High-Quality Training Datasets

This dataset contains 200,000 sets of images and bilingual captions (Chinese and English) featuring landmark buildings from over 20 countries, including the United States, United Kingdom, France, Germany, and Russia. Each set includes 1–10 images of a specific landmark, captured from different angles, distances, and time periods. The dataset covers approximately 80,000 domestic landmarks and 120,000 international ones. Types of landmarks include commercial buildings, ancient architecture, monuments, libraries, and scenic spots. Annotations include landmark country, city, location, category, and descriptive captions. This high-quality dataset is ideal for training models in landmark recognition, image classification, multilingual image captioning, and image-to-text retrieval.

This 3D high-fidelity synthetic dataset simulates real-world Driver Monitoring System (DMS) environments using photorealistic 3D scene modeling. It includes multi-modal sensor outputs such as camera images, videos, and point clouds, all generated through simulation. The dataset is richly annotated with object classification, detection, and segmentation labels, as well as human pose data (head, eye, arm, and leg position/orientation), camera parameters, and temporal metadata such as illumination and weather conditions. Ideal for training and evaluating models in autonomous driving, robotics, driver monitoring, computer vision, and synthetic perception tasks.

This dataset is collected from the Japanese OKWAVE Q&A platform and includes large-scale parsed and processed text data suitable for LLM training and Japanese natural language understanding. It contains structured fields such as questions, answers, categories, timestamps, user metadata, and supplementary explanations. As of April 2025, the dataset includes 8.4 million questions with 2.3 billion words, 27 million answers totaling 7.6 billion words, 15.5 million thank-you messages (1.7 billion words), and 2.1 million supplementary replies (360 million words). Continuously updated and rich in user-generated content, this dataset is ideal for building Japanese conversational AI, ChatGPT fine-tuning, question answering systems, text summarization, and semantic parsing models. All data complies with relevant data usage and privacy regulations.

This dataset includes 500 hours of scripted Tamil monologue speech collected using smartphones. Each sample is transcribed with text content and metadata such as speaker ID, gender, and age. The dataset features diverse speakers from various regions, making it highly representative of real-world Tamil language use and suitable for automatic speech recognition (ASR), text-to-speech (TTS), voice activity detection (VAD), and natural language processing (NLP) tasks. Validated by leading AI companies, the dataset is designed to enhance model robustness in multilingual environments and low-resource languages. All data was collected in full compliance with global privacy regulations including GDPR, CCPA, and PIPL, ensuring ethical sourcing and responsible AI development.

Lao Scripted Monologue Smartphone speech dataset, collected from monologue based on given scripts. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Chinese Multi-emotional Modal particle and Natural Conversation Speech Synthesis Corpus, is recorded by multiple native Chinese voice actors. It not only includes sentences rich in modal particles that align with daily expression habits, but also encompasses free conversation data on given topics. In each conversation, the audio of each speaker is independently stored in their respective tracks. Professional phoneticians have annotated information such as text content, meeting the precise requirements for speech synthesis research and development to a full extent.

2,499,771 Boxes 7,262 Images Human Facial Skin Defects Dataset.The data includes the following seven types of facial skin defects: acne, moles, scars, herpes (sores), speckles, freckles, and others. This data can be used for tasks such as skin defects detection.

Burmese Scripted Monologue Smartphone speech dataset, collected from monologue based on given prompts. Transcribed with text content. Our dataset was collected from extensive and diversify speakers, geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Fine-Tuning text data set for English LLM General Domain SFT, a training resource specifically designed for AI model optimization, significantly enhances the model's instruction understanding and execution capabilities, double-checked by linguistic experts and AI engineers, perfectly supports the fine-tuning needs of mainstream pre-trained models.

This dataset features 30 million high-resolution video clips sourced from authorized and legally compliant channels. Each video offers exceptional clarity, color accuracy, and scene diversity across various environments and themes. All clips include clearly documented copyright ownership and commercial usage rights, making them safe and reliable for both academic research and business applications. The dataset is ideal for computer vision tasks such as video classification, action recognition, multimodal learning, object tracking, and content generation. Whether you're training deep learning models or sourcing clean, scalable visual data, this video dataset offers a comprehensive, large-scale solution.

This dataset contains 80 million high-quality vector images (SVG, EPS, AI formats), offering a vast collection for use in computer vision, machine learning, and creative applications. Each image is copyright-cleared and legally sourced through authorized channels, with transparent usage rights for both commercial and academic purposes. The dataset features a wide variety of vector content—icons, illustrations, infographics, and more—with excellent color fidelity and scalable resolution. Ideal for AI model training (e.g., image classification, object recognition), generative design models, and creative design inspiration, this resource ensures traceable IP rights and enables safe, large-scale usage in real-world environments.

This image database contains 200 million high-quality images that have undergone professional review. The resources are diverse in type, featuring high resolution and clarity, excellent color accuracy, and rich detail. All materials have been legally obtained through authorized channels, with clear indications of copyright ownership and usage authorization scope. The entire collection provides commercial-grade usage rights and has been granted permission for scientific research use, ensuring clear and traceable intellectual property attribution. The vast and high-quality image resources offer robust support for a wide range of applications, including research in the field of computer vision, training of image recognition algorithms, and sourcing materials for creative design, thereby facilitating efficient progress in related areas.