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https://github.com/liuxindazz/PDD271

Last synced: 9 days ago
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Host: GitHub
URL: https://github.com/liuxindazz/PDD271
Owner: liuxindazz
Created: 2020-10-08T07:42:12.000Z (about 4 years ago)
Default Branch: main
Last Pushed: 2021-09-02T12:20:16.000Z (about 3 years ago)
Last Synced: 2024-08-02T15:22:23.337Z (3 months ago)
Size: 7.05 MB
Stars: 7
Watchers: 2
Forks: 5
Open Issues: 1
Metadata Files:
- Readme: README.md

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README

# PDD271
This is a Python3 / Pytorch implementation of PDD271, as described in the following paper:

**Plant Disease Recognition:A Large-Scale Benchmark Dataset and a Visual Region and Loss Reweighting Approach**, by
Xinda Liu, Weiqing Min, Shuhuan Mei, Lili Wang, and Shuqiang Jiang

which has been accepted by IEEE Transactions on Image Processing as a regular paper.
To facilitate the plant disease recognition research, we construct a new large-scale plant disease dataset with 271 plant disease
categories and 220,592 images. Based on this dataset, we tackle plant disease recognition via reweighting both visual regions
and loss to emphasize diseased parts.
![avatar](https://github.com/liuxindazz/PDD271/raw/main/datasetShow.png)
Disease leaf image samples from various categories of PDD271 (one samples per category). The dataset contains three macro-classes:
Fruit Tree, Vegetable, and Field Crops.

Due to the company's policy restrictions, we cannot open source pre-trained models and related codes, and can only open source a part of the data set for everyone to use.

## Dataset Sample
The PDD271 dataset belongs to the [Beijing Puhui Sannong Technology Co. Ltd.](https://www.aiphsn.com/)
You can download the dataset sample in
url: https://drive.google.com/file/d/1QMR1bUfEuMbZz-Mb3u2IXdbMgz7oj2Pe/view?usp=sharing