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PyTorch\ub294 \uba38\uc2e0\ub7ec\ub2dd \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \ud2b9\ud788 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc758 \uac1c\ubc1c\uacfc \ud559\uc2b5\uc5d0 \ub9ce\uc774 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \ubcf8 \uac15\uc88c\uc5d0\uc11c\ub294 PyTorch\ub85c \ud559\uc2b5\ud55c \ubaa8\ub378\uc744 OpenCV\ub97c \ud1b5\ud574 \ub85c\ub4dc\ud558\uc5ec \uc2e4\uc2dc\uac04\uc73c\ub85c \uc2e4\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 2.\u2026","rel":"","context":""OpenCV"\uc5d0\uc11c","block_context":{"text":"OpenCV","link":"https:\/\/atmokpo.com\/w\/category\/opencv\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":38822,"url":"https:\/\/atmokpo.com\/w\/38822\/","url_meta":{"origin":40019,"position":3},"title":"OpenCV \uac15\uc88c, \ub2e4\uc591\ud55c \uc0ac\uc804 \ud559\uc2b5 \ubaa8\ub378 \ube44\uad50 \ubc0f \ud29c\ub2dd","author":"root","date":"2024\ub144 11\uc6d4 02\uc77c","format":false,"excerpt":"\uc791\uc131\uc790: \uc870\uad11\ud615 \uc791\uc131\uc77c: [\ub0a0\uc9dc] 1. OpenCV \uc18c\uac1c OpenCV(Open Source Computer Vision Library)\ub294 \uc774\ubbf8\uc9c0 \ucc98\ub9ac\ub97c \uc704\ud55c \uc624\ud508 \uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \uc2e4\uc2dc\uac04 \ucef4\ud4e8\ud130 \ube44\uc804 \uc751\uc6a9 \ud504\ub85c\uadf8\ub7a8\uc758 \uac1c\ubc1c\uc744 \uc9c0\uc6d0\ud569\ub2c8\ub2e4. C++, Python, Java \ub4f1 \ub2e4\uc591\ud55c \uc5b8\uc5b4\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc73c\uba70, \uc774 \uae00\uc5d0\uc11c\ub294 \uc8fc\ub85c Python\uacfc \ud568\uaed8 OpenCV\ub97c \ud65c\uc6a9\ud55c \ub2e4\uc591\ud55c \uc0ac\uc804 \ud559\uc2b5 \ubaa8\ub378\uc744 \ube44\uad50\ud558\uace0 \ud29c\ub2dd\ud558\ub294 \ubc29\ubc95\uc744 \ub2e4\ub8e8\uaca0\uc2b5\ub2c8\ub2e4. 2.\u2026","rel":"","context":""OpenCV"\uc5d0\uc11c","block_context":{"text":"OpenCV","link":"https:\/\/atmokpo.com\/w\/category\/opencv\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":38732,"url":"https:\/\/atmokpo.com\/w\/38732\/","url_meta":{"origin":40019,"position":4},"title":"OpenCV \uac15\uc88c, \ubaa8\uc591\uc758 \uba74\uc801, \ub458\ub808 \uae38\uc774 \ub4f1 \uae30\ubcf8 \ubd84\uc11d","author":"root","date":"2024\ub144 11\uc6d4 02\uc77c","format":false,"excerpt":"OpenCV(\uc624\ud508\uc18c\uc2a4 \ucef4\ud4e8\ud130 \ube44\uc804 \ub77c\uc774\ube0c\ub7ec\ub9ac)\ub294 \uc774\ubbf8\uc9c0\uc640 \ube44\ub514\uc624\ub97c \ucc98\ub9ac\ud558\ub294 \ub370 \uc720\uc6a9\ud55c \ub2e4\uc591\ud55c \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 \uc774\ubbf8\uc9c0\uc5d0\uc11c \ubaa8\uc591\uc758 \uba74\uc801\uacfc \ub458\ub808 \uae38\uc774\ub97c \uce21\uc815\ud558\ub294 \uae30\ubcf8\uc801\uc778 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. \uc774 \uac15\uc88c\ub294 Python\uc744 \uae30\ubc18\uc73c\ub85c \ud558\uba70, \ub2e4\uc591\ud55c \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4\uc5d0\uc11c\uc758 \uc801\uc6a9 \uac00\ub2a5\uc131\uc744 \uace0\ub824\ud558\uc600\uc2b5\ub2c8\ub2e4. 1. OpenCV \uc18c\uac1c OpenCV\ub294 2000\ub144\ub300 \ucd08\ubc18\uc5d0 \uac1c\ubc1c\ub41c \uc624\ud508\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \ucef4\ud4e8\ud130 \ube44\uc804 \ubc0f \uc774\ubbf8\uc9c0 \ucc98\ub9ac\uc5d0 \ud544\uc694\ud55c\u2026","rel":"","context":""OpenCV"\uc5d0\uc11c","block_context":{"text":"OpenCV","link":"https:\/\/atmokpo.com\/w\/category\/opencv\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":25341,"url":"https:\/\/atmokpo.com\/w\/25341\/","url_meta":{"origin":40019,"position":5},"title":"\ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac: 1D CNN\uc73c\ub85c \uc2a4\ud338 \uba54\uc77c \ubd84\ub958\ud558\uae30","author":"root","date":"2024\ub144 10\uc6d4 26\uc77c","format":false,"excerpt":"\uc791\uc131\uc790: \uc870\uad11\ud615 | \ub0a0\uc9dc: [\ub0a0\uc9dc] \uc11c\ub860 \ucd5c\uadfc \uba87 \ub144\uac04 \ub525 \ub7ec\ub2dd \uae30\uc220\uc774 \ube44\uc57d\uc801\uc73c\ub85c \ubc1c\uc804\ud558\uba74\uc11c \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0 \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(Natural Language Processing, NLP)\ub294 \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \uc0dd\uc131\ud558\ub294 \uae30\uc220\ub85c, \uc774\uba54\uc77c \ubd84\ub958, \uac10\uc815 \ubd84\uc11d, \uae30\uacc4 \ubc88\uc5ed \ub4f1 \ub2e4\ubc29\uba74\uc5d0\uc11c \ud65c\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 1\ucc28\uc6d0 \ud569\uc131\uacf1 \uc2e0\uacbd\ub9dd(1D CNN)\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc2a4\ud338 \uba54\uc77c\uc744\u2026","rel":"","context":""\ub525\ub7ec\ub2dd \uc790\uc5f0\uc5b4\ucc98\ub9ac"\uc5d0\uc11c","block_context":{"text":"\ub525\ub7ec\ub2dd \uc790\uc5f0\uc5b4\ucc98\ub9ac","link":"https:\/\/atmokpo.com\/w\/category\/%eb%94%a5%eb%9f%ac%eb%8b%9d-%ec%9e%90%ec%97%b0%ec%96%b4%ec%b2%98%eb%a6%ac\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/posts\/40019","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/comments?post=40019"}],"version-history":[{"count":1,"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/posts\/40019\/revisions"}],"predecessor-version":[{"id":40020,"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/posts\/40019\/revisions\/40020"}],"wp:attachment":[{"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/media?parent=40019"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/categories?post=40019"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/atmokpo.com\/w\/wp-json\/wp\/v2\/tags?post=40019"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

