os.path.join(path, 'dataset')
时间: 2023-11-23 15:27:51 浏览: 26
This function joins the path variable and the string 'dataset' together, using the appropriate separator for the current operating system.
For example, if the path is 'C:\Users\John' on Windows, and the string 'dataset' is given as the second argument, the function will return 'C:\Users\John\dataset'.
On Unix-based systems, the separator is '/', so if the path is '/home/user' and the second argument is 'dataset', the function will return '/home/user/dataset'.
This function is useful for constructing file paths in a platform-independent way, as it takes care of using the correct separator depending on the operating system.
相关问题
processed_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "dataset/")
processed_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "dataset/") 是一个用于生成文件路径的代码。它使用了Python的os模块中的一些函数来构建路径。
首先,os.path.abspath(__file__) 返回当前脚本的绝对路径。__file__ 是一个内置变量,表示当前脚本的文件名。
然后,os.path.dirname() 函数返回指定路径的父目录路径。在这里,它返回了当前脚本所在文件的目录路径。
最后,os.path.join() 函数将多个路径组合成一个完整的路径。它接受多个参数,并根据操作系统的规则正确地连接路径。
所以,processed_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "dataset/") 的作用是生成一个包含当前脚本所在目录和子目录 "dataset/" 的完整路径。
将下面代码简洁化:def split_dataset(img_path, target_folder_path, output_path): filename = [] total_imgs = os.listdir(img_path) #for root, dirs, files in os.walk(img_path): for img in total_imgs: filename.append(img) np.random.shuffle(filename) train = filename[:int(len(filename) * 0.9)] test = filename[int(len(filename) * 0.9):] out_images = os.path.join(output_path, 'imgs') if not os.path.exists(out_images): os.makedirs(out_images) out_images_train = os.path.join(out_images, 'training') if not os.path.exists(out_images_train): os.makedirs(out_images_train) out_images_test = os.path.join(out_images, 'test') if not os.path.exists(out_images_test): os.makedirs(out_images_test) out_annotations = os.path.join(output_path, 'annotations') if not os.path.exists(out_annotations): os.makedirs(out_annotations) out_annotations_train = os.path.join(out_annotations, 'training') if not os.path.exists(out_annotations_train): os.makedirs(out_annotations_train) out_annotations_test = os.path.join(out_annotations, 'test') if not os.path.exists(out_annotations_test): os.makedirs(out_annotations_test) for i in train: print(os.path.join(img_path, i)) print(os.path.join(out_images_train, i)) shutil.copyfile(os.path.join(img_path, i), os.path.join(out_images_train, i)) annotations_name = "gt_" + i[:-3] + 'txt' shutil.copyfile(os.path.join(target_folder_path, annotations_name), os.path.join(out_annotations_train, annotations_name)) for i in test: shutil.copyfile(os.path.join(img_path, i), os.path.join(out_images_test, i)) annotations_name = "gt_" + i[:-3] + 'txt' shutil.copyfile(os.path.join(target_folder_path, annotations_name), os.path.join(out_annotations_test, annotations_name))
def split_dataset(img_path, target_folder_path, output_path):
filename = os.listdir(img_path)
np.random.shuffle(filename)
train = filename[:int(len(filename) * 0.9)]
test = filename[int(len(filename) * 0.9):]
out_images = os.path.join(output_path, 'imgs')
os.makedirs(out_images, exist_ok=True)
out_images_train = os.path.join(out_images, 'training')
os.makedirs(out_images_train, exist_ok=True)
out_images_test = os.path.join(out_images, 'test')
os.makedirs(out_images_test, exist_ok=True)
out_annotations = os.path.join(output_path, 'annotations')
os.makedirs(out_annotations, exist_ok=True)
out_annotations_train = os.path.join(out_annotations, 'training')
os.makedirs(out_annotations_train, exist_ok=True)
out_annotations_test = os.path.join(out_annotations, 'test')
os.makedirs(out_annotations_test, exist_ok=True)
for i in train:
img_src = os.path.join(img_path, i)
img_dst = os.path.join(out_images_train, i)
shutil.copyfile(img_src, img_dst)
annotations_name = "gt_" + i[:-3] + 'txt'
annotations_src = os.path.join(target_folder_path, annotations_name)
annotations_dst = os.path.join(out_annotations_train, annotations_name)
shutil.copyfile(annotations_src, annotations_dst)
for i in test:
img_src = os.path.join(img_path, i)
img_dst = os.path.join(out_images_test, i)
shutil.copyfile(img_src, img_dst)
annotations_name = "gt_" + i[:-3] + 'txt'
annotations_src = os.path.join(target_folder_path, annotations_name)
annotations_dst = os.path.join(out_annotations_test, annotations_name)
shutil.copyfile(annotations_src, annotations_dst)