datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
fruit-and-vegetable-image-recognitionsudoku-image-recognition
Dataset Card for Sudoku Image Recognition
Images of Sudoku puzzles for puzzle recognition. This dataset was used to bootstrap the Sudoku OCR engine.
Dataset Details
Dataset Description
This dataset consists of 1400 labelled images of Sudoku puzzles. It is intended for training and evaluating a system that can automatically determine the state of each cell in the puzzle: whether it is solved or unsolved, and which digits it contains. The images are split into… See the full description on the dataset page: https://huggingface.co/datasets/Lexski/sudoku-image-recognition.face-recognition-image-dataset
Image Dataset of face images for compuer vision tasks
Dataset comprises 500,600+ images of individuals representing various races, genders, and ages, with each person having a single face image. It is designed for facial recognition and face detection research, supporting the development of advanced recognition systems.
By leveraging this dataset, researchers and developers can enhance deep learning models, improve face verification and face identification techniques, and refine… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/face-recognition-image-dataset.Infant-Sleep-Posture-Recognition-Image-Dataset
Infant Sleep Posture Recognition Image Dataset
Currently, there are many challenges in improving infant sleep safety, including the difficulty of assessing posture and monitoring sleep status without affecting normal infant sleep. Existing monitoring equipment often relies on clothing sensors, which may cause discomfort and excessive interference. This dataset aims to address the risk of asphyxiation caused by incorrect infant sleep posture through visual recognition technology… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Infant-Sleep-Posture-Recognition-Image-Dataset.Amusement-Park-Game-Facility-Recognition-Image-Dataset
Amusement Park Game Facility Recognition Image Dataset
In the retail e-commerce sector, as consumer demand for amusement park facilities increases, merchants face challenges in quickly identifying and managing various facilities. Existing image recognition technologies still lack in accuracy and speed, especially in scenarios with diverse facility combinations. This dataset aims to enhance the precision and efficiency of amusement park facility recognition, satisfying the business… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Amusement-Park-Game-Facility-Recognition-Image-Dataset.Pansy-Recognition-Image-Dataset
Pansy Recognition Image Dataset
Currently, garden management faces the challenge of efficiently and accurately identifying flower varieties. Traditional manual identification relies on experience and is inefficient. Existing image recognition technologies still need improvement in the accuracy of specific flower types, especially in complex backgrounds. This dataset aims to address common accuracy deficiencies in pansy recognition by providing a large number of high-quality images… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Pansy-Recognition-Image-Dataset.Strawflower-Recognition-Image-Dataset
Strawflower Recognition Image Dataset
In the agriculture, forestry, and fisheries domains, horticultural management and plant care face significant challenges. Improving accuracy and efficiency through automation and intelligent systems is a crucial transformation direction for the industry. Existing solutions often use traditional manual recognition or simple feature matching methods, which are easily affected by external environments and are inefficient. This dataset aims to solve… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Strawflower-Recognition-Image-Dataset.Amusement-Park-Game-Facility-Recognition-Image-Dataset
Amusement Park Game Facility Recognition Image Dataset
In the retail e-commerce sector, as consumer demand for amusement park facilities increases, merchants face challenges in quickly identifying and managing various facilities. Existing image recognition technologies still lack in accuracy and speed, especially in scenarios with diverse facility combinations. This dataset aims to enhance the precision and efficiency of amusement park facility recognition, satisfying the business… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Amusement-Park-Game-Facility-Recognition-Image-Dataset.Infant-Sleep-Posture-Recognition-Image-Dataset
Infant Sleep Posture Recognition Image Dataset
Currently, there are many challenges in improving infant sleep safety, including the difficulty of assessing posture and monitoring sleep status without affecting normal infant sleep. Existing monitoring equipment often relies on clothing sensors, which may cause discomfort and excessive interference. This dataset aims to address the risk of asphyxiation caused by incorrect infant sleep posture through visual recognition technology… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Infant-Sleep-Posture-Recognition-Image-Dataset.Ornamental-Flowers-Plum-Recognition-Image-Dataset
