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important for improving production efficiency and carrying out scientific research. However, due to the large number of plant species and morphological similarities, traditional manual identification methods are time-consuming and labor-intensive, and prone to misjudgment. Therefore, there is an urgent need for an efficient and accurate automated identification system in current technology. This dataset aims to provide high-quality image sample resources for the automated identification and classification of orchids, meeting the needs of intelligent agriculture systems and ecological research.The images in this dataset are sourced from actual gardens and flower plantations, with collection tools including high-resolution cameras and drones, collected in outdoor scenes under natural light conditions. In terms of quality control measures, we ensured the accuracy and reliability of the data annotations through multiple rounds of expert annotation and consistency checks. The annotation team consists of 20 researchers with a botanical background. Data preprocessing includes image enhancement, denoising, and normalization to improve sample quality and meet diverse algorithmic needs. The data is ultimately stored in JPEG format and organized by plant species for ease of access and use.This dataset has significant advantages in terms of data quality, with an annotation accuracy reaching a high level of 98%, and extremely high consistency after multiple rounds of review. In terms of technical innovation, augmented reality annotation methods and the latest machine learning preprocessing techniques were adopted, driving the generalization capability of the data. In practical applications, this dataset significantly improves the accuracy and response speed of orchid identification systems and is more rigorous in detail compared to other similar datasets, making it suitable for complex ecosystem analyses. Additionally, due to the diversity of collection regions and species, this dataset possesses rarity and wide applicability, and can be extended to other plant identification and ecological monitoring tasks.","2026-02-04 17:11:19","2026-10-19 17:44:17","0.00",731,500,0,"orchid identification, garden flower identification, agricultural image data, plant image database, horticultural management dataset","High-quality orchid identification image dataset, aiding intelligent agriculture.","JPG","1.3G","plant identification, horticultural management, plant classification, agricultural technology, ecological research","image classification, species identification, plant detection, machine vision, precision agriculture 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fruiting.",{"id":605,"name":606,"field":607,"intro":608,"type":590},7128,"Flower Color","flower_color","The color of the Dendrobium flowers.",{"id":610,"name":611,"field":612,"intro":613,"type":590},7129,"Leaf Shape","leaf_shape","The leaf shape characteristics of the Dendrobium.",{"id":615,"name":616,"field":617,"intro":618,"type":619},7130,"Blossom Count","blossom_count","The number of Dendrobium blossoms in the image.","int",{"id":621,"name":622,"field":623,"intro":624,"type":625},7131,"Stem Height","stem_height","The height of the Dendrobium stem in centimeters.","float",{"id":627,"name":628,"field":629,"intro":630,"type":590},7132,"Leaf Color","leaf_color","The color of the Dendrobium leaves.",{"id":632,"name":633,"field":634,"intro":635,"type":590},7133,"Environment Condition","environment_condition","The light, humidity, and other conditions of the environment where the Dendrobium is located.",{"id":637,"name":638,"field":639,"intro":640,"type":590},7134,"Disease Symptom","disease_symptom","Possible disease symptoms present on the Dendrobium as observed in the image.",{"id":642,"name":643,"field":644,"intro":645,"type":590},7135,"Background Type","background_type","The type of background in the image, such as natural, horticultural facilities, etc.",[647,651,655,659,663],{"id":648,"question":649,"answer":650},5069,"What image content does the Orchid Identification Image Dataset include?","The dataset includes high-resolution images of specific Dendrobium species found in garden flowers.",{"id":652,"question":653,"answer":654},5070,"How can the Orchid Identification Image Dataset improve agricultural productivity?","By improving the accuracy of dendrobium identification, the dataset can help agricultural practitioners to plant and manage more effectively.",{"id":656,"question":657,"answer":658},5071,"Which research fields is the Orchid Identification Image Dataset suitable for?","The dataset is suitable for agricultural research, plant taxonomy, 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