This blog stems from my curiosity to research the performance of Paddle-OCR, a robust and versatile optical character recognition (OCR) toolkit. Paddle-OCR offers an array of features and capabilities for extracting text from images and documents, and I was eager to explore its capabilities and limitations.

config_dict = {
    "alpha": 1.0,
    "benchmark": False,
    "beta": 1.0,
    "cls_batch_num": 6,
    "cls_image_shape": '3, 48, 192',
    "cls_model_dir": '/Users/prajendr/.paddleocr/whl/cls/ch_ppocr_mobile_v2.0_cls_infer',
    "cls_thresh": 0.9,
    "cpu_threads": 10,
    "crop_res_save_dir": './output',
    "det": True,
    "det_algorithm": 'DB',
    "det_box_type": 'quad',
    "det_db_box_thresh": 0.6,
    "det_db_score_mode": 'fast',
    "det_db_thresh": 0.3,
    "det_db_unclip_ratio": 1.5,
    "det_east_cover_thresh": 0.1,
    "det_east_nms_thresh": 0.2,
    "det_east_score_thresh": 0.8,
    "det_limit_side_len": 960,
    "det_limit_type": 'max',
    "det_model_dir": '/Users/prajendr/.paddleocr/whl/det/en/en_PP-OCRv3_det_infer',
    "det_pse_box_thresh": 0.85,
    "det_pse_min_area": 16,
    "det_pse_scale": 1,
    "det_pse_thresh": 0,
    "det_sast_nms_thresh": 0.2,
    "det_sast_score_thresh": 0.5,
    "draw_img_save_dir": './inference_results',
    "drop_score": 0.5,
    "e2e_algorithm": 'PGNet',
    "e2e_char_dict_path": './ppocr/utils/ic15_dict.txt',
    "e2e_limit_side_len": 768,
    "e2e_limit_type": 'max',
    "e2e_model_dir": None,
    "e2e_pgnet_mode": 'fast',
    "e2e_pgnet_score_thresh": 0.5,
    "e2e_pgnet_valid_set": 'totaltext',
    "enable_mkldnn": False,
    "fourier_degree": 5,
    "gpu_mem": 500,
    "help": '==SUPPRESS==',
    "image_dir": None,
    "image_orientation": False,
    "ir_optim": True,
    "kie_algorithm": 'LayoutXLM',
    "label_list": ['0', '180'],
    "lang": 'en',
    "layout": True,
    "layout_dict_path": None,
    "layout_model_dir": None,
    "layout_nms_threshold": 0.5…