - - dt_boxes = post_result[0]["points"] - dt_boxes = self.filter_tag_det_res(dt_boxes, ori_im_shape) - return dt_boxes - - def order_points_clockwise(self, pts): - """ - reference from: - https://github.com/jrosebr1/imutils/blob/master/imutils/perspective.py - sort the points based on their x-coordinates - """ - xSorted = pts[np.argsort(pts[:, 0]), :] - - # grab the left-most and right-most points from the sorted - # x-roodinate points - leftMost = xSorted[:2, :] - rightMost = xSorted[2:, :] - - # now, sort the left-most coordinates according to their - # y-coordinates so we can grab the top-left and bottom-left - # points, respectively - leftMost = leftMost[np.argsort(leftMost[:, 1]), :] - (tl, bl) = leftMost - - rightMost = rightMost[np.argsort(rightMost[:, 1]), :] - (tr, br) = rightMost - - rect = np.array([tl, tr, br, bl], dtype="float32") - return rect - - def clip_det_res(self, points, img_height, img_width): - for pno in range(points.shape[0]): - points[pno, 0] = int(min(max(points[pno, 0], 0), img_width - 1)) - points[pno, 1] = int(min(max(points[pno, 1], 0), img_height - 1)) - return points - - def filter_tag_det_res(self, dt_boxes, image_shape): - """对检测结果进行过滤""" - img_height, img_width = image_shape[:2] - dt_boxes_new = [] - for box in dt_boxes: - box = self.order_points_clockwise(box) - box = self.clip_det_res(box, img_height, img_width) - rect_width = int(np.linalg.norm(box[0] - box[1])) - rect_height = int(np.linalg.norm(box[0] - box[3])) - if rect_width <= 3 or rect_height <= 3: - continue - dt_boxes_new.append(box) - return dt_boxes_new diff --git a/ocrweb_multi/rapidocr/detect_process.py b/ocrweb_multi/rapidocr/detect_process.py deleted file mode 100644 index e941039..0000000 --- a/ocrweb_multi/rapidocr/detect_process.py +++ /dev/null @@ -1,379 +0,0 @@ -""" -# Copyright (c) 2020 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. -""" -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com -from copy import deepcopy -import sys - -import cv2 -import numpy as np -import pyclipper -import six -from shapely.geometry import Polygon - - -class DecodeImage: - """decode image""" - - def __init__(self, img_mode="RGB", channel_first=False): - self.img_mode = img_mode - self.channel_first = channel_first - - def __call__(self, data): - img = data["image"] - if six.PY2: - assert ( - type(img) is str and len(img) > 0 - ), "invalid input 'img' in DecodeImage" - else: - assert ( - type(img) is bytes and len(img) > 0 - ), "invalid input 'img' in DecodeImage" - - img = np.frombuffer(img, dtype="uint8") - img = cv2.imdecode(img, 1) - if img is None: - return None - - if self.img_mode == "GRAY": - img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) - elif self.img_mode == "RGB": - assert img.shape[2] == 3, f"invalid shape of image[{img.shape}]" - img = img[:, :, ::-1] - - if self.channel_first: - img = img.transpose((2, 0, 1)) - data["image"] = img - return data - - -class NormalizeImage: - """normalize image such as substract mean, divide std""" - - def __init__(self, scale=None, mean=None, std=None, order="chw"): - self.scale = np.float32(scale if scale is not None else 1.0 / 255.0) - mean = mean if mean is not None else [0.485, 0.456, 0.406] - std = std if std is not None else [0.229, 0.224, 0.225] - shape = (3, 1, 1) if order == "chw" else (1, 1, 3) - self.mean = np.array(mean).reshape(shape).astype("float32") - self.std = np.array(std).reshape(shape).astype("float32") - - def __call__(self, data): - img = np.array(data["image"]).astype(np.float32) - data["image"] = (img * self.scale - self.mean) / self.std - return data - - -class ToCHWImage: - """convert hwc image to chw image""" - - def __init__(self): - pass - - def __call__(self, data): - img = data["image"] - data["image"] = img.transpose((2, 0, 1)) - return data - - -class KeepKeys: - def __init__(self, keep_keys): - self.keep_keys = keep_keys - - def __call__(self, data): - data_list = [] - for key in self.keep_keys: - data_list.append(data[key]) - return data_list - - -class DetResizeForTest: - def __init__(self, **kwargs): - super(DetResizeForTest, self).