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Arabic Image Captioning Dataset
The multimodal dataset features a diverse array of images accompanied by Arabic language captions for each image. It encompasses image data, text captions, and comprehensive metadata.
Category
Visual Caption Dataset
Total Volume
25,000+ Captions
Last updated
Aug 2024
Number of participants
100+
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About This OTS Dataset
Introduction
Welcome to the Arabic Language Image Captioning Dataset! A collection of Images with associated text captions to facilitate the development of AI models capable of generating high-quality captions for images. This dataset is meticulously crafted to support research and innovation in computer vision and natural language processing.
Image Data
This dataset features over 5,000 high-resolution images sourced from diverse categories and scenes. Each image is meticulously selected to encompass a wide array of contexts, objects, and environments, ensuring comprehensive coverage for training robust image captioning models.
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Sources:
Images are sourced from public databases and proprietary collections.
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Clarity and Relevance:
Each image is vetted for visual clarity and relevance, ensuring it accurately represents real-world scenarios.
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Copyright:
All selected images are free from copyright restrictions, allowing for unrestricted use in research and development.
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Format:
Images in the dataset are available in various formats like JPEG, PNG, and HEIC.
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Image Categories:
The dataset spans a wide range of image categories to ensure thorough training, fine-tuning, and testing of image captioning models. categories include:
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Daily Life:
Images about household objects, activities, and daily routines.
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Nature and Environment:
Images related to natural scenes, plants, animals, and weather.
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Technology and Gadgets:
Images about electronic devices, tools, and machinery.
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Human Activities:
Images about people, their actions, professions, and interactions.
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Geography and Landmarks:
Images related to specific locations, landmarks, and geographic features.
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Food and Dining:
Images about different foods, meals, and dining settings.
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Education:
Images related to educational settings, materials, and activities.
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Sports and Recreation:
Images about various sports, games, and recreational activities.
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Transportation:
Images about vehicles, travel methods, and transportation infrastructure.
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Cultural and Historical:
Images about cultural artifacts, historical events, and traditions.
Caption Data
Each image in the dataset is paired with a high-quality descriptive caption. These captions are carefully crafted to provide detailed and contextually rich descriptions of the images, enhancing the dataset's utility for training sophisticated image captioning algorithms.
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Human Generated:
Each caption is generated by native Arabic people.
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Quality Assurance:
Captions are meticulously reviewed for linguistic accuracy, coherence, and relevance to the corresponding images.
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Contextual Relevance:
Captions are generated by keeping the visual insights like objects, scenes, actions, and settings depicted in the images.
Metadata
Each image-caption pair is accompanied by comprehensive metadata to facilitate informed decision-making in model development:
•Image File Name
•Category
•Caption
Usage and Applications
The Image Captioning Dataset serves various applications across different domains:
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Training Image Captioning Models:
Provides high-quality data for training and fine-tuning Generative AI models to generate accurate and contextually relevant captions for images.
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Content Understanding:
Facilitates automated content analysis and understanding in fields such as media, entertainment, and education.
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Accessibility Enhancement:
Supports the development of tools that generate descriptive captions for visually impaired individuals, improving accessibility to visual content.
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Multimodal Learning:
Enables research in multimodal AI, where models learn to associate images with textual descriptions to enhance cross-modal understanding.
Secure and Ethical Collection
•Our proprietary platform “Yugo” was used throughout the process of this dataset creation.
•Throughout the dataset creation process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.
•It does not include any personally identifiable information, which makes the dataset safe to use.
•The content included in the dataset does not infringe upon any copyrights or intellectual property rights.
Updates and Customization
We understand the importance of evolving datasets to meet diverse research needs. Therefore, our dataset is regularly updated with new images and captions captured in various real-world conditions.
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Image Categories:
The addition of new images in any specific categories can be added and question-answer pairs can be generated as per requirement.
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Custom Language:
A similar dataset can be prepared in any specific language.
License
This Arabic Language Image Captioning Dataset, created by FutureBeeAI, is available for commercial use.
Use Cases
Image Caption Models
Content Understanding
Multi Modal Learning
Dataset Sample(s)
Samples will be available soon!
Contact us to get the samples immediately for this dataset.
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Dataset Details
Dataset Type
Image Captioning Dataset
Language
Arabic
Media
Multi-Modal Image & Text
Image Volume
5000+
Caption Volume
25000+ Captions
Image File Details
Image Format
JPEG, PNG, HEIC
Dataset Format
JSON, XLXS, TXT
Domain
Multiple
Annotation
Upon Request
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