deploy: e8025ca

docs/changelog/index.html

@@ -712,8 +712,8 @@ <h4 id="2023-09-15-v003-update">2023-09-15 v0.0.3 update: <a href="#2023-09-15-v
                 id:  1 ,
                 href: "\/LabelConvert\/docs\/supportconversions\/labelimg_to_yolov5\/",
                 title: "labelImg → YOLOV5",
-                description: "Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelimg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.",
-                content: " Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelimg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.2 --src_dir: the directory where labelImg is stored after labeling. --out_dir: the location where the data is stored after conversion. --val_ratio: the ratio of the generated validation set to the whole data, default is 0.2. --have_test: whether to generate the test part of the data, the default is False. If this parameter appears, it is True. --test_ratio: percentage of the whole data of the test data, default is 0.2. Converted directory structure (see dataset/labelImg_dataset_output for details):\nlabelImg_dataset_output/ ├── classes.txt ├── images │ ├── images(13).jpg │ ├── images(3).jpg │ ├── images4.jpg │ ├── images5.jpg │ └── images7.jpg ├── labels │ ├── images(13).txt │ ├── images(3).txt │ ├── images4.txt │ ├── images5.txt │ └── images7.txt ├── non_labels # This is the catalog without the labeled images. │ └── images6.jpg ├── test.txt ├── train.txt └── val.txt You can further directly convert the dataset/labelImg_dataset_output directory to COCO\nyolov5_to_coco --data_dir dataset/labellImg_dataset_output "
+                description: "Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelImg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.",
+                content: " Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelImg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.2 --src_dir: the directory where labelImg is stored after labeling. --out_dir: the location where the data is stored after conversion. --val_ratio: the ratio of the generated validation set to the whole data, default is 0.2. --have_test: whether to generate the test part of the data, the default is False. If this parameter appears, it is True. --test_ratio: percentage of the whole data of the test data, default is 0.2. Converted directory structure (see dataset/labelImg_dataset_output for details):\nlabelImg_dataset_output/ ├── classes.txt ├── images │ ├── images(13).jpg │ ├── images(3).jpg │ ├── images4.jpg │ ├── images5.jpg │ └── images7.jpg ├── labels │ ├── images(13).txt │ ├── images(3).txt │ ├── images4.txt │ ├── images5.txt │ └── images7.txt ├── non_labels # This is the catalog without the labeled images. │ └── images6.jpg ├── test.txt ├── train.txt └── val.txt You can further directly convert the dataset/labelImg_dataset_output directory to COCO\nyolov5_to_coco --data_dir dataset/labellImg_dataset_output "
             }
         );
     index.add(

docs/index.html

@@ -654,8 +654,8 @@ <h1 class="content-title mb-0">
                 id:  1 ,
                 href: "\/LabelConvert\/docs\/supportconversions\/labelimg_to_yolov5\/",
                 title: "labelImg → YOLOV5",
-                description: "Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelimg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.",
-                content: " Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelimg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.2 --src_dir: the directory where labelImg is stored after labeling. --out_dir: the location where the data is stored after conversion. --val_ratio: the ratio of the generated validation set to the whole data, default is 0.2. --have_test: whether to generate the test part of the data, the default is False. If this parameter appears, it is True. --test_ratio: percentage of the whole data of the test data, default is 0.2. Converted directory structure (see dataset/labelImg_dataset_output for details):\nlabelImg_dataset_output/ ├── classes.txt ├── images │ ├── images(13).jpg │ ├── images(3).jpg │ ├── images4.jpg │ ├── images5.jpg │ └── images7.jpg ├── labels │ ├── images(13).txt │ ├── images(3).txt │ ├── images4.txt │ ├── images5.txt │ └── images7.txt ├── non_labels # This is the catalog without the labeled images. │ └── images6.jpg ├── test.txt ├── train.txt └── val.txt You can further directly convert the dataset/labelImg_dataset_output directory to COCO\nyolov5_to_coco --data_dir dataset/labellImg_dataset_output "
+                description: "Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelImg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.",
+                content: " Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelImg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.2 --src_dir: the directory where labelImg is stored after labeling. --out_dir: the location where the data is stored after conversion. --val_ratio: the ratio of the generated validation set to the whole data, default is 0.2. --have_test: whether to generate the test part of the data, the default is False. If this parameter appears, it is True. --test_ratio: percentage of the whole data of the test data, default is 0.2. Converted directory structure (see dataset/labelImg_dataset_output for details):\nlabelImg_dataset_output/ ├── classes.txt ├── images │ ├── images(13).jpg │ ├── images(3).jpg │ ├── images4.jpg │ ├── images5.jpg │ └── images7.jpg ├── labels │ ├── images(13).txt │ ├── images(3).txt │ ├── images4.txt │ ├── images5.txt │ └── images7.txt ├── non_labels # This is the catalog without the labeled images. │ └── images6.jpg ├── test.txt ├── train.txt └── val.txt You can further directly convert the dataset/labelImg_dataset_output directory to COCO\nyolov5_to_coco --data_dir dataset/labellImg_dataset_output "
             }
         );
     index.add(