__init__() - self.resize_type = 0 - if "image_shape" in kwargs: - self.image_shape = kwargs["image_shape"] - self.resize_type = 1 - elif "limit_side_len" in kwargs: - self.limit_side_len = kwargs["limit_side_len"] - self.limit_type = kwargs.get("limit_type", "min") - elif "resize_long" in kwargs: - self.resize_type = 2 - self.resize_long = kwargs.get("resize_long", 960) - else: - self.limit_side_len = 736 - self.limit_type = "min" - - def __call__(self, data): - img = data["image"] - src_h, src_w, _ = img.shape - - if self.resize_type == 0: - # img, shape = self.resize_image_type0(img) - img, [ratio_h, ratio_w] = self.resize_image_type0(img) - elif self.resize_type == 2: - img, [ratio_h, ratio_w] = self.resize_image_type2(img) - else: - # img, shape = self.resize_image_type1(img) - img, [ratio_h, ratio_w] = self.resize_image_type1(img) - data["image"] = img - data["shape"] = np.array([src_h, src_w, ratio_h, ratio_w]) - return data - - def resize_image_type1(self, img): - resize_h, resize_w = self.image_shape - ori_h, ori_w = img.shape[:2] # (h, w, c) - ratio_h = float(resize_h) / ori_h - ratio_w = float(resize_w) / ori_w - img = cv2.resize(img, (int(resize_w), int(resize_h))) - # return img, np.array([ori_h, ori_w]) - return img, [ratio_h, ratio_w] - - def resize_image_type0(self, img): - """ - resize image to a size multiple of 32 which is required by the network - args: - img(array): array with shape [h, w, c] - return(tuple): - img, (ratio_h, ratio_w) - """ - limit_side_len = self.limit_side_len - h, w, _ = img.shape - - # limit the max side - if self.limit_type == "max": - if max(h, w) > limit_side_len: - if h > w: - ratio = float(limit_side_len) / h - else: - ratio = float(limit_side_len) / w - else: - ratio = 1.0 - else: - if min(h, w) < limit_side_len: - if h < w: - ratio = float(limit_side_len) / h - else: - ratio = float(limit_side_len) / w - else: - ratio = 1.0 - resize_h = int(h * ratio) - resize_w = int(w * ratio) - - resize_h = int(round(resize_h / 32) * 32) - resize_w = int(round(resize_w / 32) * 32) - - try: - if int(resize_w) <= 0 or int(resize_h) <= 0: - return None, (None, None) - img = cv2.resize(img, (int(resize_w), int(resize_h))) - except: - print(img.shape, resize_w, resize_h) - sys.exit(0) - ratio_h = resize_h / float(h) - ratio_w = resize_w / float(w) - return img, [ratio_h, ratio_w] - - def resize_image_type2(self, img): - h, w, _ = img.shape - - resize_w = w - resize_h = h - - # Fix the longer side - if resize_h > resize_w: - ratio = float(self.resize_long) / resize_h - else: - ratio = float(self.resize_long) / resize_w - - resize_h = int(resize_h * ratio) - resize_w = int(resize_w * ratio) - - max_stride = 128 - resize_h = (resize_h + max_stride - 1) // max_stride * max_stride - resize_w = (resize_w + max_stride - 1) // max_stride * max_stride - img = cv2.resize(img, (int(resize_w), int(resize_h))) - ratio_h = resize_h / float(h) - ratio_w = resize_w / float(w) - - return img, [ratio_h, ratio_w] - - -def transform(data, ops=None): - """transform""" - if ops is None: - ops = [] - - for op in ops: - data = op(data) - if data is None: - return None - return data - - -def create_operators(op_param_list): - """ - create operators based on the config - """ - op_map = globals() - ops = [] - for args in op_param_list: - args = deepcopy(args) - op_class = op_map[args.pop("class")] - ops.append(op_class(**args)) - return ops - - -def draw_text_det_res(dt_boxes, img_path): - src_im = cv2.imread(img_path) - for box in dt_boxes: - box = np.array(box).astype(np.int32).reshape(-1, 2) - cv2.polylines(src_im, [box], True, color=(255, 255, 0), thickness=2) - return src_im - - -class DBPostProcess: - """The post process for Differentiable Binarization (DB).""" - - def __init__( - self, - thresh=0.3, - box_thresh=0.7, - max_candidates=1000, - unclip_ratio=2.0, - use_dilation=False, - ): - self.thresh = thresh - self.box_thresh = box_thresh - self.max_candidates = max_candidates - self.unclip_ratio = unclip_ratio - self.min_size = 3 - - if use_dilation: - self.dilation_kernel = np.array([[1, 1], [1, 1]]) - else: - self.dilation_kernel = None - - def boxes_from_bitmap(self, pred, _bitmap, dest_width, dest_height): - """ - _bitmap: single map with shape (1, H, W), - whose values are binarized as {0, 1} - """ - - bitmap = _bitmap - height, width = bitmap.shape - - outs = cv2.findContours( - (bitmap * 255).astype(np.uint8), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE - ) - if len(outs) == 3: - img, contours, _ = outs[0], outs[1], outs[2] - elif len(outs) == 2: - contours, _ = outs[0], outs[1] - - num_contours = min(len(contours), self.max_candidates) - - boxes = [] - scores = [] - for index in range(num_contours): - contour = contours[index] - points, sside = self.get_mini_boxes(contour) - if sside < self.min_size: - continue - points = np.array(points) - score = self.box_score_fast(pred, points.reshape(-1, 2)) - if self.box_thresh > score: - continue - - box = self.unclip(points).reshape(-1, 1, 2) - box, sside = self.get_mini_boxes(box) - if sside < self.min_size + 2: - continue - box = np.array(box) - - box[:, 0] = np.clip(np.round(box[:, 0] / width * dest_width), 0, dest_width) - box[:, 1] = np.clip( - np.round(box[:, 1] / height * dest_height), 0, dest_height - ) - boxes.append(box.astype(np.int16)) - scores.append(score) - return np.array(boxes, dtype=np.int16), scores - - def unclip(self, box): - unclip_ratio = self.unclip_ratio - poly = Polygon(box) - distance = poly.area * unclip_ratio / poly.length - offset = pyclipper.PyclipperOffset() - offset.AddPath(box, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON) - expanded = np.array(offset.Execute(distance)) - return expanded - - def get_mini_boxes(self, contour): - bounding_box = cv2.minAreaRect(contour) - points = sorted(list(cv2.boxPoints(bounding_box)), key=lambda x: x[0]) - - index_1, index_2, index_3, index_4 = 0, 1, 2, 3 - if points[1][1] > points[0][1]: - index_1 = 0 - index_4 = 1 - else: - index_1 = 1 - index_4 = 0 - if points[3][1] > points[2][1]: - index_2 = 2 - index_3 = 3 - else: - index_2 = 3 - index_3 = 2 - - box = [points[index_1], points[index_2], points[index_3], points[index_4]] - return box, min(bounding_box[1]) - - def box_score_fast(self, bitmap, _box): - h, w = bitmap.shape[:2] - box = _box.copy() - xmin = np.clip(np.floor(box[:, 0].min()).astype(int), 0, w - 1) - xmax = np.clip(np.ceil(box[:, 0].max()).astype(int), 0, w - 1) - ymin = np.clip(np.floor(box[:, 1].min()).astype(int), 0, h - 1) - ymax = np.clip(np.ceil(box[:, 1].max()).astype(int), 0, h - 1) - - mask = np.zeros((ymax - ymin + 1, xmax - xmin + 1), dtype=np.uint8) - box[:, 0] = box[:, 0] - xmin - box[:, 1] = box[:, 1] - ymin - cv2.fillPoly(mask, box.reshape(1, -1, 2).astype(np.int32), 1) - return cv2.mean(bitmap[ymin : ymax + 1, xmin : xmax + 1], mask)[0] - - def __call__(self, pred, shape_list): - pred = pred[:, 0, :, :] - segmentation = pred > self.thresh - - boxes_batch = [] - for batch_index in range(pred.shape[0]): - src_h, src_w, ratio_h, ratio_w = shape_list[batch_index] - if self.dilation_kernel is not None: - mask = cv2.dilate( - np.array(segmentation[batch_index]).astype(np.uint8), - self.dilation_kernel, - ) - else: - mask = segmentation[batch_index] - boxes, scores = self.boxes_from_bitmap( - pred[batch_index], mask, src_w, src_h - ) - - boxes_batch.append({"points": boxes}) - return boxes_batch diff --git a/ocrweb_multi/rapidocr/main.py b/ocrweb_multi/rapidocr/main.py deleted file mode 100644 index 016ebea..0000000 --- a/ocrweb_multi/rapidocr/main.py +++ /dev/null @@ -1,57 +0,0 @@ -# -*- encoding: utf-8 -*- -# @Author: SWHL -# @Contact: liekkaskono@163.com -import copy -from functools import lru_cache -from pathlib import Path - -import numpy as np -import cv2 - -from utils.config import conf -from rapidocr.rapid_ocr_api import RapidOCR - - -@lru_cache(maxsize=None) -def load_language_model(lang="ch"): - models = conf["languages"][lang] - print("model", models) - return RapidOCR(models) - - -def detect_recognize(image, lang="ch", detect=True, classify=True): - model = load_language_model(lang) - results, ts = model(image, detect=detect, classify=classify) - ts["total"] = sum(ts.values()) - return {"ts": ts, "results": results} - - -def check_and_read_gif(img_path): - if Path(img_path).suffix.lower() == "gif": - gif = cv2.VideoCapture(img_path) - ret, frame = gif.read() - if not ret: - print("Cannot read {}. This gif image maybe corrupted.") - return None, False - if len(frame.shape) == 2 or frame.shape[-1] == 1: - frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2RGB) - imgvalue = frame[:, :, ::-1] - return imgvalue, True - return None, False - - -def draw_text_det_res(dt_boxes, raw_im): - src_im = copy.deepcopy(raw_im) - for i, box in enumerate(dt_boxes): - box = np.array(box).astype(np.int32).reshape(-1, 2) - cv2.polylines(src_im, [box], True, color=(0, 0, 255), thickness=1) - cv2.putText( - src_im, - str(i), - (int(box[0][0]), int(box[0][1])), - cv2.FONT_HERSHEY_SIMPLEX, - 0.5, - (0, 0, 0), - 2, - ) - return src_im diff --git a/ocrweb_multi/rapidocr/rapid_ocr_api.py b/ocrweb_multi/rapidocr/rapid_ocr_api.py deleted file mode 100644 index d2710a9..0000000 --- a/ocrweb_multi/rapidocr/rapid_ocr_api.py +++ /dev/null @@ -1,160 +0,0 @@ -# !/usr/bin/env python -# -*- encoding: utf-8 -*- -import copy - -import cv2 -import numpy as np - -from functools import lru_cache -from utils.config import conf -from utils.utils import Ticker -from .classify import TextClassifier -from .detect import TextDetector -from .recognize import TextRecognizer - - -def get_rotate_crop_image(img, points): - """根据box定义, 从图像中截取相应的部分, 通过透视变换转换为标准长方形图像""" - img_crop_width = int( - max( - np.linalg.norm(points[0] - points[1]), - np.linalg.norm(points[2] - points[3]), - ) - ) - img_crop_height = int( - max( - np.linalg.norm(points[0] - points[3]), - np.linalg.norm(points[1] - points[2]), - ) - ) - pts_std = np.float32( - [ - [0, 0], - [img_crop_width, 0], - [img_crop_width, img_crop_height], - [0, img_crop_height], - ] - ) - transform = cv2.getPerspectiveTransform(points, pts_std) - dst_img = cv2.warpPerspective( - img, - transform, - (img_crop_width, img_crop_height), - borderMode=cv2.BORDER_REPLICATE, - flags=cv2.INTER_CUBIC, - ) - dst_img_height, dst_img_width = dst_img.shape[:2] - # 将竖向的文字方向转为横向, 仅当 高>1.5*宽 时进行转换 - if dst_img_height * 1.0 / dst_img_width >= 1.5: - dst_img = np.rot90(dst_img) - return dst_img - - -@lru_cache(maxsize=None) -def load_onnx_model(step, name): - model_config = conf["models"][step][name] - model_class = { - "detect": TextDetector, - "classify": TextClassifier, - "recognize": TextRecognizer, - }[step] - return model_class(model_config["path"], model_config.get("config")) - - -class RapidOCR: - def __init__(self, config): - super(RapidOCR).