{"id":19824998,"url":"https://github.com/mjahmadee/image_captioning","last_synced_at":"2026-06-11T17:31:50.219Z","repository":{"id":181360623,"uuid":"666646125","full_name":"MJAHMADEE/Image_Captioning","owner":"MJAHMADEE","description":"Image Captioning","archived":false,"fork":false,"pushed_at":"2024-03-16T12:46:13.000Z","size":23646,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-28T20:45:39.121Z","etag":null,"topics":["computer-vision","image-captioning","nlp"],"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/MJAHMADEE.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":"2023-07-15T05:21:39.000Z","updated_at":"2024-11-09T19:15:19.000Z","dependencies_parsed_at":"2024-03-16T14:26:10.719Z","dependency_job_id":"767f83c5-63a2-41a9-9135-9dc3de4d7dea","html_url":"https://github.com/MJAHMADEE/Image_Captioning","commit_stats":null,"previous_names":["mjahmadee/image_captioning"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MJAHMADEE/Image_Captioning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MJAHMADEE%2FImage_Captioning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MJAHMADEE%2FImage_Captioning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MJAHMADEE%2FImage_Captioning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MJAHMADEE%2FImage_Captioning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MJAHMADEE","download_url":"https://codeload.github.com/MJAHMADEE/Image_Captioning/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MJAHMADEE%2FImage_Captioning/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34211061,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-11T02:00:06.485Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["computer-vision","image-captioning","nlp"],"created_at":"2024-11-12T11:06:40.369Z","updated_at":"2026-06-11T17:31:50.195Z","avatar_url":"https://github.com/MJAHMADEE.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Image Captioning with Neural Networks 🖼️🤖\n\n![Python](https://img.shields.io/badge/Python-3.8-blue.svg)\n![PyTorch](https://img.shields.io/badge/PyTorch-1.8.1-orange.svg)\n![License](https://img.shields.io/badge/License-MIT-green.svg)\n\nImage Captioning with Neural Networks is a deep learning project that combines Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to generate captions for images automatically. This implementation utilizes a pre-trained ResNet model for image feature extraction and an LSTM network for generating textual descriptions of the images.\n\n## Features 🌟\n- Utilizes a pre-trained ResNet-18 model for efficient image feature extraction.\n- Employs an LSTM network for generating descriptive captions based on image features.\n- Supports training with and without fine-tuning of the ResNet model.\n- Includes functionality for both training and testing the model with a custom dataset.\n- Visualizes training loss and sample predictions to assess model performance.\n\n## Setup and Installation 🛠️\n1. Clone the repository from GitHub.\n2. Navigate to the project directory.\n3. Install the required dependencies listed in the `requirements.txt` file.\n\n## Dataset 📁\nThe model is trained and tested on the Flickr8k dataset, which comprises 8,000 images each paired with five different captions. For the purpose of this project, the dataset is pre-processed to align with the model's requirements.\n\n## Training the Model 🚀\nTraining the model involves executing the training script, which will start the training process and save the model weights periodically.\n\n## Testing the Model 🧪\nAfter training, the model's performance can be evaluated by executing the testing script, which generates captions for the images in the test dataset.\n\n## Results and Evaluation 📊\nThe model's performance can be evaluated based on the captions generated for the test images. A qualitative assessment involves comparing the predicted captions against the ground truth captions.\n\n## License 📜\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\n## Acknowledgements 🙌\n- Thanks to the creators of the Flickr8k dataset for providing the resources necessary for training and testing the model.\n- PyTorch documentation for providing comprehensive guides and tutorials.\n\n## Notebook and Copyright\n\u003ca href=\"https://colab.research.google.com/drive/1F-jXcFv6xzmKIH9Z9xIm320AYFRG9lcS?usp=sharing\"\u003e\u003cimg src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"\u003e\u003c/a\u003e\n\n@misc{MJImageCaptioning2023,\n  author = {Mohammad Javad (MJ) Ahmadi},\n  title = {Image Captioning},\n  year = {2023},\n  publisher = {GitHub},\n  journal = {GitHub repository},\n  howpublished = {\\url{https://github.com/MJAHMADEE/Image_Captioning}}\n}\n\n---\nFor more information, please refer to the [official repository](https://github.com/MJAHMADEE/Image_Captioning).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmjahmadee%2Fimage_captioning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmjahmadee%2Fimage_captioning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmjahmadee%2Fimage_captioning/lists"}