def CreateDataSet(file_path):
""" demo :
file_path: ./datasets/
datasets/
train/
Classification_1/
img_1.jpg
img_2.jpg
img_3.jpg
...
Classification_2/
img_1.jpg
img_2.jpg
img_3.jpg
...
Classification_3/
...
val/
Classification_1/
...
Classification_2/
...
test/
... """
class_train_filename = os.listdir(file_path + 'train' + '/')
class_val_filename = os.listdir(file_path + 'val' + '/')
class_test_filename = os.listdir(file_path + 'test' + '/')
train_data, val_data, test_data = [], [], []
train_label, val_label, test_label = [], [], []
for index in range(len(class_train_filename)):
path = file_path + 'train' + '/' + class_train_filename[index]
dir_name_list = os.listdir(path + '/')
for item in dir_name_list:
img_path = path + '/' + item
item_image = cv2.imread(img_path) # 读取图片数据信息
train_data.append(item_image)
train_label.append(class_train_filename[index])
for index in range(len(class_val_filename)):
path = file_path + 'val' + '/' + class_val_filename[index]
dir_name_list = os.listdir(path + '/')
for item in dir_name_list:
img_path = path + '/' + item
item_image = cv2.imread(img_path)
val_data.append(item_image)
val_label.append(class_val_filename[index])
for index in range(len(class_test_filename)):
path = file_path + 'test' + '/' + class_test_filename[index]
dir_name_list = os.listdir(path + '/')
for item in dir_name_list:
img_path = path + '/' + item
item_image = cv2.imread(img_path)
test_data.append(item_image)
test_label.append(class_test_filename[index])
return train_data, train_label, \
val_data, val_label, \
test_data, test_label
在机器学习和深度学习中创建属于自己的数据集
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转载自blog.csdn.net/Stybill_LV_/article/details/110847179
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