Added project files

.gitignore

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+/.idea/

Dockerfile

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+FROM python:3.9.10-slim
+
+RUN apt-get update -y && apt-get upgrade -y && apt-get install -y pkg-config build-essential libudev-dev libssl-dev
+RUN apt install -y wget bzip2 ca-certificates nginx supervisor libglib2.0-0 libxext6 libsm6 libxrender1 libgl1-mesa-glx libzbar0 build-essential libpcre3 git mercurial subversion locales procps
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN useradd -m -u 1000 user
+USER user
+
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+WORKDIR $HOME/app
+
+COPY --chown=user . $HOME/app
+
+RUN pip install paddlepaddle -i https://pypi.tuna.tsinghua.edu.cn/simple
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+RUN git clone https://github.com/PaddlePaddle/PaddleOCR
+
+CMD ["python3", "app.py"]

app.py

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+import os
+import glob
+import gradio as gr
+import yaml
+from utils import load_config, get_args, download_model
+from ocr import OCR
+import PIL
+import numpy as np
+
+config = load_config()
+download_model('inference.pdmodel', config['inference.pdmodel'])
+download_model('inference.pdiparams', config['inference.pdiparams'])
+
+model = OCR(get_args(config['svtr_nums']['params']))
+
+def process_image(image):
+  img = image.convert('RGB')
+  img = np.array(img)
+  val, conf = model(img)
+  return val, conf
+
+title = "Interactive demo: SVTR-Tiny"
+description = "Demo for SVTR-Tiny. The model supports only digit recognition. To use it, simply upload a (single-text line) image or use one of the example images below and click 'submit'. Results will show up in a few seconds."
+article = "<p style='text-align: center'><a href='https://arxiv.org/pdf/2205.00159.pdf'>SVTR: Scene Text Recognition with a Single Visual Model</a> | <a href='https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/doc/doc_en/algorithm_rec_svtr_en.md'>Github Repo</a></p>"
+
+demo = gr.Interface(fn=process_image,
+                     inputs=gr.inputs.Image(type="pil"),
+                     outputs=gr.outputs.Textbox(),
+                     title=title,
+                     description=description,
+                     article=article,
+                     examples=glob.glob('examples/*.jpeg'))
+
+demo.launch(server_name="0.0.0.0", server_port=7860, debug=True)

configs/model.yaml

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+svtr_nums:
+  params:
+    max_text_length: 13
+    rec_algorithm: SVTR
+    rec_image_shape: '3,64,256'
+    rec_char_dict_path: 'configs/nums_dict.txt'
+    use_space_char: False
+    rec_model_dir: 'weights'
+
+inference.pdmodel: https://drive.google.com/file/d/1sTD0klxkin81MDMzXIsO-POWuESD3Ebh/view?usp=sharing
+inference.pdiparams: https://drive.google.com/file/d/1fdRoRLFi1S0NnD3FLP7Mpc_PbrEJ4JSm/view?usp=sharing
+
+

configs/nums_dict.txt

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+0
+1
+2
+3
+4
+5
+6
+7
+8
+9

ocr.py

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+import os
+import sys
+
+sys.path.append('PaddleOCR')
+os.environ["FLAGS_allocator_strategy"] = 'auto_growth'
+
+from PaddleOCR.tools.infer.predict_rec import TextRecognizer
+
+
+class OCR:
+
+    def __init__(self, *args):
+        self.ocr_model = TextRecognizer(*args)
+
+    def __call__(self, img):
+        [rec_res], _ = self.ocr_model([img])
+        return rec_res[0], rec_res[1]
+
+
+
+
+

requirements.txt

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+shapely
+scikit-image
+imgaug
+pyclipper
+lmdb
+tqdm
+numpy
+visualdl
+rapidfuzz
+opencv-python<=4.6.0.66
+opencv-contrib-python<=4.6.0.66
+cython
+lxml
+premailer
+openpyxl
+attrdict
+PyMuPDF<1.21.0
+Pillow>=10.0.0
+pyyaml
+gdown
+gradio
+paddleocr>=2.0.1
+