\uc11c\ub860<\/h2>\n

\n \uc778\uacf5\uc9c0\ub2a5(AI)\uc740 \ud604\ub300 \uae30\uc220\uc5d0\uc11c \ud544\uc218\uc801\uc778 \uc694\uc18c\ub85c \uc790\ub9ac\uc7a1\uace0 \uc788\uc73c\uba70, \ud2b9\ud788 \uc774\ubbf8\uc9c0 \uc778\uc2dd \ubd84\uc57c\uc5d0\uc11c \uadf8 \uac00\ub2a5\uc131\uc744 \uadf9\ub300\ud654\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.
\n OpenCV(Open Source Computer Vision Library)\uc640 PyTorch\ub294 \uc774\ub7ec\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd \uae30\uc220\uc744 \uad6c\ud604\ud558\ub294 \ub370 \uc788\uc5b4 \uac00\uc7a5 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \ud234\uc785\ub2c8\ub2e4.
\n \ubcf8 \uae00\uc5d0\uc11c\ub294 \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc758 \uae30\ubcf8 \uc6d0\ub9ac\ubd80\ud130 \uc2dc\uc791\ud558\uc5ec OpenCV\uc640 PyTorch\uc758 \ud65c\uc6a9 \ubc29\ubc95, \uc2e4\uc81c \uc608\uc81c \ubc0f \ub370\uc774\ud130\uc14b\uc744 \uc5bb\uc744 \uc218 \uc788\ub294 \uc18c\uc2a4\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud558\uace0\uc790 \ud569\ub2c8\ub2e4.\n <\/p>\n<\/section>\n

