{"id":26870791,"url":"https://github.com/gabrli/easycnn","last_synced_at":"2025-03-31T07:17:07.428Z","repository":{"id":280320712,"uuid":"941024537","full_name":"Gabrli/EasyCNN","owner":"Gabrli","description":"EasyCNN it's liblary enabling quick creating, training and visualizing convolutional models (CNN).","archived":false,"fork":false,"pushed_at":"2025-03-25T18:47:52.000Z","size":1243,"stargazers_count":4,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-25T19:35:30.769Z","etag":null,"topics":["ai","cnn","deep-learning","easycnn","keras","model","neural-network","news","opencv","python","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Gabrli.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"contributing.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-01T09:52:14.000Z","updated_at":"2025-03-25T18:47:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"ec5fc8f9-797a-4db6-84d7-fe55dba9c8b2","html_url":"https://github.com/Gabrli/EasyCNN","commit_stats":null,"previous_names":["gabrli/easycnn"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabrli%2FEasyCNN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabrli%2FEasyCNN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabrli%2FEasyCNN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabrli%2FEasyCNN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Gabrli","download_url":"https://codeload.github.com/Gabrli/EasyCNN/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246429494,"owners_count":20775808,"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":["ai","cnn","deep-learning","easycnn","keras","model","neural-network","news","opencv","python","tensorflow"],"created_at":"2025-03-31T07:17:06.662Z","updated_at":"2025-03-31T07:17:07.421Z","avatar_url":"https://github.com/Gabrli.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# EasyCNN - Easy Creating and Visualizing CNN Model\n\nEasyCNN it's liblary enabling quick creating, training and visualizing convolutional models (CNN).\n\n\n## Features\n\n- Easy definition of CNN layers\n- Training and evolution models\n- Visualization of the model structure\n- 15 ready to easy and quick use the most popular presets of keras applications\n\n\n\n## Documentation\n\n[Documentation](https://github.com/Gabrli/EasyCNN---docs)\n\n\n\n## Authors\n\n- [@Gabrli](https://github.com/Gabrli)\n\n\n## Tech Stack\n\n**Languages:** Python\n  \n**Libraries:** Tensorflow, Matplotlib, Numpy, OpenCv\n\n## License\n\n[MIT](https://choosealicense.com/licenses/mit/)\n\n\n## FAQ\n\n#### what are the advantages ?\n\n- Very easy and comfortable syntax\n- Full control for developer\n- Automatic data preparation and visualization processes\n\n#### What functionalities are under construction?\n\n- Presets for popular models\n- Exporter and Converter for files with models\n\n\n## Contributing\n\nContributions are always welcome!\n\nSee `contributing.md` for ways to get started.\n\nPlease adhere to this project's `code of conduct`.\n\n\n## Usage/Examples\n\n```python\nfrom easycnn.core import EasyCNN\nfrom easycnn.visualizer import TrainingVisualizer\nimport os\nfrom tensorflow.keras.datasets import cifar10\n\nclass_names = ['car', 'plane', 'cat', 'dog', 'bird', 'deer', 'horse', 'frog', 'ship', 'truck']\n\n(x_train, y_train), (x_test, y_test) = cifar10.load_data()\n\nmy_file = os.path.join(os.path.dirname(__file__), 'car.jpg')\n\nx_train = x_train[:2000]\ny_train = y_train[:2000]\nx_test = x_test[:400]\ny_test = y_test[:400]\nx_train = x_train / 255\nx_test = x_test / 255\n\nmodel = EasyCNN()\nmodel.add_conv(32, 3)\nmodel.add_max_pool(2)\nmodel.add_conv(64, 3)\nmodel.add_max_pool(2)\nmodel.add_conv(128, 3)\nmodel.add_max_pool(2)\nmodel.add_flatten()\nmodel.add_dense(10, activation='softmax')\nmodel.compile()\nhistory = model.train(x_train, y_train, x_test, y_test, epochs=5)\nprediction = model.predict(my_file)\n\nvisualizer = TrainingVisualizer()\nvisualizer.plot_training(history)\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgabrli%2Feasycnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgabrli%2Feasycnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgabrli%2Feasycnn/lists"}