125 lines
5.5 KiB
Markdown
125 lines
5.5 KiB
Markdown
# Visualization
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<!-- TOC -->
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- [Visualization](#visualization)
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- [Pipeline Visualization](#pipeline-visualization)
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- [Usage](#usage)
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- [FAQs](#faqs)
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<!-- TOC -->
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## pipeline visualization
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### Usage
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```bash
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python tools/visualizations/vis_pipeline.py \
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${CONFIG_FILE} \
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--output-dir ${OUTPUT_DIR} \
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--phase ${DATASET_PHASE} \
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--number ${BUNBER_IMAGES_DISPLAY} \
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--skip-type ${SKIP_TRANSFORM_TYPE}
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--mode ${DISPLAY_MODE} \
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--show \
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--adaptive \
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--min-edge-length ${MIN_EDGE_LENGTH} \
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--max-edge-length ${MAX_EDGE_LENGTH} \
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--bgr2rgb \
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--window-size ${WINDOW_SIZE}
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```
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**Description of all arguments**：
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- `config` : The path of a model config file.
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- `--output-dir`: The output path for visualized images. If not specified, it will be set to `''`, which means not to save.
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- `--phase`: Phase of visualizing dataset，must be one of `[train, val, test]`. If not specified, it will be set to `train`.
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- `--number`: The number of samples to visualize. If not specified, display all images in the dataset.
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- `--skip-type`: The pipelines to be skipped. If not specified, it will be set to `['ToTensor', 'Normalize', 'ImageToTensor', 'Collect']`.
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- `--mode`: The display mode, can be one of `[original, pipeline, concat]`. If not specified, it will be set to `concat`.
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- `--show`: If set, display pictures in pop-up windows.
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- `--adaptive`: If set, automatically adjust the size of the visualization images.
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- `--min-edge-length`: The minimum edge length, used when `--adaptive` is set. When any side of the picture is smaller than `${MIN_EDGE_LENGTH}`, the picture will be enlarged while keeping the aspect ratio unchanged, and the short side will be aligned to `${MIN_EDGE_LENGTH}`. If not specified, it will be set to 200.
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- `--max-edge-length`: The maximum edge length, used when `--adaptive` is set. When any side of the picture is larger than `${MAX_EDGE_LENGTH}`, the picture will be reduced while keeping the aspect ratio unchanged, and the long side will be aligned to `${MAX_EDGE_LENGTH}`. If not specified, it will be set to 1000.
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- `--bgr2rgb`: If set, flip the color channel order of images.
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- `--window-size`: The shape of the display window. If not specified, it will be set to `12*7`. If used, it must be in the format `'W*H'`.
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```{note}
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1. If the `--mode` is not specified, it will be set to `concat` as default, get the pictures stitched together by original pictures and transformed pictures; if the `--mode` is set to `original`, get the original pictures; if the `--mode` is set to `pipeline`, get the transformed pictures.
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2. When `--adaptive` option is set, images that are too large or too small will be automatically adjusted, you can use `--min-edge-length` and `--max-edge-length` to set the adjust size.
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```
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**Examples**：
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1. Visualize all the transformed pictures of the `ImageNet` training set and display them in pop-up windows：
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```shell
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python ./tools/visualizations/vis_pipeline.py ./configs/resnet/resnet50_b32x8_imagenet.py --show --mode pipeline
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```
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<div align=center><img src="../_static/image/pipeline.JPEG" style=" width: auto; height: 40%; "></div>
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2. Visualize 10 comparison pictures in the `ImageNet` train set and save them in the `./tmp` folder：
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```shell
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python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --output-dir tmp --number 10 --adaptive
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```
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<div align=center><img src="../_static/image/concat.JPEG" style=" width: auto; height: 40%; "></div>
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3. Visualize 100 original pictures in the `CIFAR100` validation set, then display and save them in the `./tmp` folder：
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```shell
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python ./tools/visualizations/vis_pipeline.py configs/resnet/resnet50_b16x8_cifar100.py --phase val --output-dir tmp --mode original --number 100 --show --adaptive --bgr2rgb
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```
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<div align=center><img src="../_static/image/original.JPEG" style=" width: auto; height: 40%; "></div>
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## lr schedule visualization
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### Usage
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```bash
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python tools/visualizations/vis_lr.py \
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${CONFIG_FILE} \
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--dataset-size ${DATASET_SIZE} \
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--ngpus ${NUM_GPUs}
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--save-path ${SAVE_PATH} \
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--title ${TITLE} \
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--style ${STYLE} \
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--window-size ${WINDOW_SIZE}
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--cfg-options
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```
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**Description of all arguments**：
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- `config` : The path of a model config file.
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- `dataset-size` : The size of the datasets. If set，`build_dataset` will be skipped and `${DATASET_SIZE}` will be used as the size. Default to use the function `build_dataset`.
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- `ngpus` : The number of GPUs used in training, default to be 1.
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- `save-path` : The learning rate curve plot save path, default not to save.
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- `title` : Title of figure. If not set, default to be config file name.
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- `style` : Style of plt. If not set, default to be `whitegrid`.
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- `window-size`: The shape of the display window. If not specified, it will be set to `12*7`. If used, it must be in the format `'W*H'`.
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- `cfg-options` : Modifications to the configuration file, refer to [Tutorial 1: Learn about Configs](https://mmclassification.readthedocs.io/en/latest/tutorials/config.html).
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```{note}
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Loading annotations maybe consume much time, you can directly specify the size of the dataset with `dataset-size` to save time.
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```
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**Examples**：
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```bash
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python tools/visualizations/vis_lr.py configs/resnet/resnet50_b16x8_cifar100.py
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```
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When using ImageNet, directly specify the size of ImageNet, as below:
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```bash
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python tools/visualizations/vis_lr.py configs/repvgg/repvgg-B3g4_4xb64-autoaug-lbs-mixup-coslr-200e_in1k.py --dataset-size 1281167 --ngpus 4 --save-path ./repvgg-B3g4_4xb64-lr.jpg
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```
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## FAQs
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- None
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