diff --git a/docs/en/_static/image/tools/visualization/pipeline-concat.jpg b/docs/en/_static/image/tools/visualization/pipeline-concat.jpg deleted file mode 100644 index e5e69974..00000000 Binary files a/docs/en/_static/image/tools/visualization/pipeline-concat.jpg and /dev/null differ diff --git a/docs/en/_static/image/tools/visualization/pipeline-original.jpg b/docs/en/_static/image/tools/visualization/pipeline-original.jpg deleted file mode 100644 index fa23a029..00000000 Binary files a/docs/en/_static/image/tools/visualization/pipeline-original.jpg and /dev/null differ diff --git a/docs/en/_static/image/tools/visualization/pipeline-pipeline.jpg b/docs/en/_static/image/tools/visualization/pipeline-pipeline.jpg deleted file mode 100644 index aa7df13b..00000000 Binary files a/docs/en/_static/image/tools/visualization/pipeline-pipeline.jpg and /dev/null differ diff --git a/docs/en/tools/miscellaneous.md b/docs/en/tools/miscellaneous.md index 0463b525..4e66d91a 100644 --- a/docs/en/tools/miscellaneous.md +++ b/docs/en/tools/miscellaneous.md @@ -1,4 +1,4 @@ -# MISCELLANEOUS +# Miscellaneous diff --git a/docs/en/tools/visualization.md b/docs/en/tools/visualization.md index a519b972..f224fe68 100644 --- a/docs/en/tools/visualization.md +++ b/docs/en/tools/visualization.md @@ -2,11 +2,10 @@ -- [Visualization](#visualization) - - [Pipeline Visualization](#pipeline-visualization) - - [Learning Rate Schedule Visualization](#learning-rate-schedule-visualization) - - [Class Activation Map Visualization](#class-activation-map-visualization) - - [FAQs](#faqs) +- [Pipeline Visualization](#pipeline-visualization) +- [Learning Rate Schedule Visualization](#learning-rate-schedule-visualization) +- [Class Activation Map Visualization](#class-activation-map-visualization) +- [FAQs](#faqs) ## Pipeline Visualization @@ -14,17 +13,18 @@ ```bash python tools/visualizations/vis_pipeline.py \ ${CONFIG_FILE} \ - --output-dir ${OUTPUT_DIR} \ - --phase ${DATASET_PHASE} \ - --number ${BUNBER_IMAGES_DISPLAY} \ - --skip-type ${SKIP_TRANSFORM_TYPE} - --mode ${DISPLAY_MODE} \ - --show \ - --adaptive \ - --min-edge-length ${MIN_EDGE_LENGTH} \ - --max-edge-length ${MAX_EDGE_LENGTH} \ - --bgr2rgb \ - --window-size ${WINDOW_SIZE} + [--output-dir ${OUTPUT_DIR}] \ + [--phase ${DATASET_PHASE}] \ + [--number ${BUNBER_IMAGES_DISPLAY}] \ + [--skip-type ${SKIP_TRANSFORM_TYPE}] \ + [--mode ${DISPLAY_MODE}] \ + [--show] \ + [--adaptive] \ + [--min-edge-length ${MIN_EDGE_LENGTH}] \ + [--max-edge-length ${MAX_EDGE_LENGTH}] \ + [--bgr2rgb] \ + [--window-size ${WINDOW_SIZE}] \ + [--cfg-options ${CFG_OPTIONS}] ``` **Description of all arguments**： @@ -32,48 +32,57 @@ python tools/visualizations/vis_pipeline.py \ - `config` : The path of a model config file. - `--output-dir`: The output path for visualized images. If not specified, it will be set to `''`, which means not to save. - `--phase`: Phase of visualizing dataset，must be one of `[train, val, test]`. If not specified, it will be set to `train`. -- `--number`: The number of samples to visualize. If not specified, display all images in the dataset. +- `--number`: The number of samples to visualized. If not specified, display all images in the dataset. - `--skip-type`: The pipelines to be skipped. If not specified, it will be set to `['ToTensor', 'Normalize', 'ImageToTensor', 'Collect']`. - `--mode`: The display mode, can be one of `[original, pipeline, concat]`. If not specified, it