1. \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc758 \uae30\ubcf8 \uc6d0\ub9ac<\/h2>\n

\n \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc740 \ucef4\ud4e8\ud130\uac00 \uc774\ubbf8\uc9c0\ub97c \ubd84\uc11d\ud558\uace0 \uc774\ud574\ud558\uc5ec \uadf8 \uc0ac\uc9c4\uc5d0 \ub2f4\uae34 \ub0b4\uc6a9\uc774\ub098 \ubb3c\uccb4, \uc0ac\ub78c \ub4f1\uc744 \uc2dd\ubcc4\ud558\ub294 \uacfc\uc815\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.
\n \uc774\ub294 \ub525\ub7ec\ub2dd, \uba38\uc2e0\ub7ec\ub2dd, \ucef4\ud4e8\ud130 \ube44\uc804 \ub4f1 \ub2e4\uc591\ud55c \uae30\uc220\uc758 \uc735\ud569\uc744 \ud1b5\ud574 \uc774\ub8e8\uc5b4\uc9d1\ub2c8\ub2e4.
\n \uae30\ubcf8\uc801\uc73c\ub85c \uc774\ubbf8\uc9c0\ub97c \ucc98\ub9ac\ud558\uc5ec \ud2b9\uc9d5\uc744 \ucd94\ucd9c\ud558\uace0, \uc774\ub7ec\ud55c \ud2b9\uc9d5\uc744 \ubc14\ud0d5\uc73c\ub85c \ubd84\ub958 \ubaa8\ub378\uc744 \uad6c\uc131\ud558\uc5ec \ucd5c\uc885\uc801\uc73c\ub85c \uc778\uc2dd \uacb0\uacfc\ub97c \ub3c4\ucd9c\ud558\uac8c \ub429\ub2c8\ub2e4.\n <\/p>\n

\n \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc758 \uacfc\uc815\uc740 \ud06c\uac8c \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e8\uacc4\ub85c \ub098\ub20c \uc218 \uc788\uc2b5\ub2c8\ub2e4:\n <\/p>\n

\uc774\ubbf8\uc9c0 \uc218\uc9d1: \uc774\ubbf8\uc9c0 \ub370\uc774\ud130\ub97c \uc218\uc9d1\ud558\ub294 \ub2e8\uacc4\uc785\ub2c8\ub2e4.<\/li>\n
\uc804\ucc98\ub9ac: \uc774\ubbf8\uc9c0\ub97c \uc218\uce58\ub85c \ubcc0\ud658\ud558\uace0, \uc7a1\uc74c\uc744 \uc81c\uac70\ud558\uba70, \ud06c\uae30\ub97c \uc870\uc815\ud558\ub294 \uacfc\uc815\uc785\ub2c8\ub2e4.<\/li>\n
\ud2b9\uc9d5 \ucd94\ucd9c: \uc774\ubbf8\uc9c0\uc5d0\uc11c \uc911\uc694\ud55c \uc815\ubcf4\ub97c \ucd94\ucd9c\ud558\ub294 \ub2e8\uacc4\ub85c, \uc804\ud1b5\uc801\uc778 \ucef4\ud4e8\ud130 \ube44\uc804 \uae30\ubc95\uc774\ub098 \ub525\ub7ec\ub2dd\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n
\ubd84\ub958: \ucd94\ucd9c\ud55c \ud2b9\uc9d5\uc744 \ubc14\ud0d5\uc73c\ub85c \uc774\ubbf8\uc9c0\ub97c \ubd84\ub958\ud558\ub294 \ub2e8\uacc4\uc785\ub2c8\ub2e4.<\/li>\n

\uacb0\uacfc \ubd84\uc11d: \uc778\uc2dd\ub41c \uacb0\uacfc\ub97c \ud1b5\ud574 \ud1b5\ucc30\uc744 \ub3c4\ucd9c\ud558\ub294 \ub2e8\uacc4\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n

