{"id":25764690,"url":"https://github.com/akshadk7/multi-label-genre-classification","last_synced_at":"2026-02-25T05:35:52.618Z","repository":{"id":250137495,"uuid":"431292804","full_name":"AkshadK7/Multi-Label-Genre-Classification","owner":"AkshadK7","description":"A Tensorflow ConvNet Approach to the Multi Label Genre Classification on Movie Posters","archived":false,"fork":false,"pushed_at":"2025-02-10T10:54:34.000Z","size":451,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-10T11:36:55.592Z","etag":null,"topics":["cnn-keras","convolutional-neural-networks","genre-classifier","multi-label-image-classification","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/AkshadK7.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"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":"2021-11-24T00:07:44.000Z","updated_at":"2025-02-10T10:54:37.000Z","dependencies_parsed_at":"2024-07-25T12:23:07.089Z","dependency_job_id":null,"html_url":"https://github.com/AkshadK7/Multi-Label-Genre-Classification","commit_stats":null,"previous_names":["akshadk7/multi-label-genre-classification"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AkshadK7%2FMulti-Label-Genre-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AkshadK7%2FMulti-Label-Genre-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AkshadK7%2FMulti-Label-Genre-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AkshadK7%2FMulti-Label-Genre-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AkshadK7","download_url":"https://codeload.github.com/AkshadK7/Multi-Label-Genre-Classification/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240935268,"owners_count":19881123,"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-keras","convolutional-neural-networks","genre-classifier","multi-label-image-classification","tensorflow"],"created_at":"2025-02-26T21:20:03.216Z","updated_at":"2026-02-25T05:35:47.595Z","avatar_url":"https://github.com/AkshadK7.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Multi-Label Genre Classification\n\nA TensorFlow Convolutional Neural Network (ConvNet) Approach to Multi-Label Genre Classification on Movie Posters.\n\n## Overview\n\nThis project implements a Convolutional Neural Network (CNN) using TensorFlow to perform multi-label genre classification of movie posters. The model analyzes visual features of movie posters to predict multiple genres associated with each movie.\n\n## Repository Contents\n\n- `Multi_Label_Genre_Classification.ipynb`: Jupyter Notebook detailing data preprocessing, model architecture, training procedures, and evaluation metrics.\n- `LICENSE`: MIT License file.\n\n## Requirements\n\n- Python 3.x\n- Jupyter Notebook\n- TensorFlow\n- Keras\n- Pandas\n- NumPy\n- Scikit-learn\n- Matplotlib\n\n## Setup Instructions\n\n1. **Clone the Repository**:\n   ```bash\n   git clone https://github.com/AkshadK7/Multi-Label-Genre-Classification.git\n   cd Multi-Label-Genre-Classification\n   ```\n\n2. **Install Dependencies**:\n   It's recommended to use a virtual environment to manage dependencies.\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. **Run the Jupyter Notebook**:\n   ```bash\n   jupyter notebook Multi_Label_Genre_Classification.ipynb\n   ```\n\n## Usage\n\n- Open the `Multi_Label_Genre_Classification.ipynb` notebook.\n- Follow the steps to preprocess the data, build and train the CNN model, and evaluate its performance.\n- Modify the notebook as needed to experiment with different model architectures or parameters.\n\n## Results\n\nThe notebook provides performance metrics and visualizations comparing the model's predictions to the actual genres. These insights help assess the model's accuracy and identify areas for improvement.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](https://github.com/AkshadK7/Multi-Label-Genre-Classification/blob/main/LICENSE) file for details.\n\n## Acknowledgements\n\nSpecial thanks to the contributors of the datasets and the open-source community for providing tools and libraries that made this project possible.\n```\n\n*Note: Ensure that the `requirements.txt` file includes all necessary dependencies for the project. If it doesn't exist, you may need to create it by listing the required packages.* \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakshadk7%2Fmulti-label-genre-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakshadk7%2Fmulti-label-genre-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakshadk7%2Fmulti-label-genre-classification/lists"}