File size: 2,153 Bytes
94e47fe 8f9376d 94e47fe 8f9376d 0cd915e e2ee18d 96fa747 14f61a9 e2ee18d 14f61a9 8f9376d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
---
license: cc-by-nc-nd-4.0
language:
- en
metrics:
- accuracy
pipeline_tag: image-classification
tags:
- biology
- agriculture
---
Based on Inception V3
K Plant Disease Detection 2 Epoch 10
53 diffrent (class) diseased/healthy types of plant photos used
The reason of low accuracy is It gets confused because of same types of diseases of diffrent types of plants like "Peach___Bacterial_spot" and "Tomato___Bacterial_spot"
Here is the list of datasets used to train:
- [tomato dataset by Ashishmotwani](https://www.kaggle.com/datasets/ashishmotwani/tomato)
- [coffee-plant-disease dataset by Coffeedisease](https://www.kaggle.com/datasets/coffeedisease/coffee-plant-disease)
- [chili-plant-disease dataset by Dhenyd](https://www.kaggle.com/datasets/dhenyd/chili-plant-disease)
- [rice-leaf-diseases datase by Vbookshelf](https://www.kaggle.com/datasets/vbookshelf/rice-leaf-diseases)
- [new-plant-diseases-dataset by Vipool](https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset)
Device used: 8XLarge - 32 cores - 256 GB RAM - 100Gi Disk
Provider: Saturn Cloud
# Accuracy Metrics



 |