Ornamental Flowers Plum Recognition Image Dataset
In the current field of agriculture, forestry, and fisheries, plant recognition, especially the recognition of plum varieties, faces challenges of low efficiency and insufficient accuracy in manual recognition. Existing solutions largely depend on human experience and simple image retrieval, which are inadequate to meet the recognition needs under complex varieties and environments. This dataset aims to enhance the automation and… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Ornamental-Flowers-Plum-Recognition-Image-Dataset.fruit-and-vegetable-image-recognitionGarden-Plant-Tamarisk-Recognition-Image-Dataset
Garden Plant Tamarisk Recognition Image Dataset
In agricultural and garden management, accurately identifying and classifying flowers is an important and challenging task. Traditional manual recognition methods are inefficient, easily influenced by the professional capability of the identifier, and difficult to promote in large-scale applications. Existing automated solutions, though somewhat effective, are often limited by insufficient data and inaccurate annotations. The… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Garden-Plant-Tamarisk-Recognition-Image-Dataset.Garden-Flower-Conical-Hydrangea-Image-Recognition-Dataset
Garden Flower Conical Hydrangea Image Recognition Dataset
With the rapid development of the landscaping industry, garden plants, especially flowers, have a wide variety, making accurate identification and classification a major challenge for the industry. Existing manual identification and traditional image recognition methods have shortcomings such as being time-consuming and having low accuracy. The construction of this dataset aims to enhance the accuracy and efficiency of… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Garden-Flower-Conical-Hydrangea-Image-Recognition-Dataset.raw_is_dataset_for_image_recognitionPansy-Recognition-Image-Dataset
Pansy Recognition Image Dataset
Currently, garden management faces the challenge of efficiently and accurately identifying flower varieties. Traditional manual identification relies on experience and is inefficient. Existing image recognition technologies still need improvement in the accuracy of specific flower types, especially in complex backgrounds. This dataset aims to address common accuracy deficiencies in pansy recognition by providing a large number of high-quality images… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Pansy-Recognition-Image-Dataset.Pharmacy-Drug-Image-Recognition-Dataset
Pharmacy Drug Image Recognition Dataset
The dataset is characterized by 99% annotation accuracy and 95% annotation consistency. It uses innovative multimodal image enhancement technology and quality assessment methods specific to medical images, ensuring excellent performance and a 92% recognition accuracy in various usage environments. In comparison with other medical image datasets, this dataset stands out with its refined category annotations and diverse collection conditions… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Pharmacy-Drug-Image-Recognition-Dataset.Face-Recognition-Image-Dataset
Face Recognition Image Dataset
Currently, face recognition is widely used in smart devices, but factors such as environmental changes and lighting effects pose challenges to recognition accuracy. Existing datasets often lack diversity and annotation quality, limiting the algorithm's performance improvement. This dataset aims to improve the accuracy of recognition algorithms by providing a rich diversity of high-quality face images. During data collection, various types of camera… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Face-Recognition-Image-Dataset.Pomegranate-Fruit-Recognition-Image-Dataset-for-Garden-Flowers
Pomegranate Fruit Recognition Image Dataset for Garden Flowers
In the current agricultural sector, efficiently recognizing and managing garden plants, particularly pomegranate fruits, is a significant challenge. Conventional manual recognition and management methods are time-consuming, labor-intensive, and have low accuracy. The application of existing image recognition technologies in complex environments still faces many bottlenecks. The construction of this dataset aims to solve… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Pomegranate-Fruit-Recognition-Image-Dataset-for-Garden-Flowers.Flowers_End_to_End_Image_Recognition_TensorFlowGarden-Floral-and-Flower-Tobacco-Recognition-Image-Dataset