__init__() - self.config = config - self.text_score = config["config"]["text_score"] - self.min_height = config["config"]["min_height"] - - models = config["models"] - self.text_detector = load_onnx_model("detect", models["detect"]) - self.text_recognizer = load_onnx_model("recognize", models["recognize"]) - self.text_cls = load_onnx_model("classify", models["classify"]) - - def __call__(self, img: np.ndarray, detect=True, classify=True): - ticker = Ticker() - h, w = img.shape[:2] - if not detect or h < self.min_height: - dt_boxes, img_crop_list = self.get_boxes_img_without_det(img, h, w) - ticker.tick("detect") - else: - dt_boxes = self.text_detector(img) - ticker.tick("detect") - - if dt_boxes is None or len(dt_boxes) < 1: - return [], ticker.maps - if conf["global"]["verbose"]: - print(f"boxes num: {len(dt_boxes)}") - - dt_boxes = self.sorted_boxes(dt_boxes) - - img_crop_list = self.get_crop_img_list(img, dt_boxes) - ticker.tick("post-detect") - - if classify: - # 进行子图像角度修正 - img_crop_list, _ = self.text_cls(img_crop_list) - ticker.tick("classify") - if conf["global"]["verbose"]: - print(f"cls num: {len(img_crop_list)}") - - recog_result = self.text_recognizer(img_crop_list) - ticker.tick("recognize") - if conf["global"]["verbose"]: - print(f"rec_res num: {len(recog_result)}") - - results = self.filter_boxes_rec_by_score(dt_boxes, recog_result) - ticker.tick("post-recognize") - return results, ticker.maps - - def get_boxes_img_without_det(self, img, h, w): - x0, y0, x1, y1 = 0, 0, w, h - dt_boxes = np.array([[x0, y0], [x1, y0], [x1, y1], [x0, y1]]) - dt_boxes = dt_boxes[np.newaxis, ...] - img_crop_list = [img] - return dt_boxes, img_crop_list - - def get_crop_img_list(self, img, dt_boxes): - img_crop_list = [] - for box in dt_boxes: - tmp_box = copy.deepcopy(box) - img_crop = get_rotate_crop_image(img, tmp_box) - img_crop_list.append(img_crop) - return img_crop_list - - @staticmethod - def sorted_boxes(dt_boxes): - """对文本框检测结果进行排序, 调整为从上到下、从左到右 - - args: - dt_boxes(array): detected text boxes with shape [4, 2] - return: - sorted boxes(array) with shape [4, 2] - """ - - class AlignBox: - def __init__(self, data) -> None: - self.data = data - self.x = data[0][0] - self.y = data[0][1] - - def __lt__(self, other: "AlignBox"): - dy = self.y - other.y - # y差距小于10, 视为相等, 根据x排序 - if abs(dy) < 10: - return self.x < other.x - # 否则根据y排序 - return dy < 0 - - align_boxes = sorted([AlignBox(b) for b in dt_boxes]) - return [b.data for b in align_boxes] - - def filter_boxes_rec_by_score(self, dt_boxes, rec_res): - results = [] - for box, rec_reuslt in zip(dt_boxes, rec_res): - text, score = rec_reuslt - if score >= self.text_score: - results.append({"box": box, "text": text, "score": score}) - return results diff --git a/ocrweb_multi/rapidocr/recognize.py b/ocrweb_multi/rapidocr/recognize.py deleted file mode 100644 index ff79e25..0000000 --- a/ocrweb_multi/rapidocr/recognize.py +++ /dev/null @@ -1,158 +0,0 @@ -# Copyright (c) 2020 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 json -import math -from typing import List - -import cv2 -import numpy as np - -from utils.utils import OrtInferSession - - -class CTCLabelDecode: - """Convert between text-label and text-index""" - - def __init__(self, characters: List[str]): - super(CTCLabelDecode, self).