docs/overview/index.html

@@ -778,8 +778,8 @@ <h3 id="contributing">Contributing <a href="#contributing" class="anchor" aria-h
                 id:  1 ,
                 href: "\/LabelConvert\/docs\/supportconversions\/labelimg_to_yolov5\/",
                 title: "labelImg → YOLOV5",
-                description: "Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelimg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.",
-                content: " Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelimg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.2 --src_dir: the directory where labelImg is stored after labeling. --out_dir: the location where the data is stored after conversion. --val_ratio: the ratio of the generated validation set to the whole data, default is 0.2. --have_test: whether to generate the test part of the data, the default is False. If this parameter appears, it is True. --test_ratio: percentage of the whole data of the test data, default is 0.2. Converted directory structure (see dataset/labelImg_dataset_output for details):\nlabelImg_dataset_output/ ├── classes.txt ├── images │ ├── images(13).jpg │ ├── images(3).jpg │ ├── images4.jpg │ ├── images5.jpg │ └── images7.jpg ├── labels │ ├── images(13).txt │ ├── images(3).txt │ ├── images4.txt │ ├── images5.txt │ └── images7.txt ├── non_labels # This is the catalog without the labeled images. │ └── images6.jpg ├── test.txt ├── train.txt └── val.txt You can further directly convert the dataset/labelImg_dataset_output directory to COCO\nyolov5_to_coco --data_dir dataset/labellImg_dataset_output "
+                description: "Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelImg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.",
+                content: " Convert the yolo data format marked by the labelImg library to YOLOV5 format data with one click.\nThe labelImg label data directory structure is as follows (see dataset/labelImg_dataset for details):\nlabelImg_dataset ├── classes.txt ├── images(13).jpg ├── images(13).txt ├── images(3).jpg ├── images(3).txt ├── images4.jpg ├── images4.txt ├── images5.jpg ├── images5.txt ├── images6.jpg ├── images7.jpg └── images7.txt Convert\nlabelImg_to_yolov5 --src_dir dataset/labelImg_dataset \\ --out_dir dataset/labelImg_dataset_output \\ --val_ratio 0.2 \\ --have_test \\ --test_ratio 0.2 --src_dir: the directory where labelImg is stored after labeling. --out_dir: the location where the data is stored after conversion. --val_ratio: the ratio of the generated validation set to the whole data, default is 0.2. --have_test: whether to generate the test part of the data, the default is False. If this parameter appears, it is True. --test_ratio: percentage of the whole data of the test data, default is 0.2. Converted directory structure (see dataset/labelImg_dataset_output for details):\nlabelImg_dataset_output/ ├── classes.txt ├── images │ ├── images(13).jpg │ ├── images(3).jpg │ ├── images4.jpg │ ├── images5.jpg │ └── images7.jpg ├── labels │ ├── images(13).txt │ ├── images(3).txt │ ├── images4.txt │ ├── images5.txt │ └── images7.txt ├── non_labels # This is the catalog without the labeled images. │ └── images6.jpg ├── test.txt ├── train.txt └── val.txt You can further directly convert the dataset/labelImg_dataset_output directory to COCO\nyolov5_to_coco --data_dir dataset/labellImg_dataset_output "
             }
         );
     index.add(