EADST

Brazilian Coffee Scenes Dataset (BCS) has five folders, and each folder has coffee and uncoffee images. So I wrote a python file to split BCS into two folders - Coffee and Uncoffee.

Here is the splited zip.

• BCS Split

Here is the code.

import os, shutil

path = "D:\\brazilian_coffee_scenes\\fold1"
new_path = "D:\\brazilian_coffee_scenes"
cls_dict = {}
path_list = os.listdir(path)
with open("fold1.txt", "r+") as f:
    for line in f.readlines():
        lst = line.strip().split("ffee.")
        if lst[0] not in cls_dict.keys():
            cls_dict[lst[0]] = [lst[1]]
        else:
            cls_dict[lst[0]].append(lst[1])


for name in path_list:
    if name[:-4] in cls_dict['co']:
        number = "1"
    elif name[:-4] in cls_dict['nonco']:
        number = "2"
    else:
        number = "3"
    file = os.path.join(path, name)
    new_file = os.path.join(new_path, number, name)
    shutil.copyfile(file, new_file)

Brazilian Coffee Scenes Dataset (BCS)

- [BCS Dataset Webpage](http://patreo.dcc.ufmg.br/2017/11/12/brazilian-coffee-scenes-dataset/)

- Paper: O. A. B. Penatti, K. Nogueira, J. A. dos Santos. Do Deep Features Generalize from Everyday Objects to Remote Sensing and Aerial Scenes Domains? In: EarthVision 2015, Boston. IEEE Computer Vision and Pattern Recognition Workshops, 2015.