__init__() - - self.characters = characters - self.characters.append(" ") - - dict_character = self.add_special_char(self.characters) - self.character = dict_character - - self.dict = {} - for i, char in enumerate(dict_character): - self.dict[char] = i - - def __call__(self, preds, label=None): - preds_idx = preds.argmax(axis=2) - preds_prob = preds.max(axis=2) - text = self.decode(preds_idx, preds_prob, is_remove_duplicate=True) - if label is None: - return text - label = self.decode(label) - return text, label - - def add_special_char(self, dict_character): - dict_character = ["blank"] + dict_character - return dict_character - - def get_ignored_tokens(self): - return [0] # for ctc blank - - def decode(self, text_index, text_prob=None, is_remove_duplicate=False): - """convert text-index into text-label.""" - - result_list = [] - ignored_tokens = self.get_ignored_tokens() - batch_size = len(text_index) - for batch_idx in range(batch_size): - char_list = [] - conf_list = [] - for idx in range(len(text_index[batch_idx])): - if text_index[batch_idx][idx] in ignored_tokens: - continue - if is_remove_duplicate: - # only for predict - if ( - idx > 0 - and text_index[batch_idx][idx - 1] == text_index[batch_idx][idx] - ): - continue - char_list.append(self.character[int(text_index[batch_idx][idx])]) - if text_prob is not None: - conf_list.append(text_prob[batch_idx][idx]) - else: - conf_list.append(1) - # avoid `Mean of empty slice.` warning - score = np.mean(conf_list) if conf_list else 0 - text = "".join(char_list) - result_list.append((text, score)) - return result_list - - -class TextRecognizer: - def __init__(self, path, config): - self.rec_batch_num = config.get("rec_batch_num", 6) - - session_instance = OrtInferSession(path) - self.session = session_instance.session - - metamap = session_instance.session.get_modelmeta().custom_metadata_map - chars = metamap["dictionary"].splitlines() - self.postprocess_op = CTCLabelDecode(chars) - self.rec_image_shape = json.loads(metamap["shape"]) - self.input_name = session_instance.get_input_name() - - def resize_norm_img(self, img, max_wh_ratio): - img_channel, img_height, img_width = self.rec_image_shape - assert img_channel == img.shape[2] - - img_width = int((32 * max_wh_ratio)) - max_wh_ratio = 1 - - h, w = img.shape[:2] - ratio = w / float(h) - if math.ceil(img_height * ratio) > img_width: - resized_w = img_width - else: - resized_w = int(math.ceil(img_height * ratio)) - - resized_image = cv2.resize(img, (resized_w, img_height)) - resized_image = resized_image.astype("float32") - resized_image = resized_image.transpose((2, 0, 1)) / 255 - resized_image -= 0.5 - resized_image /= 0.5 - - padding_im = np.zeros((img_channel, img_height, img_width), dtype=np.float32) - padding_im[:, :, 0:resized_w] = resized_image - return padding_im - - def __call__(self, img_list: List[np.ndarray]): - if isinstance(img_list, np.ndarray): - img_list = [img_list] - - # Calculate the aspect ratio of all text bars - width_list = [img.shape[1] / float(img.shape[0]) for img in img_list] - - # Sorting can speed up the recognition process - indices = np.argsort(np.array(width_list)) - - img_num = len(img_list) - rec_res = [["", 0.0]] * img_num - - batch_num = self.rec_batch_num - for beg_img_no in range(0, img_num, batch_num): - end_img_no = min(img_num, beg_img_no + batch_num) - max_wh_ratio = 0 - for ino in range(beg_img_no, end_img_no): - h, w = img_list[indices[ino]].shape[0:2] - wh_ratio = w * 1.0 / h - max_wh_ratio = max(max_wh_ratio, wh_ratio) - - norm_img_batch = [] - for ino in range(beg_img_no, end_img_no): - norm_img = self.resize_norm_img(img_list[indices[ino]], max_wh_ratio) - norm_img_batch.append(norm_img[np.newaxis, :]) - norm_img_batch = np.concatenate(norm_img_batch).astype(np.float32) - - onnx_inputs = {self.input_name: norm_img_batch} - preds = self.session.run(None, onnx_inputs)[0] - rec_result = self.postprocess_op(preds) - - for rno in range(len(rec_result)): - rec_res[indices[beg_img_no + rno]] = rec_result[rno] - return rec_res diff --git