2. OpenCV\ub780 \ubb34\uc5c7\uc778\uac00?<\/h2>\n

\n OpenCV\ub294 \ucef4\ud4e8\ud130 \ube44\uc804 \ubc0f \uba38\uc2e0 \ub7ec\ub2dd\uc744 \uc704\ud55c \uc624\ud508\uc18c\uc2a4 \ub77c\uc774\ube0c\ub7ec\ub9ac\ub85c, \ub2e4\uc591\ud55c \uc774\ubbf8\uc9c0 \ucc98\ub9ac \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.
\n C++\uc744 \uae30\ubc18\uc73c\ub85c \uc124\uacc4\ub418\uc5c8\uc9c0\ub9cc Python, Java \ub4f1 \uc5ec\ub7ec \uc5b8\uc5b4\uc5d0\uc11c\ub3c4 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n OpenCV\uc758 \uc8fc\uc694 \uae30\ub2a5\uc5d0\ub294 \uc774\ubbf8\uc9c0 \ubc0f \ube44\ub514\uc624 \ubd84\uc11d, \uc774\ubbf8\uc9c0 \ud544\ud130\ub9c1, \uac1d\uccb4 \ud0d0\uc9c0, \uc5bc\uad74 \uc778\uc2dd \ub4f1\uc774 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n

\n OpenCV\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uc7a5\uc810\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4:\n <\/p>\n

\uad11\ubc94\uc704\ud55c \uae30\ub2a5: \uc774\ubbf8\uc9c0 \ubc0f \ube44\ub514\uc624 \ucc98\ub9ac\uc5d0 \ud544\uc694\ud55c \ub2e4\uc591\ud55c \uc54c\uace0\ub9ac\uc998\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/li>\n
\ub2e4\uc591\ud55c \uc5b8\uc5b4 \uc9c0\uc6d0: \uc5ec\ub7ec \ud504\ub85c\uadf8\ub798\ubc0d \uc5b8\uc5b4\uc5d0\uc11c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc5b4 \uc811\uadfc\uc131\uc774 \ub192\uc2b5\ub2c8\ub2e4.<\/li>\n

\ub300\uaddc\ubaa8 \ucee4\ubba4\ub2c8\ud2f0: \ud65c\ubc1c\ud55c \ucee4\ubba4\ub2c8\ud2f0\uac00 \ud615\uc131\ub418\uc5b4 \uc788\uc5b4 \ub2e4\uc591\ud55c \uc815\ubcf4\uc640 \uc9c0\uc6d0\uc744 \ubc1b\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n

3. PyTorch\ub780 \ubb34\uc5c7\uc778\uac00?<\/h2>\n

\n PyTorch\ub294 Facebook\uc5d0\uc11c \uac1c\ubc1c\ud55c \uc624\ud508\uc18c\uc2a4 \uba38\uc2e0\ub7ec\ub2dd \ud504\ub808\uc784\uc6cc\ud06c\ub85c, \ud2b9\ud788 \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uad6c\ucd95\ud558\uace0 \ud6c8\ub828\uc2dc\ud0a4\ub294 \ub370 \uc911\uc810\uc744 \ub450\uace0 \uc788\uc2b5\ub2c8\ub2e4.
\n \ub3d9\uc801 \uacc4\uc0b0 \uadf8\ub798\ud504\ub97c \uae30\ubc18\uc73c\ub85c \ud558\uc5ec \uc9c1\uad00\uc801\uc774\uace0 \uc720\uc5f0\ud55c \uc0ac\uc6a9\uc774 \uac00\ub2a5\ud558\uba70, \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \ubd84\uc11d\uacfc \ubcd1\ub82c \ucc98\ub9ac\uc5d0 \ucd5c\uc801\ud654\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.\n <\/p>\n

\n PyTorch\uc758 \uc8fc\uc694 \uae30\ub2a5 \ubc0f \uc7a5\uc810\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4:\n <\/p>\n

\ub3d9\uc801 \uacc4\uc0b0 \uadf8\ub798\ud504: \uc5f0\uc0b0\uc744 \uc9c4\ud589\ud558\uba74\uc11c \uadf8\ub798\ud504\uac00 \uc0dd\uc131\ub418\ubbc0\ub85c \ub514\ubc84\uae45\uc774 \uc6a9\uc774\ud569\ub2c8\ub2e4.<\/li>\n
\uc26c\uc6b4 \uc0ac\uc6a9\ubc95: Pythonic\ud55c \uc778\ud130\ud398\uc774\uc2a4\ub97c \uc81c\uacf5\ud558\uc5ec \uc9c1\uad00\uc801\uc73c\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n

