{"id":27783,"date":"2026-03-04T10:20:52","date_gmt":"2026-03-04T01:20:52","guid":{"rendered":"https:\/\/nbsigh2.com\/?p=27783"},"modified":"2026-03-05T07:51:21","modified_gmt":"2026-03-04T22:51:21","slug":"ndlocr-lite-gui","status":"publish","type":"post","link":"https:\/\/nbsigh2.com\/?p=27783","title":{"rendered":"\u56fd\u7acb\u56fd\u4f1a\u56f3\u66f8\u9928\u306eOCR\u30a2\u30d7\u30ea\u3000NDLOCR-Lite"},"content":{"rendered":"

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https:\/\/github.com\/ndl-lab\/ndlocr-lite\/releases<\/a>
\n\u304b\u3089\u3000Linux \u7528\u3001MacOS apple silicon \u7528\u3001MacOS intel \u7528\u3001Windows \u7528\u3044\u305a\u308c\u304b\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u89e3\u51cd\u3059\u308b\u3002<\/p>\n

Mac \u306e\u5834\u5408\u3001\u89e3\u51cd\u3057\u3066\u3067\u304d\u305f\u3000ndlocr-lite-gui\u3000\u3092\u30c0\u30d6\u30eb\u30af\u30ea\u30c3\u30af\u3059\u308b\u3068\u3000\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u3092\u30af\u30ea\u30a2\u3067\u304d\u306a\u3044\u3068\u3044\u3063\u3066\u958b\u304f\u3053\u3068\u304c\u3067\u304d\u306a\u3044\u304b\u3089\u3001\u30c0\u30d6\u30eb\u30af\u30ea\u30c3\u30af\u3057\u305f\u5f8c\u3000\u30b7\u30b9\u30c6\u30e0\u8a2d\u5b9a\u2192\u30d7\u30e9\u30a4\u30d0\u30b7\u30fc\u3068\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u2192\u3000\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u306e\u3068\u3053\u308d\u306b\u8868\u793a\u3055\u308c\u3066\u3044\u308b\u304b\u3089\u3000\u958b\u304f\u3000\u3092\u30af\u30ea\u30c3\u30af\u3000\u3067\u8d77\u52d5\u3067\u304d\u308b\u3002\u4e00\u5ea6\u901a\u308c\u3070\u4ee5\u964d\u306f\u666e\u901a\u306b\u8d77\u52d5\u3067\u304d\u308b\u3002
\n\"\"<\/a>
\n\u3068\u3044\u3046\u753b\u50cf\u3092\u5b9f\u65bd\u3059\u308b\u3068<\/p>\n

v1.1.2 Latest
\n\u4e3b\u306a\u6539\u5584\u70b9
\n\u30fb\u51e6\u7406\u306e\u9ad8\u901f\u5316
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\nWhat’s Changed
\n\u30fb\u753b\u50cf\u5165\u529b\u5468\u308a\u306e\u4fee\u6b63by@ndl-lab-staff in#23
\n\u30fb\u304c\u8907\u6570\u542b\u307e\u308c\u308b\u30d5\u30a1\u30a4\u30eb\u540d\u3078\u306e\u5bfe\u5fdc(cli\u306e\u307f)byndl-lab-staff in#24
\n\u30fbperf: replace PIL with cv2 and optimize numpy operations in preprocessing by ookilip in #2
\nFull Changelog: 1.1.1.2<\/p><\/blockquote>\n

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\n\"\"<\/a><\/p>\n

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\u3068\u306a\u308a\u307e\u3057\u305f\u3002Google\u304c\u5727\u5012\u7684\u306b\u512a\u308c\u3066\u3044\u307e\u3059\u306a\u3002<\/p>\n

[ \u8ffd\u8a18 ] 2026.3.5 \u3053\u306e\u8a18\u4e8b\u3092\u66f8\u3044\u305f\u5f8c\u3001\u3053\u306eOCR\u30a2\u30d7\u30ea\u3092\u8a55\u4fa1\u3057\u305f\u8a18\u4e8b<\/a>\u3092\u898b\u3064\u3051\u305f\u3002\u7d50\u8ad6\u306f\u3053\u306e\u8a18\u4e8b\u306e\u7d50\u8ad6\u306e\u3072\u3068\u3064\u201d\u8efd\u5feb\u201d\u304c\u4e00\u81f4\u3057\u3066\u3044\u308b\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

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