Cherry pick pipeline (PaddlePaddle#7798)

* ppvehicle add customized docs, test=document_fix

* fix pipeline readme.md test=document_fix

* fix pipeline readme.md link test=document_fix

* add licensed to lane_to_mask.py

* ppvehicle_violation.md add args list test=document_fix

deploy/pipeline/README.md

@@ -155,10 +155,10 @@
 
 - [快速开始](docs/tutorials/ppvehicle_press.md)
 
-- [二次开发教程]
+- [二次开发教程](../../docs/advanced_tutorials/customization/ppvehicle_violation.md)
 
 #### 车辆逆行
 
 - [快速开始](docs/tutorials/ppvehicle_retrograde.md)
 
-- [二次开发教程]
+- [二次开发教程](../../docs/advanced_tutorials/customization/ppvehicle_violation.md)

deploy/pipeline/README_en.md

@@ -152,10 +152,10 @@ Click to download the model, then unzip and save it in the `. /output_inference`
 
 - [A quick start](docs/tutorials/ppvehicle_press_en.md)
 
-- [Customized development tutorials]
+- [Customized development tutorials](../../docs/advanced_tutorials/customization/ppvehicle_violation_en.md)
 
 #### Vehicle Retrograde
 
 - [A quick start](docs/tutorials/ppvehicle_retrograde_en.md)
 
-- [Customized development tutorials]
+- [Customized development tutorials](../../docs/advanced_tutorials/customization/ppvehicle_violation_en.md)

deploy/pipeline/tools/create_dataset_list.py

@@ -0,0 +1,147 @@
+# coding: utf8
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserve.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import glob
+import os.path
+import argparse
+import warnings
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(
+        description='PaddleSeg generate file list on cityscapes or your customized dataset.'
+    )
+    parser.add_argument('dataset_root', help='dataset root directory', type=str)
+    parser.add_argument(
+        '--type',
+        help='dataset type: \n'
+        '- cityscapes \n'
+        '- custom(default)',
+        default="custom",
+        type=str)
+    parser.add_argument(
+        '--separator',
+        dest='separator',
+        help='file list separator',
+        default=" ",
+        type=str)
+    parser.add_argument(
+        '--folder',
+        help='the folder names of images and labels',
+        type=str,
+        nargs=2,
+        default=['images', 'labels'])
+    parser.add_argument(
+        '--second_folder',
+        help='the second-level folder names of train set, validation set, test set',
+        type=str,
+        nargs='*',
+        default=['train', 'val', 'test'])
+    parser.add_argument(
+        '--format',
+        help='data format of images and labels, e.g. jpg or png.',
+        type=str,
+        nargs=2,
+        default=['jpg', 'png'])
+    parser.add_argument(
+        '--postfix',
+        help='postfix of images or labels',
+        type=str,
+        nargs=2,
+        default=['', ''])
+
+    return parser.parse_args()
+
+
+def get_files(image_or_label, dataset_split, args):
+    dataset_root = args.dataset_root
+    postfix = args.postfix
+    format = args.format
+    folder = args.folder
+
+    pattern = '*%s.%s' % (postfix[image_or_label], format[image_or_label])
+
+    search_files = os.path.join(dataset_root, folder[image_or_label],
+                                dataset_split, pattern)
+    search_files2 = os.path.join(dataset_root, folder[image_or_label],
+                                 dataset_split, "*", pattern)  # 包含子目录
+    search_files3 = os.path.join(dataset_root, folder[image_or_label],
+                                 dataset_split, "*", "*", pattern)  # 包含三级目录
+    search_files4 = os.path.join(dataset_root, folder[image_or_label],
+                                 dataset_split, "*", "*", "*",
+                                 pattern)  # 包含四级目录
+    search_files5 = os.path.join(dataset_root, folder[image_or_label],
+                                 dataset_split, "*", "*", "*", "*",
+                                 pattern)  # 包含五级目录
+
+    filenames = glob.glob(search_files)
+    filenames2 = glob.glob(search_files2)
+    filenames3 = glob.glob(search_files3)
+    filenames4 = glob.glob(search_files4)
+    filenames5 = glob.glob(search_files5)
+
+    filenames = filenames + filenames2 + filenames3 + filenames4 + filenames5
+
+    return sorted(filenames)
+
+
+def generate_list(args):
+    dataset_root = args.dataset_root
+    separator = args.separator
+
+    for dataset_split in args.second_folder:
+        print("Creating {}.txt...".format(dataset_split))
+        image_files = get_files(0, dataset_split, args)
+        label_files = get_files(1, dataset_split, args)
+        if not image_files:
+            img_dir = os.path.join(dataset_root, args.folder[0], dataset_split)
+            warnings.warn("No images in {} !!!".format(img_dir))
+        num_images = len(image_files)
+
+        if not label_files:
+            label_dir = os.path.join(dataset_root, args.folder[1],
+                                     dataset_split)
+            warnings.warn("No labels in {} !!!".format(label_dir))
+        num_label = len(label_files)
+
+        if num_images != num_label and num_label > 0:
+            raise Exception(
+                "Number of images = {}    number of labels = {} \n"
+                "Either number of images is equal to number of labels, "
+                "or number of labels is equal to 0.\n"
+                "Please check your dataset!".format(num_images, num_label))
+
+        file_list = os.path.join(dataset_root, dataset_split + '.txt')
+        with open(file_list, "w") as f:
+            for item in range(num_images):
+                left = image_files[item].replace(dataset_root, '', 1)
+                if left[0] == os.path.sep:
+                    left = left.lstrip(os.path.sep)
+
+                try:
+                    right = label_files[item].replace(dataset_root, '', 1)
+                    if right[0] == os.path.sep:
+                        right = right.lstrip(os.path.sep)
+                    line = left + separator + right + '\n'
+                except:
+                    line = left + '\n'
+
+                f.write(line)
+                print(line)
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    generate_list(args)