\ud65c\ubc1c\ud55c \ucee4\ubba4\ub2c8\ud2f0: \ud48d\ubd80\ud55c \uc790\ub8cc\uc640 \uc9c0\uc6d0\uc744 \ubc1b\uc744 \uc218 \uc788\ub294 \ucee4\ubba4\ub2c8\ud2f0\uac00 \ud615\uc131\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n

4. OpenCV\uc640 PyTorch\uc758 \ud1b5\ud569<\/h2>\n

\n OpenCV\uc640 PyTorch\ub294 \uac01\uae30 \ub2e4\ub978 \uc6a9\ub3c4\ub85c \uc0ac\uc6a9\ub418\uc9c0\ub9cc, \ud568\uaed8 \uc0ac\uc6a9\ud558\uba74 \uac15\ub825\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd \uc194\ub8e8\uc158\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n OpenCV\ub294 \uc774\ubbf8\uc9c0 \uc804\ucc98\ub9ac \ubc0f \ud2b9\uc9d5 \ucd94\ucd9c\uc5d0 \ub6f0\uc5b4\ub09c \uc131\ub2a5\uc744 \ubc1c\ud718\ud558\uba70, PyTorch\ub294 \ubcf5\uc7a1\ud55c \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uc27d\uac8c \uad6c\ucd95\ud558\uace0 \ud6c8\ub828\uc2dc\ud0a4\ub294 \ub370 \uc720\uc6a9\ud569\ub2c8\ub2e4.\n <\/p>\n<\/section>\n

5. OpenCV\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc804\ucc98\ub9ac<\/h2>\n

\n \uc774\ubbf8\uc9c0 \uc804\ucc98\ub9ac\ub294 \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc5d0 \uc788\uc5b4 \ub9e4\uc6b0 \uc911\uc694\ud55c \ub2e8\uacc4\uc774\uba70, OpenCV\ub97c \ud65c\uc6a9\ud558\uba74 \uc5ec\ub7ec \uac00\uc9c0 \uc804\ucc98\ub9ac \uae30\ubc95\uc744 \uc190\uc27d\uac8c \uc801\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n \uc5ec\uae30\uc5d0\ub294 \uc774\ubbf8\uc9c0 \ub9ac\uc0ac\uc774\uc9d5, \uc0c9\uc0c1 \ubcc0\ud658, \uc18c\uc74c \uc81c\uac70, \uc724\uacfd\uc120 \ud0d0\uc9c0 \ub4f1\uc774 \ud3ec\ud568\ub429\ub2c8\ub2e4.\n <\/p>\n

