Brassica juncea

Published: 8 April 2024| Version 1 | DOI: 10.17632/n78zj449tv.1
Contributors:
SOUVIK BASAK, Tanmay Sarkar

Description

The dataset comprises over 500 images of pigweed leaves (Brassica juncea album), categorized into two classes: "good" and "bad." These images were captured using a Redmi Note 8 Pro mobile camera against a black background under daylight conditions. **Data Description:** 1. **Classes:** - Good: Represents healthy pigweed leaves that exhibit desired characteristics such as uniform color, absence of discoloration or lesions, and overall vitality. - Bad: Encompasses pigweed leaves showing signs of disease, damage, or other undesirable traits such as discoloration, spots, wilting, or pest infestation. 2. **Image Collection:** - Over 500 images collected in total, with a significant number representing both good and bad instances of pigweed leaves. - Images captured under consistent conditions to maintain uniformity and reduce variability. - Black background utilized to enhance leaf visibility and isolate the subject. 3. **Data Source:** - The images were captured using a Redmi Note 8 Pro mobile camera, ensuring consistent image quality across the dataset. - Daylight conditions were chosen to provide natural lighting, minimizing artificial effects on leaf appearance. 4. **Annotation:** - Each image is labeled according to its class (good or bad), enabling supervised learning tasks. - Annotation may include bounding boxes or masks outlining the leaf area to aid in localization tasks. 5. **Data Preprocessing:** - Images may have undergone preprocessing steps such as resizing, normalization, and background removal to enhance model performance and reduce computational complexity. - Metadata such as image resolution, format, and capture settings may accompany the dataset for reference. 6. **Data Distribution:** - The dataset maintains a balanced distribution between good and bad pigweed leaves, ensuring equal representation of both classes. - Randomization techniques may have been employed during data collection and organization to prevent biases in model training. 7. **Potential Applications:** - The dataset can be utilized for various machine learning tasks, including classification, object detection, and image segmentation. - Applications may include automated agricultural systems for pest detection, disease diagnosis, and crop health monitoring. 8. **Limitations:** - While efforts were made to ensure data consistency and quality, variations in lighting conditions, camera angles, and leaf orientation may introduce some degree of variability. - The dataset primarily focuses on pigweed leaves of Brassica juncea and may not generalize well to other plant species or environmental conditions. In summary, the dataset provides a comprehensive collection of annotated pigweed leaf images suitable for training and evaluating machine learning algorithms in agricultural applications, particularly in the context of plant health assessment and crop management.

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Categories

Biological Classification, Characterization of Food

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