utils.py

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+import argparse
+import yaml
+import gdown
+import os
+
+
+def load_config(path='configs/model.yaml'):
+    with open(path, 'r', encoding='utf-8') as f:
+        return yaml.load(f, Loader=yaml.FullLoader)
+
+
+def str2bool(v):
+    return v.lower() in ("true", "yes", "t", "y", "1")
+
+
+def init_args():
+    parser = argparse.ArgumentParser()
+    # params for prediction engine
+    parser.add_argument("--use_gpu", type=str2bool, default=False)
+    parser.add_argument("--use_xpu", type=str2bool, default=False)
+    parser.add_argument("--use_npu", type=str2bool, default=False)
+    parser.add_argument("--ir_optim", type=str2bool, default=True)
+    parser.add_argument("--use_tensorrt", type=str2bool, default=False)
+    parser.add_argument("--min_subgraph_size", type=int, default=15)
+    parser.add_argument("--precision", type=str, default="fp32")
+    parser.add_argument("--gpu_mem", type=int, default=500)
+    parser.add_argument("--gpu_id", type=int, default=0)
+
+    # params for text detector
+    parser.add_argument("--image_dir", type=str)
+    parser.add_argument("--page_num", type=int, default=0)
+    parser.add_argument("--det_algorithm", type=str, default='DB')
+    parser.add_argument("--det_model_dir", type=str)
+    parser.add_argument("--det_limit_side_len", type=float, default=960)
+    parser.add_argument("--det_limit_type", type=str, default='max')
+    parser.add_argument("--det_box_type", type=str, default='quad')
+
+    # DB parmas
+    parser.add_argument("--det_db_thresh", type=float, default=0.3)
+    parser.add_argument("--det_db_box_thresh", type=float, default=0.6)
+    parser.add_argument("--det_db_unclip_ratio", type=float, default=1.5)
+    parser.add_argument("--max_batch_size", type=int, default=10)
+    parser.add_argument("--use_dilation", type=str2bool, default=False)
+    parser.add_argument("--det_db_score_mode", type=str, default="fast")
+
+    # EAST parmas
+    parser.add_argument("--det_east_score_thresh", type=float, default=0.8)
+    parser.add_argument("--det_east_cover_thresh", type=float, default=0.1)
+    parser.add_argument("--det_east_nms_thresh", type=float, default=0.2)
+
+    # SAST parmas
+    parser.add_argument("--det_sast_score_thresh", type=float, default=0.5)
+    parser.add_argument("--det_sast_nms_thresh", type=float, default=0.2)
+
+    # PSE parmas
+    parser.add_argument("--det_pse_thresh", type=float, default=0)
+    parser.add_argument("--det_pse_box_thresh", type=float, default=0.85)
+    parser.add_argument("--det_pse_min_area", type=float, default=16)
+    parser.add_argument("--det_pse_scale", type=int, default=1)
+
+    # FCE parmas
+    parser.add_argument("--scales", type=list, default=[8, 16, 32])
+    parser.add_argument("--alpha", type=float, default=1.0)
+    parser.add_argument("--beta", type=float, default=1.0)
+    parser.add_argument("--fourier_degree", type=int, default=5)
+
+    # params for text recognizer
+    parser.add_argument("--rec_algorithm", type=str, default='SVTR_LCNet')
+    parser.add_argument("--rec_model_dir", type=str)
+    parser.add_argument("--rec_image_inverse", type=str2bool, default=True)
+    parser.add_argument("--rec_image_shape", type=str, default="3, 48, 320")
+    parser.add_argument("--rec_batch_num", type=int, default=6)
+    parser.add_argument("--max_text_length", type=int, default=25)
+    parser.add_argument(
+        "--rec_char_dict_path",
+        type=str,
+        default="./ppocr/utils/ppocr_keys_v1.txt")
+    parser.add_argument("--use_space_char", type=str2bool, default=True)
+    parser.add_argument(
+        "--vis_font_path", type=str, default="./doc/fonts/simfang.ttf")
+    parser.add_argument("--drop_score", type=float, default=0.5)
+
+    # params for e2e
+    parser.add_argument("--e2e_algorithm", type=str, default='PGNet')
+    parser.add_argument("--e2e_model_dir", type=str)
+    parser.add_argument("--e2e_limit_side_len", type=float, default=768)
+    parser.add_argument("--e2e_limit_type", type=str, default='max')
+
+    # PGNet parmas
+    parser.add_argument("--e2e_pgnet_score_thresh", type=float, default=0.5)
+    parser.add_argument(
+        "--e2e_char_dict_path", type=str, default="./ppocr/utils/ic15_dict.txt")
+    parser.add_argument("--e2e_pgnet_valid_set", type=str, default='totaltext')
+    parser.add_argument("--e2e_pgnet_mode", type=str, default='fast')
+
+    # params for text classifier
+    parser.add_argument("--use_angle_cls", type=str2bool, default=False)
+    parser.add_argument("--cls_model_dir", type=str)
+    parser.add_argument("--cls_image_shape", type=str, default="3, 48, 192")
+    parser.add_argument("--label_list", type=list, default=['0', '180'])
+    parser.add_argument("--cls_batch_num", type=int, default=6)
+    parser.add_argument("--cls_thresh", type=float, default=0.9)
+
+    parser.add_argument("--enable_mkldnn", type=str2bool, default=False)
+    parser.add_argument("--cpu_threads", type=int, default=10)
+    parser.add_argument("--use_pdserving", type=str2bool, default=False)
+    parser.add_argument("--warmup", type=str2bool, default=False)
+
+    # SR parmas
+    parser.add_argument("--sr_model_dir", type=str)
+    parser.add_argument("--sr_image_shape", type=str, default="3, 32, 128")
+    parser.add_argument("--sr_batch_num", type=int, default=1)
+
+    #
+    parser.add_argument(
+        "--draw_img_save_dir", type=str, default="./inference_results")
+    parser.add_argument("--save_crop_res", type=str2bool, default=False)
+    parser.add_argument("--crop_res_save_dir", type=str, default="./output")
+
+    # multi-process
+    parser.add_argument("--use_mp", type=str2bool, default=False)
+    parser.add_argument("--total_process_num", type=int, default=1)
+    parser.add_argument("--process_id", type=int, default=0)
+
+    parser.add_argument("--benchmark", type=str2bool, default=False)
+    parser.add_argument("--save_log_path", type=str, default="./log_output/")
+
+    parser.add_argument("--show_log", type=str2bool, default=True)
+    parser.add_argument("--use_onnx", type=str2bool, default=False)
+    return parser
+
+
+def get_args(model_params):
+    print(model_params)
+    args, _ = init_args().parse_known_args()
+    for key, val in model_params.items():
+        setattr(args, key, val)
+    return args
+
+
+def download_model(filename, url, save_path='weights'):
+    gdown.download(url=url, output=os.path.join(save_path, filename), quiet=False, fuzzy=True, use_cookies=False)