will be set to `concat`. - `--show`: If set, display pictures in pop-up windows. -- `--adaptive`: If set, automatically adjust the size of the visualization images. +- `--adaptive`: If set, adaptively resize images for better visualization. - `--min-edge-length`: The minimum edge length, used when `--adaptive` is set. When any side of the picture is smaller than `${MIN_EDGE_LENGTH}`, the picture will be enlarged while keeping the aspect ratio unchanged, and the short side will be aligned to `${MIN_EDGE_LENGTH}`. If not specified, it will be set to 200. - `--max-edge-length`: The maximum edge length, used when `--adaptive` is set. When any side of the picture is larger than `${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. - `--bgr2rgb`: If set, flip the color channel order of images. - `--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'`. +- `--cfg-options` : Modifications to the configuration file, refer to [Tutorial 1: Learn about Configs](https://mmclassification.readthedocs.io/en/latest/tutorials/config.html). ```{note} -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. +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 `transformed`, get the transformed pictures; if the `--mode` is set to `pipeline`, get all the intermediate images through the pipeline. 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. ``` **Examples**： -1. Visualize all the transformed pictures of the `ImageNet` training set and display them in pop-up windows： +1. In **'original'** mode, visualize 100 original pictures in the `CIFAR100` validation set, then display and save them in the `./tmp` folder： - ```shell - python ./tools/visualizations/vis_pipeline.py ./configs/resnet/resnet50_8xb32_in1k.py --show --mode pipeline - ``` + ```shell + python ./tools/visualizations/vis_pipeline.py configs/resnet/resnet50_8xb16_cifar100.py --phase val --output-dir tmp --mode original --number 100 --show --adaptive --bgr2rgb + ``` -
+
-2. Visualize 10 comparison pictures in the `ImageNet` train set and save them in the `./tmp` folder： +2. In **'transformed'** mode, visualize all the transformed pictures of the `ImageNet` training set and display them in pop-up windows： - ```shell - python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --output-dir tmp --number 10 --adaptive - ``` + ```shell + python ./tools/visualizations/vis_pipeline.py ./configs/resnet/resnet50_8xb32_in1k.py --show --mode transformed + ``` -
+
-3. Visualize 100 original pictures in the `CIFAR100` validation set, then display and save them in the `./tmp` folder： +3. In **'concat'** mode, visualize 10 pairs of origin and transformed images for comparison in the `ImageNet` train set and save them in the `./tmp` folder： - ```shell - python ./tools/visualizations/vis_pipeline.py configs/resnet/resnet50_8xb16_cifar100.py --phase val --output-dir tmp --mode original --number 100 --show --adaptive --bgr2rgb - ``` + ```shell + python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --output-dir tmp --number 10 --adaptive + ``` -
+
+ +4. In **'pipeline'** mode, visualize all the intermediate pictures in the `ImageNet` train set through the pipeline： + + ```shell + python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --adaptive --mode pipeline --show + ``` + +
