49 lines
2.1 KiB
Plaintext
49 lines
2.1 KiB
Plaintext
@version 1
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# OCR models. Each [model NAME] names the files it needs from this folder (fetch_models.jai
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# downloads them) and how it is run; ocr_create takes the NAME. Changes apply to engines created
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# after the file is saved.
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#
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# title shown to people
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# detector, recognizer, dictionary file names, quoted
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# textline_ori optional: a text line orientation classifier's file name, quoted; lines it
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# finds upside down are read both ways and the more confident reading kept
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# det_max_side wider images are scaled down to this width for detection (px)
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# det_tile_height taller images are detected in overlapping strips this high (px, after scaling)
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# det_threshold a pixel is text when its probability is above this
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# box_threshold a text region is kept when its mean probability is at least this
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# unclip_ratio how far each region is grown, as DB detection networks expect
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# rec_height each text line is scaled to this height for recognition (px)
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# rec_batch_gpu text lines recognized together in one run, on the GPU
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# rec_batch_cpu the same on the CPU, where one at a time is fastest: a batch is padded to its
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# widest line, and the padding costs time and changes what is read a little
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[model ppocr-v5-mobile]
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title: "PP-OCRv5 mobile (light)"
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detector: "ch_PP-OCRv5_det_mobile.onnx"
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recognizer: "ch_PP-OCRv5_rec_mobile.onnx"
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dictionary: "ppocrv5_dict.txt"
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textline_ori: "ch_PP-LCNet_x0_25_textline_ori_cls_mobile.onnx"
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det_max_side: 2560
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det_tile_height: 1536
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det_threshold: 0.3
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box_threshold: 0.6
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unclip_ratio: 1.5
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rec_height: 48
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rec_batch_gpu: 16
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rec_batch_cpu: 1
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[model ppocr-v5-server]
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title: "PP-OCRv5 server (heavy)"
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detector: "ch_PP-OCRv5_det_server.onnx"
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recognizer: "ch_PP-OCRv5_rec_server.onnx"
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dictionary: "ppocrv5_dict.txt"
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textline_ori: "ch_PP-LCNet_x0_25_textline_ori_cls_mobile.onnx"
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det_max_side: 2560
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det_tile_height: 1536
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det_threshold: 0.3
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box_threshold: 0.6
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unclip_ratio: 1.5
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rec_height: 48
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rec_batch_gpu: 8
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rec_batch_cpu: 1
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