{"id":13598514,"url":"https://github.com/0x454447415244/HandwritingRecognitionSystem","last_synced_at":"2025-04-10T09:31:30.237Z","repository":{"id":39738345,"uuid":"154915461","full_name":"0x454447415244/HandwritingRecognitionSystem","owner":"0x454447415244","description":"Handwriting Recognition System based on a deep Convolutional Recurrent Neural Network architecture","archived":false,"fork":false,"pushed_at":"2023-08-22T01:05:09.000Z","size":5136,"stargazers_count":433,"open_issues_count":5,"forks_count":139,"subscribers_count":21,"default_branch":"master","last_synced_at":"2024-11-06T23:38:26.690Z","etag":null,"topics":["cnn","deep-learning","handwriting-recognition","machine-learning","rnn","tensorflow"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/0x454447415244.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"License.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2018-10-27T02:19:21.000Z","updated_at":"2024-11-04T08:51:37.000Z","dependencies_parsed_at":"2024-01-14T04:43:36.333Z","dependency_job_id":"c6a60fd2-6920-4404-ac58-017f78943a0b","html_url":"https://github.com/0x454447415244/HandwritingRecognitionSystem","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x454447415244%2FHandwritingRecognitionSystem","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x454447415244%2FHandwritingRecognitionSystem/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x454447415244%2FHandwritingRecognitionSystem/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/0x454447415244%2FHandwritingRecognitionSystem/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/0x454447415244","download_url":"https://codeload.github.com/0x454447415244/HandwritingRecognitionSystem/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248191712,"owners_count":21062556,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cnn","deep-learning","handwriting-recognition","machine-learning","rnn","tensorflow"],"created_at":"2024-08-01T17:00:53.225Z","updated_at":"2025-04-10T09:31:25.215Z","avatar_url":"https://github.com/0x454447415244.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"# Handwriting Recognition System\n\nThis repository is the Tensorflow implementation of the Handwriting Recognition System described in [Handwriting Recognition of Historical Documents with Few Labeled Data](https://www.researchgate.net/publication/325993975_Handwriting_Recognition_of_Historical_Documents_with_Few_Labeled_Data) (please cite the paper if you use this code in your research paper). This code was also used for the baseline system in [Fine-tuning Handwriting Recognition systems with Temporal Dropout](https://www.researchgate.net/publication/348958179_Fine-tuning_Handwriting_Recognition_systems_with_Temporal_Dropout).\n\nThis code is free for academic and research use. For commercial use of the code please contact [Edgard Chammas](mailto:contact@edgard.net).\n\nTo help run the system, sample images from [ICDAR2017 Competition on Handwritten Text Recognition on the READ Dataset](https://scriptnet.iit.demokritos.gr/competitions/8/) are added.\n\n\u003cimg src=\"https://github.com/0x454447415244/HandwritingRecognitionSystem/raw/master/image.jpg\" width=\"30%\"\u003e\n\n## Configuration\nGeneral configuration can be found in config.py\n\nCNN-specific architecture configuration can be found in cnn.py\n\n## Training\n```\npython train.py\n```\nThis will generate a text log file and a Tensorflow summary.\n\n\u003cimg src=\"https://github.com/0x454447415244/HandwritingRecognitionSystem/blob/master/TensorBoard.png\" width=\"100%\"\u003e\n\n## Decoding\n```\npython test.py\n```\nThis will generate, for each image, the line transcription. The output will be written to decoded.txt by default.\n\n```\npython compute_probs.py\n```\nThis will generate, for each image, the posterior probabilities at each timestep. Files will be stored in Probs by default.\n\n## Dependencies\n- Tensorflow\n- OpenCV-Python\n\n## Citation\nPlease cite the following paper if you use this code in your research paper:\n```\n@inproceedings{chammas2018handwriting,\n  title={Handwriting Recognition of Historical Documents with few labeled data},\n  author={Chammas, Edgard and Mokbel, Chafic and Likforman-Sulem, Laurence},\n  booktitle={2018 13th IAPR International Workshop on Document Analysis Systems (DAS)},\n  pages={43--48},\n  year={2018},\n  organization={IEEE}\n}\n```\n\n## Acknowledgment\nWe gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.\n\n\u003cimg src=\"https://upload.wikimedia.org/wikipedia/sco/thumb/2/21/Nvidia_logo.svg/1280px-Nvidia_logo.svg.png\" width=\"20%\"\u003e\n\n## Contributions\nFeel free to send your pull request or open issues.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F0x454447415244%2FHandwritingRecognitionSystem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2F0x454447415244%2FHandwritingRecognitionSystem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F0x454447415244%2FHandwritingRecognitionSystem/lists"}