python实现98%准确率的工业级端到端的ocr场景字符识别代码

[{"title":"（ 49 个子文件 180.84MB ） python实现98%准确率的工业级端到端的ocr场景字符识别代码","children":[{"title":"ocr-predict","children":[{"title":"create_lmdb_dataset.py <span style='color:#111;'> 2.63KB </span>","children":null,"spread":false},{"title":"alphabets.py <span style='color:#111;'> 24.34KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 6.75KB </span>","children":null,"spread":false},{"title":"alphabets_all.py <span style='color:#111;'> 23.19KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 251B </span>","children":null,"spread":false},{"title":".idea","children":[{"title":".gitignore <span style='color:#111;'> 50B </span>","children":null,"spread":false},{"title":"misc.xml <span style='color:#111;'> 188B </span>","children":null,"spread":false},{"title":"workspace.xml <span style='color:#111;'> 1.56KB </span>","children":null,"spread":false},{"title":"inspectionProfiles","children":[{"title":"Project_Default.xml <span style='color:#111;'> 1.01KB </span>","children":null,"spread":false},{"title":"profiles_settings.xml <span style='color:#111;'> 174B </span>","children":null,"spread":false}],"spread":true},{"title":"ocr-predict.iml <span style='color:#111;'> 452B </span>","children":null,"spread":false},{"title":"modules.xml <span style='color:#111;'> 281B </span>","children":null,"spread":false}],"spread":true},{"title":"__pycache__","children":[{"title":"dataset.cpython-36.pyc <span style='color:#111;'> 11.04KB </span>","children":null,"spread":false},{"title":"alphabets_all.cpython-36.pyc <span style='color:#111;'> 23.31KB </span>","children":null,"spread":false},{"title":"alphabets.cpython-36.pyc <span style='color:#111;'> 24.46KB </span>","children":null,"spread":false},{"title":"utils.cpython-36.pyc <span style='color:#111;'> 7.03KB </span>","children":null,"spread":false},{"title":"model.cpython-36.pyc <span style='color:#111;'> 3.45KB </span>","children":null,"spread":false}],"spread":true},{"title":"dataset.py <span style='color:#111;'> 14.55KB </span>","children":null,"spread":false},{"title":"demo.py <span style='color:#111;'> 6.64KB </span>","children":null,"spread":false},{"title":"modules","children":[{"title":"bert.py <span style='color:#111;'> 9.95KB </span>","children":null,"spread":false},{"title":"transformation.py <span style='color:#111;'> 8.10KB </span>","children":null,"spread":false},{"title":"feature_extraction.py <span style='color:#111;'> 10.12KB </span>","children":null,"spread":false},{"title":"prediction.py <span style='color:#111;'> 3.93KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"bert.cpython-36.pyc <span style='color:#111;'> 10.70KB </span>","children":null,"spread":false},{"title":"resnet_aster.cpython-36.pyc <span style='color:#111;'> 5.69KB </span>","children":null,"spread":false},{"title":"transformation.cpython-36.pyc <span style='color:#111;'> 6.53KB </span>","children":null,"spread":false},{"title":"prediction.cpython-36.pyc <span style='color:#111;'> 3.08KB </span>","children":null,"spread":false},{"title":"feature_extraction.cpython-36.pyc <span style='color:#111;'> 8.16KB </span>","children":null,"spread":false},{"title":"sequence_modeling.cpython-36.pyc <span style='color:#111;'> 1.02KB </span>","children":null,"spread":false}],"spread":false},{"title":"resnet_aster.py <span style='color:#111;'> 5.78KB </span>","children":null,"spread":false},{"title":"sequence_modeling.py <span style='color:#111;'> 746B </span>","children":null,"spread":false}],"spread":true},{"title":"saved_models","children":[{"title":"best_accuracy.pth <span style='color:#111;'> 195.23MB </span>","children":null,"spread":false}],"spread":true},{"title":"demo_image","children":[{"title":"200208_4139118_1358_8.jpg <span style='color:#111;'> 10.65KB </span>","children":null,"spread":false},{"title":"26.jpg <span style='color:#111;'> 15.15KB </span>","children":null,"spread":false},{"title":"200207_8051640_2102_0.jpg <span style='color:#111;'> 11.03KB </span>","children":null,"spread":false},{"title":"11.jpg <span style='color:#111;'> 9.77KB </span>","children":null,"spread":false},{"title":"14.jpg <span style='color:#111;'> 8.92KB </span>","children":null,"spread":false},{"title":"5_5_5_5.jpg <span style='color:#111;'> 8.38KB </span>","children":null,"spread":false},{"title":"200208_4139118_1358_1.jpg <span style='color:#111;'> 4.18KB </span>","children":null,"spread":false},{"title":"25.jpg <span style='color:#111;'> 9.94KB </span>","children":null,"spread":false},{"title":"13.jpg <span style='color:#111;'> 9.36KB </span>","children":null,"spread":false},{"title":"32.jpg <span style='color:#111;'> 12.63KB </span>","children":null,"spread":false},{"title":"6.jpg <span style='color:#111;'> 9.06KB </span>","children":null,"spread":false},{"title":"18.jpg <span style='color:#111;'> 10.08KB </span>","children":null,"spread":false},{"title":"24.jpg <span style='color:#111;'> 10.90KB </span>","children":null,"spread":false},{"title":"4_4_4_4.jpg <span style='color:#111;'> 9.58KB </span>","children":null,"spread":false}],"spread":false},{"title":"result.txt <span style='color:#111;'> 907B </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 5.18KB </span>","children":null,"spread":false},{"title":"distance.py <span style='color:#111;'> 4.56KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]