Garden Floral and Flower Tobacco Recognition Image Dataset
In modern agriculture and garden management, swiftly and accurately recognizing and classifying flower species is a major challenge. Traditional manual recognition methods are inefficient and prone to errors. Existing solutions rely on general image datasets, which often lack the precision and diversity specific to flower recognition. This dataset focuses on enhancing the recognition capabilities of flowers and flower… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Garden-Floral-and-Flower-Tobacco-Recognition-Image-Dataset.Amaryllis-Image-Recognition-Dataset
Amaryllis Image Recognition Dataset
Currently, with the rapid development of the horticulture industry, the diversification and increase in the number of flower varieties pose challenges to flower management. Current solutions such as manual recognition and recording are inefficient and prone to errors. The establishment of the Amaryllis Image Recognition Dataset aims to leverage advanced image recognition technology to achieve fast and accurate flower classification, optimizing… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Amaryllis-Image-Recognition-Dataset.Sorting-Center-Package-Manifest-Text-Recognition-Image-Dataset
Sorting Center Package Manifest Text Recognition Image Dataset
The core advantage of the dataset lies in its high-quality image acquisition, high-precision annotation information, and rich data diversity. Annotation accuracy exceeds 98%, ensuring consistency and completeness of information. The technical innovation includes the introduction of advanced data augmentation techniques and quality assessment methods, ensuring efficient utilization and reliability of the data. Its… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Sorting-Center-Package-Manifest-Text-Recognition-Image-Dataset.Garden-Flower-Digitalis-Recognition-Image-Dataset
Garden Flower Digitalis Recognition Image Dataset
In modern horticultural management, accurate identification and monitoring of garden plant species is crucial. However, existing techniques often face issues such as insufficient image resolution and the time-consuming and inaccurate nature of manual recognition. This dataset aims to improve the accuracy and efficiency of automated recognition by providing high-quality images of Digitalis. The images in the dataset were collected… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Garden-Flower-Digitalis-Recognition-Image-Dataset.Rice-Tillering-Recognition-Image-Dataset
Rice Tillering Recognition Image Dataset
The core advantage of this dataset lies in its high quality and high precision annotations, with accuracy exceeding 95%. It provides multi-angle, consistent image data. By introducing advanced semi-automatic annotation techniques and data augmentation techniques such as flipping, rotation, and color adjustment, the diversity and practicality of the dataset are enhanced. When applied to rice tillering recognition tasks, this dataset has… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Rice-Tillering-Recognition-Image-Dataset.ImageRecognitionData
표/그림 객체 인식 데이터셋
본 데이터셋은 논문 및 연구보고서 등 학술문헌의 표와 그림을 자동으로 추출하기 위한 데이터셋이다.
데이터 포맷(JPG, TXT)
유형
설명
JPG
표/그림이 존재하는 연구보고서의 페이지를 이미지 파일로 변환
TXT
각 페이지에 존재하는 표, 그림, 캡션의 레이블 및 좌표 정보를 포함
<표, 그림, 캡션 레이블 및 좌표 정보 예>
데이터 통계
페이지(파일) 수: 9,124개
데이터셋 개수: 표: 7,096 그림: 107,30 표캡션: 6,799 그림캡션: 10,615
레이블 개수: 4 (0: 표, 1: 그림, 2: 표캡션, 3: 그림캡션)
데이터 구축방법
2021~2022년에 등록된 국가R&D보고서를 대상으로 이미지 추출 모델을 이용하여 1차로 표와 그림을 추출하고, 이후 어노테이터가 검증하는 방식으로 구축했다.… See the full description on the dataset page: https://huggingface.co/datasets/KISTI-AIDATA/ImageRecognitionData.31K_Kashmiri_text_and_image_dataset_for_text_RecognitionDirectory Structure:
Zip File/
├── images/
│ ├── 000001.png
│ ├── 000002.png
│ ├── 000003.png
│ ├── ...
│ ├── 031000.png
├── labels.csv
└── metadata.json
Description:
Zip File: The root directory that contains all other files and folders.
images/: A folder containing 31,000 images named sequentially from 000001.png to 031000.png.
labels.csv: A CSV file that includes information about the labels for each image.
metadata.json: A JSON file that contains metadata about the dataset… See the full description on the dataset page: https://huggingface.co/datasets/Omarrran/31K_Kashmiri_text_and_image_dataset_for_text_Recognition.image-recognition
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
{"messages": [{"role": "user", "content": "https://poliedrostorage1.file.core.windows.net/fine-tuning-contador-analogico-agua-dia-noche/1.jpg?sv=2023-11-03&si=fine-tuning-contador-analogico-a-194AD01421A&sr=f&sig=C%2BHLdTnaGjCIeXn4CJehi%2B5j1nlpP%2BcaQXbgR8owPaQ%3D"}, {"role":… See the full description on the dataset page: https://huggingface.co/datasets/poliedrosoftware/image-recognition.cifar10_image_recognition