import cv2\n\n# \uc774\ubbf8\uc9c0 \uc77d\uae30\nimage = cv2.imread('image.jpg')\n\n# \uadf8\ub808\uc774\uc2a4\ucf00\uc77c \ubcc0\ud658\ngray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n\n# \uc774\ubbf8\uc9c0 \ub9ac\uc0ac\uc774\uc9d5\nresized_image = cv2.resize(gray_image, (128, 128))\n\n# \uc18c\uc74c \uc81c\uac70\ndenoised_image = cv2.GaussianBlur(resized_image, (5, 5), 0)\n\n# \uc724\uacfd\uc120 \ud0d0\uc9c0\nedges = cv2.Canny(denoised_image, 100, 200)\n            <\/code><\/pre>\n\n                \uc774\ucc98\ub7fc OpenCV\ub97c \ud65c\uc6a9\ud558\uc5ec \uc774\ubbf8\uc9c0\ub97c \ub2e4\uc591\ud55c \ubc29\uc2dd\uc73c\ub85c \uc804\ucc98\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n            <\/p>\n<\/section>\n
\n6. PyTorch\ub97c \ud65c\uc6a9\ud55c \ub525\ub7ec\ub2dd \ubaa8\ub378 \uad6c\ucd95<\/h2>\n\n                OpenCV\ub85c \uc804\ucc98\ub9ac\ub41c \uc774\ubbf8\uc9c0\ub97c \uae30\ubc18\uc73c\ub85c PyTorch\ub97c \ud65c\uc6a9\ud558\uc5ec \ub525\ub7ec\ub2dd \ubaa8\ub378\uc744 \uad6c\ucd95\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n                PyTorch\ub294 \ub2e4\uc591\ud55c \ub525\ub7ec\ub2dd \uc544\ud0a4\ud14d\ucc98\ub97c \uc27d\uac8c \uad6c\ud604\ud560 \uc218 \uc788\uac8c \ub3c4\uc640\uc90d\ub2c8\ub2e4. \uc544\ub798\ub294 \uac04\ub2e8\ud55c \uc2e0\uacbd\ub9dd \ubaa8\ub378\uc758 \uc608\uc2dc\uc785\ub2c8\ub2e4.\n            <\/p>\n
import torch\nimport torch.nn as nn\n\nclass SimpleNN(nn.Module):\n    def __init__(self):\n        super(SimpleNN, self).__init__()\n        self.fc1 = nn.Linear(128 * 128, 256)\n        self.fc2 = nn.Linear(256, 10)  # \uc608\ub97c \ub4e4\uc5b4 10\uac00\uc9c0 \ud074\ub798\uc2a4 \ubd84\ub958\n\n    def forward(self, x):\n        x = torch.relu(self.fc1(x))\n        x = self.fc2(x)\n        return x\n            <\/code><\/pre>\n\n                \uc704\uc758 \ubaa8\ub378\uc740 \ub2e8\uc21c\ud55c \uc120\ud615 \uc2e0\uacbd\ub9dd\uc73c\ub85c, \uc785\ub825 \uc774\ubbf8\uc9c0\uac00(128×128 \ud06c\uae30\ub85c \uac00\uc815) 256\ucc28\uc6d0\uc73c\ub85c \ubcc0\ud658\ub418\uace0 \ucd5c\uc885\uc801\uc73c\ub85c 10\uac1c\uc758 \ud074\ub798\uc2a4\ub85c \ubd84\ub958\ub429\ub2c8\ub2e4.\n            <\/p>\n<\/section>\n
\n7. \ud6c8\ub828 \ubc0f \ud3c9\uac00<\/h2>\n\n                \ud6c8\ub828 \ub370\uc774\ud130\ub97c \uc900\ube44\ud55c \ud6c4, \ud6c8\ub828 \uacfc\uc815\uc744 \ud1b5\ud574 \ubaa8\ub378\uc758 \uac00\uc911\uce58\ub97c \uc5c5\ub370\uc774\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n                PyTorch\uc5d0\uc11c\ub294 \uc190\uc2e4 \ud568\uc218\uc640 \uc635\ud2f0\ub9c8\uc774\uc800\ub97c \uc124\uc815\ud558\uc5ec \uc5ec\ub7ec \ubc88\uc758 \uc5d0\ud3ec\ud06c\ub97c \uac70\uccd0 \ubaa8\ub378\uc744 \ud6c8\ub828\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n            <\/p>\n
import torch.optim as optim\n\n# \ubaa8\ub378, \uc190\uc2e4\ud568\uc218, \uc635\ud2f0\ub9c8\uc774\uc800 \uc815\uc758\nmodel = SimpleNN()\ncriterion = nn.CrossEntropyLoss()\noptimizer = optim.SGD(model.parameters(), lr=0.01)\n\n# \ud6c8\ub828 \ub8e8\ud504\nfor epoch in range(10):  # \uc5d0\ud3ec\ud06c \uc218\n    # \uc774\ubbf8\uc9c0\uc640 \ub808\uc774\ube14\uc744 \uac00\uc838\uc635\ub2c8\ub2e4.