Created
August 5, 2018 12:29
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# organize imports | |
import os | |
import glob | |
import datetime | |
# print start time | |
print ("[INFO] program started on - " + str(datetime.datetime.now)) | |
# get the input and output path | |
input_path = "/content/flower-recognition/jpg" | |
output_path = "/content/flower-recognition/dataset/train" | |
# get the class label limit | |
class_limit = 17 | |
# take all the images from the dataset | |
image_paths = glob.glob(input_path + "\\*.jpg") | |
# variables to keep track | |
label = 0 | |
i = 0 | |
j = 80 | |
# flower17 class names | |
class_names = ["daffodil", "snowdrop", "lilyvalley", "bluebell", "crocus", | |
"iris", "tigerlily", "tulip", "fritillary", "sunflower", | |
"daisy", "coltsfoot", "dandelion", "cowslip", "buttercup", | |
"windflower", "pansy"] | |
# change the current working directory | |
os.chdir(output_path) | |
# loop over the class labels | |
for x in range(1, class_limit+1): | |
# create a folder for that class | |
os.system("mkdir " + class_names[label]) | |
# get the current path | |
cur_path = output_path + "\\" + class_names[label] + "\\" | |
# loop over the images in the dataset | |
for image_path in image_paths[i:j]: | |
original_path = image_path | |
image_path = image_path.split("\\") | |
image_path = image_path[len(image_path)-1] | |
os.system("copy " + original_path + " " + cur_path + image_path) | |
i += 80 | |
j += 80 | |
label += 1 | |
# print end time | |
print ("[INFO] program ended on - " + str(datetime.datetime.now)) |
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