a/ocrweb_multi/requirements.txt b/ocrweb_multi/requirements.txt deleted file mode 100644 index b84c321..0000000 --- a/ocrweb_multi/requirements.txt +++ /dev/null @@ -1,9 +0,0 @@ -onnxruntime>=1.7.0 -opencv-python-headless==4.5.4.60 -six>=1.15.0 -pyclipper>=1.2.1 -numpy>=1.19.1 -Shapely>=1.7.1 -Flask>=2.1.2 -PyYAML -waitress diff --git a/ocrweb_multi/static/css/main.css b/ocrweb_multi/static/css/main.css deleted file mode 100644 index 23bbe1b..0000000 --- a/ocrweb_multi/static/css/main.css +++ /dev/null @@ -1,143 +0,0 @@ -html { - height: 100%; - margin: 0; -} - -body { - background-color: #ebedef; - min-height: 100%; - margin: 0; -} - -.btn-gen { - background-color: #00a1d6; - text-align: center; - border-radius: 18px; - margin: 0 5px 0 5px; - font-size: 15px; - padding: 5px 10px; - height: 20px; - min-width: 120px; - text-transform: uppercase; - color: #fff; - border: none; -} - -.btn-gen:hover, -.btn-gen:focus { - border-color: #23AAEE; - background-color: #23AAEE; - color: white; - cursor: pointer; -} - -.row { - margin: 15px; -} - -.small { - font-size: 0.8em; -} - -.verysmall { - font-size: 0.5em; -} - -.area { - text-align: center; - height: auto; - margin: auto; -} - -.leftarea { - float: left; - width: 50%; - height: auto; - position: relative; -} - -.rightarea { - float: left; - width: 50%; - height: auto; - overflow-y: auto; -} - -.table { - width: auto; - height: auto; - margin: 0 auto; - -} - -.span_title { - width: 98%; - height: 36px; - margin-top: 4px; - line-height: 32px; - background-color: #00a1d6; - border: 1px solid #00a1d6; - border-radius: 20px; - color: #fff; - display: inline-block; - text-align: center; - font-size: 22px; - transition: .3s; - box-sizing: border-box; - cursor: default; -} - -.uplodNote { - font-size: 10px; - color: #A1A1A1; -} - -a { - text-decoration: none; -} - -#input-hint { - margin: auto; - cursor: pointer; - -} - -#result_view { - position: relative; - width: 95%; - margin: auto; -} - -#result_view canvas { - width: 100%; - height: 100%; -} - -/* wrapper */ -#wrapper { - position: absolute; - top: 0; - left: 0; - width: 100%; - height: 100%; - background: - linear-gradient(#1a98ca, #1a98ca), - linear-gradient(90deg, #ffffff33 1px, transparent 0, transparent 19px), - linear-gradient(#ffffff33 1px, transparent 0, transparent 19px), - linear-gradient(transparent, #1a98ca); - background-size: 100% 1.5%, 10% 100%, 100% 8%, 100% 100%; - background-repeat: no-repeat, repeat, repeat, no-repeat; - background-position: 0% 100%, 0 0, 0 0, 0 0; - /* 初始位置 */ - clip-path: polygon(0% 0%, 100% 0%, 100% 1.5%, 0% 1.5%); - /* 添加动画效果 */ - animation: move 1s infinite linear; -} - -@keyframes move { - to { - background-position: 0 100%, 0 0, 0 0, 0 0; - /* 终止位置 */ - clip-path: polygon(0% 0%, 100% 0%, 100% 100%, 0% 100%); - } -} \ No newline at end of file diff --git a/ocrweb_multi/static/favicon.ico b/ocrweb_multi/static/favicon.ico deleted file mode 100644 index b30495c..0000000 Binary files a/ocrweb_multi/static/favicon.ico and /dev/null differ diff --git a/ocrweb_multi/static/hint.svg b/ocrweb_multi/static/hint.svg deleted file mode 100644 index f651b0d..0000000 --- a/ocrweb_multi/static/hint.svg +++ /dev/null @@ -1,4 +0,0 @@ - - 未选择图片 - \ No newline at end of file diff --git a/ocrweb_multi/static/index.html b/ocrweb_multi/static/index.html deleted file mode 100644 index 847206c..0000000 --- a/ocrweb_multi/static/index.html +++ /dev/null @@ -1,233 +0,0 @@ - - - - - - RapidOCR Demo - - - - - - -
-

- Rapid🗲OCR Demo -   - 欢迎Star  - 了解Demo -

-
-
- -
- 选择图片 支持拖拽/粘贴/点击; 支持常见图片格式; 大小不超过3M -
-
- 选择语言: - -
-
-
-
- 文 本 检 测 结 果

-
- 目标图片 - - -
-
-
- 文 本 识 别 结 果 -

-
-
-
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