\n    inputs = ... # \uc804\ucc98\ub9ac\ub41c \uc774\ubbf8\uc9c0\n    labels = ... # \ub77c\ubca8\n    \n    optimizer.zero_grad()  # \uc774\uc804 \uae30\uc6b8\uae30 \ucd08\uae30\ud654\n    outputs = model(inputs)  # \ubaa8\ub378 \uc608\uce21\n    \n    loss = criterion(outputs, labels)  # \uc190\uc2e4 \uacc4\uc0b0\n    loss.backward()  # \uc5ed\uc804\ud30c\n    optimizer.step()  # \uac00\uc911\uce58 \uc5c5\ub370\uc774\ud2b8\n            <\/code><\/pre>\n<\/section>\n\n8. \ub370\uc774\ud130\uc14b \ubc0f \uacf5\uac1c \ub370\uc774\ud130 \uc5bb\ub294 \uacf3<\/h2>\n\n                \uc774\ubbf8\uc9c0 \uc778\uc2dd \ubaa8\ub378\uc744 \ud6c8\ub828\uc2dc\ud0a4\uae30 \uc704\ud574\uc11c\ub294 \uc801\uc808\ud55c \ub370\uc774\ud130\uc14b\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. \uc5ec\ub7ec \uacf5\uac1c \ub370\uc774\ud130\uc14b\uc744 \ud1b5\ud574 \uc2e4\uc81c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc2e4\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c\uc740 \ub370\uc774\ud130\uc14b\uc744 \uc5bb\uc744 \uc218 \uc788\ub294 \uc8fc\uc694 \uc0ac\uc774\ud2b8\uc785\ub2c8\ub2e4:\n            <\/p>\n
\nImageNet<\/a>: \uad11\ubc94\uc704\ud55c \uc774\ubbf8\uc9c0 \ub370\uc774\ud130\uc14b\uc73c\ub85c, \ub2e4\uc591\ud55c \uac1d\uccb4\uc640 \uadf8 \ub77c\ubca8\uc744 \ud3ec\ud568\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n
CIFAR-10<\/a>: 10\uac1c\uc758 \ud074\ub798\uc2a4\uc5d0 \ub300\ud574 60,000\uac1c\uc758 \uc774\ubbf8\uc9c0\ub85c \uad6c\uc131\ub41c \ub370\uc774\ud130\uc14b\uc785\ub2c8\ub2e4.<\/li>\n
Kaggle Datasets<\/a>: \ub2e4\uc591\ud55c \uc774\ubbf8\uc9c0 \ub370\uc774\ud130\uc14b\uc744 \ud3ec\ud568\ud55c \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \ud50c\ub7ab\ud3fc\uc785\ub2c8\ub2e4.<\/li>\n
MS COCO<\/a>: \uc790\uc5f0 \uc774\ubbf8\uc9c0\ub97c \ub2e4\ub8ec \ub370\uc774\ud130\uc14b\uc73c\ub85c, \uac1d\uccb4 \uac10\uc9c0\uc640 \ubd84\ud560 \ubb38\uc81c\uc5d0 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/li>\n
Dog Breed Identification Dataset<\/a>: \ub2e4\uc591\ud55c \ud488\uc885\uc758 \uac1c \uc774\ubbf8\uc9c0\ub97c \ud3ec\ud568\ud558\uace0 \uc788\ub294 \ub370\uc774\ud130\uc14b\uc785\ub2c8\ub2e4.<\/li>\n<\/ul>\n<\/section>\n\n9. \uacb0\ub860<\/h2>\n\n                OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd \uae30\uc220\uc740 \ub2e8\uc21c\ud55c \uc608\uc81c\uc5d0\uc11c\ubd80\ud130 \ubcf5\uc7a1\ud55c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uae4c\uc9c0 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n                \uc774\ubbf8\uc9c0 \uc804\ucc98\ub9ac\uc640 \ub525\ub7ec\ub2dd \ubaa8\ub378 \uad6c\ucd95\uc744 \ud1b5\ud574, \uc2e4\uc81c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uace0 \ud601\uc2e0\uc801\uc778 \uc194\ub8e8\uc158\uc744 \uc81c\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.
\n                \uc774\ub7ec\ud55c \ub3c4\uad6c\ub4e4\uc744 \ud1b5\ud574 \uc5ec\ub7ec\ubd84\uc758 \uc544\uc774\ub514\uc5b4\ub97c \ud604\uc2e4\ub85c \uad6c\ud604\ud574\ubcf4\uc2dc\uae38 \ubc14\ub78d\ub2c8\ub2e4.\n            <\/p>\n<\/section>\n<\/article>\n
<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"\uc11c\ub860 \uc778\uacf5\uc9c0\ub2a5(AI)\uc740 \ud604\ub300 \uae30\uc220\uc5d0\uc11c \ud544\uc218\uc801\uc778 \uc694\uc18c\ub85c \uc790\ub9ac\uc7a1\uace0 \uc788\uc73c\uba70, \ud2b9\ud788 \uc774\ubbf8\uc9c0 \uc778\uc2dd \ubd84\uc57c\uc5d0\uc11c \uadf8 \uac00\ub2a5\uc131\uc744 \uadf9\ub300\ud654\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. OpenCV(Open Source Computer Vision Library)\uc640 PyTorch\ub294 \uc774\ub7ec\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd \uae30\uc220\uc744 \uad6c\ud604\ud558\ub294 \ub370 \uc788\uc5b4 \uac00\uc7a5 