📝 Eye Disease Image Dataset

❓A dataset of color fundus images of eye diseases

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A total of 5335 images of healthy and affected eye images were collected from Anwara Hamida Eye Hospital in Faridpur and BNS Zahrul Haque Eye Hospital in Faridpur district with the help of the hospital authorities. Then from these original images, a total of 16242 augmented images are produced by using Rotation, Width shifting, Height shifting, Translation, Flipping, and Zooming techniques to increase the number of data.
Worldwide, eye ailments are recognized as significant contributors to nonfatal disabling conditions. In Bangladesh, 1.5% of adults suffer from blindness, while 21.6% experience low vision. Therefore, eye disease detection is crucial for preserving vision, preventing blindness, and maintaining overall health. Early detection allows for prompt intervention and treatment, preventing irreversible damage and preserving quality of life.

⭐️ https://t.me/datasets1

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📝Bird vs Drone

❓Distinguishing the Skies: A Dataset for Drone vs Bird Classification

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YOLO-based Segmented Dataset for Drone vs. Bird Detection for Deep and Machine Learning Algorithms


Formatted in accordance with the YOLOv7 PyTorch specification, the dataset is organized into three folders: Test, Train, and Valid. Each folder contains two sub-folders—Images and Labels—with the Labels folder including the associated metadata in plaintext format. This metadata provides valuable information about the detected objects within each image, allowing the model to accurately learn and detect drones and birds in varying circumstances. The dataset contains a total of 20,925 images, all with a resolution of 640 x 640 pixels in JPEG format, providing comprehensive training and validation opportunities for machine learning models.

⭐️ https://t.me/datasets1

❓Bird vs Drone

⭐️ https://t.me/datasets1

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If you've worked on an interesting project with this dataset, we’d be happy to share your notebook or GitHub link with us. We’d love to feature your project on the DataScienceN channel so others can benefit from it and give you stars or feedback. This is a great opportunity for your project to get more visibility and be useful to everyone!

📝Emotions dataset

❓Emotions dataset for NLP classification tasks

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This dataset contains a collection of documents and their associated emotions, specifically designed for classification tasks in Natural Language Processing (NLP). The dataset includes a list of documents, each associated with a specific emotion label. It helps you develop machine learning models for identifying various emotions in text.

Dataset Contents:
A list of text documents with emotion labels
The dataset is split into three parts: training (Train), validation (Validation), and testing (Test) for building machine learning models.

⭐️https://t.me/datasets1

❓Emotions

⭐️ https://t.me/datasets1

❓Labelled Faces in the Wild (LFW) Dataset

⭐️https://t.me/datasets1