Guava leaves diseases datasets Bangladesh

The dataset, sourced from Vimruli Guava Garden and Floating Market in Jhalakathi, Barisal, categorizes guava leaf and fruit conditions for better crop management. It includes images of healthy and diseased samples, making it a valuable resource for researchers and practitioners working on machine learning models to identify plant diseases. The dataset includes six classes for robust model training.

Dataset Summary:
Location: Vimruli Guava Garden & Floating Market, Jhalakathi, Barisal.
Subjects: Guava leaves and fruits.
Purpose: Classification and detection of guava plant conditions.

Data Distribution:
Classes:
1. Algal Leaves Spot: 100 original, 1320 augmented, 1420 total
2. Dry Leaves: 52 original, 676 augmented, 728 total
3. Healthy Fruit: 50 original, 650 augmented, 700 total
4. Healthy Leaves: 150 original, 1600 augmented, 1750 total
5. Insects Eaten: 164 original, 1720 augmented, 1884 total
6. Red Rust: 90 original, 1170 augmented, 1260 total

Total Samples:
Original: 606
Augmented: 7136
Overall: 7742 samples

Class Details:
1. Algal Leaves Spot: Fungal spots on leaves.
2. Dry Leaves: Leaves dried from environmental/nutrient factors.
3. Healthy Fruit/Leaves: Free of diseases/damage.
4. Insects Eaten: Insect-caused damage on leaves.
5. Red Rust: Reddish spots due to fungal infection.

This dataset is well-suited for training and evaluating machine learning models to detect and classify various conditions of guava plants, aiding in automated disease identification and better agricultural management.