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \ud234\uc785\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc758 \uae30\ubcf8 \uc6d0\ub9ac\ubd80\ud130 \uc2dc\uc791\ud558\uc5ec OpenCV\uc640 PyTorch\uc758 \ud65c\uc6a9 \ubc29\ubc95, \uc2e4\uc81c \uc608\uc81c \ubc0f \ub370\uc774\ud130\uc14b\uc744 \uc5bb\uc744 \uc218 \uc788\ub294 \uc18c\uc2a4\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud558\uace0\uc790 … \ub354 \ubcf4\uae30 “\uc778\uacf5\uc9c0\ub2a5 \ud65c\uc6a9, OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[205],"tags":[],"class_list":["post-40019","post","type-post","status-publish","format-standard","hentry","category-205"],"yoast_head":"\n\uc778\uacf5\uc9c0\ub2a5 \ud65c\uc6a9, OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/40019\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\uc778\uacf5\uc9c0\ub2a5 \ud65c\uc6a9, OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\uc11c\ub860 \uc778\uacf5\uc9c0\ub2a5(AI)\uc740 \ud604\ub300 \uae30\uc220\uc5d0\uc11c \ud544\uc218\uc801\uc778 \uc694\uc18c\ub85c \uc790\ub9ac\uc7a1\uace0 \uc788\uc73c\uba70, \ud2b9\ud788 \uc774\ubbf8\uc9c0 \uc778\uc2dd \ubd84\uc57c\uc5d0\uc11c \uadf8 \uac00\ub2a5\uc131\uc744 \uadf9\ub300\ud654\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. OpenCV(Open Source Computer Vision Library)\uc640 PyTorch\ub294 \uc774\ub7ec\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd \uae30\uc220\uc744 \uad6c\ud604\ud558\ub294 \ub370 \uc788\uc5b4 \uac00\uc7a5 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \ud234\uc785\ub2c8\ub2e4. \ubcf8 \uae00\uc5d0\uc11c\ub294 \uc774\ubbf8\uc9c0 \uc778\uc2dd\uc758 \uae30\ubcf8 \uc6d0\ub9ac\ubd80\ud130 \uc2dc\uc791\ud558\uc5ec OpenCV\uc640 PyTorch\uc758 \ud65c\uc6a9 \ubc29\ubc95, \uc2e4\uc81c \uc608\uc81c \ubc0f \ub370\uc774\ud130\uc14b\uc744 \uc5bb\uc744 \uc218 \uc788\ub294 \uc18c\uc2a4\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud558\uace0\uc790 … \ub354 \ubcf4\uae30 "\uc778\uacf5\uc9c0\ub2a5 \ud65c\uc6a9, OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/atmokpo.com\/w\/40019\/\" \/>\n<meta property=\"og:site_name\" content=\"\ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"article:published_time\" content=\"2024-11-02T10:20:45+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-26T06:40:20+00:00\" \/>\n<meta name=\"author\" content=\"root\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:site\" content=\"@bebubo4\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"root\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/atmokpo.com\/w\/40019\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/atmokpo.com\/w\/40019\/\"},\"author\":{\"name\":\"root\",\"@id\":\"https:\/\/atmokpo.com\/w\/#\/schema\/person\/91b6b3b138fbba0efb4ae64b1abd81d7\"},\"headline\":\"\uc778\uacf5\uc9c0\ub2a5 \ud65c\uc6a9, OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd\",\"datePublished\":\"2024-11-02T10:20:45+00:00\",\"dateModified\":\"2024-11-26T06:40:20+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/atmokpo.com\/w\/40019\/\"},\"wordCount\":51,\"publisher\":{\"@id\":\"https:\/\/atmokpo.com\/w\/#organization\"},\"articleSection\":[\"\uc778\uacf5\uc9c0\ub2a5\ud65c\uc6a9\"],\"inLanguage\":\"ko-KR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/atmokpo.com\/w\/40019\/\",\"url\":\"https:\/\/atmokpo.com\/w\/40019\/\",\"name\":\"\uc778\uacf5\uc9c0\ub2a5 \ud65c\uc6a9, OpenCV\uc640 PyTorch\ub97c \ud65c\uc6a9\ud55c \uc774\ubbf8\uc9c0 \uc778\uc2dd - 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