## Learning Rate Schedule Visualization diff --git a/docs/zh_CN/_static/image/tools/visualization/pipeline-concat.jpg b/docs/zh_CN/_static/image/tools/visualization/pipeline-concat.jpg deleted file mode 100644 index e5e69974..00000000 Binary files a/docs/zh_CN/_static/image/tools/visualization/pipeline-concat.jpg and /dev/null differ diff --git a/docs/zh_CN/_static/image/tools/visualization/pipeline-original.jpg b/docs/zh_CN/_static/image/tools/visualization/pipeline-original.jpg deleted file mode 100644 index fa23a029..00000000 Binary files a/docs/zh_CN/_static/image/tools/visualization/pipeline-original.jpg and /dev/null differ diff --git a/docs/zh_CN/_static/image/tools/visualization/pipeline-pipeline.jpg b/docs/zh_CN/_static/image/tools/visualization/pipeline-pipeline.jpg deleted file mode 100644 index aa7df13b..00000000 Binary files a/docs/zh_CN/_static/image/tools/visualization/pipeline-pipeline.jpg and /dev/null differ diff --git a/docs/zh_CN/tools/visualization.md b/docs/zh_CN/tools/visualization.md index b236da6b..9caaf24a 100644 --- a/docs/zh_CN/tools/visualization.md +++ b/docs/zh_CN/tools/visualization.md @@ -2,11 +2,10 @@ -- [可视化](#可视化) - - [数据流水线可视化](#数据流水线可视化) - - [学习率策略可视化](#学习率策略可视化) - - [类别激活图可视化](#类别激活图可视化) - - [常见问题](#常见问题) +- [数据流水线可视化](#数据流水线可视化) +- [学习率策略可视化](#学习率策略可视化) +- [类别激活图可视化](#类别激活图可视化) +- [常见问题](#常见问题) @@ -15,17 +14,18 @@ ```bash python tools/visualizations/vis_pipeline.py \ ${CONFIG_FILE} \ - --output-dir ${OUTPUT_DIR} \ - --phase ${DATASET_PHASE} \ - --number ${BUNBER_IMAGES_DISPLAY} \ - --skip-type ${SKIP_TRANSFORM_TYPE} \ - --mode ${DISPLAY_MODE} \ - --show \ - --adaptive \ - --min-edge-length ${MIN_EDGE_LENGTH} \ - --max-edge-length ${MAX_EDGE_LENGTH} \ - --bgr2rgb \ - --window-size ${WINDOW_SIZE} + [--output-dir ${OUTPUT_DIR}] \ + [--phase ${DATASET_PHASE}] \ + [--number ${BUNBER_IMAGES_DISPLAY}] \ + [--skip-type ${SKIP_TRANSFORM_TYPE}] \ + [--mode ${DISPLAY_MODE}] \ + [--show] \ + [--adaptive] \ + [--min-edge-length ${MIN_EDGE_LENGTH}] \ + [--max-edge-length ${MAX_EDGE_LENGTH}] \ + [--bgr2rgb] \ + [--window-size ${WINDOW_SIZE}] \ + [--cfg-options ${CFG_OPTIONS}] ``` **所有参数的说明**： @@ -35,71 +35,80 @@ python tools/visualizations/vis_pipeline.py \ - `--phase`: 可视化数据集的阶段，只能为 `[train, val, test]` 之一，默认为 `train`。 - `--number`: 可视化样本数量。如果没有指定，默认展示数据集的所有图片。 - `--skip-type`: 预设跳过的数据流水线过程。如果没有指定，默认为 `['ToTensor', 'Normalize', 'ImageToTensor', 'Collect']`。 -- `--mode`: 可视化的模式，只能为 `[original, pipeline, concat]` 之一，如果没有指定，默认为 `concat`。 +- `--mode`: 可视化的模式，只能为 `[original, transformed, concat, pipeline]` 之一，如果没有指定，默认为 `concat`。 - `--show`: 将可视化图片以弹窗形式展示。 - `--adaptive`: 自动调节可视化图片的大小。 - `--min-edge-length`: 最短边长度，当使用了 `--adaptive` 时有效。 当图片任意边小于 `${MIN_EDGE_LENGTH}` 时，会保持长宽比不变放大图片，短边对齐至 `${MIN_EDGE_LENGTH}`，默认为200。 - `--max-edge-length`: 最长边长度，当使用了 `--adaptive` 时有效。 当图片任意边大于 `${MAX_EDGE_LENGTH}` 时，会保持长宽比不变缩小图片，短边对齐至 `${MAX_EDGE_LENGTH}`，默认为1000。 - `--bgr2rgb`: 将图片的颜色通道翻转。 - `--window-size`: 可视化窗口大小，如果没有指定，默认为 `12*7`。如果需要指定，按照格式 `'W*H'`。 +- `--cfg-options` : 对配置文件的修改，参考[教程 1：如何编写配置文件](https://mmclassification.readthedocs.io/zh_CN/latest/tutorials/config.html)。 ```{note} -1. 如果不指定 `--mode`，默认设置为 `concat`，获取原始图片和预处理后图片拼接的图片；如果 `--mode` 设置为 `original`，则获取原始图片； 如果 `--mode` 设置为 `pipeline`，则获取预处理后的图片。 +1. 如果不指定 `--mode`，默认设置为 `concat`，获取原始图片和预处理后图片拼接的图片；如果 `--mode` 设置为 `original`，则获取原始图片；如果 `--mode` 设置为 `transformed`，则获取预处理后的图片；如果 `--mode` 设置为 `pipeline`，则获得数据流水线所有中间过程图片。 2. 当指定了 `--adaptive` 选项时，会自动的调整尺寸过大和过小的图片，你可以通过设定 `--min-edge-length` 与 `--max-edge-length` 来指定自动调整的图片尺寸。 ``` **示例**： -1. 可视化 `ImageNet` 训练集的所有经过预处理的图片，并以弹窗形式显示： +1. **'original'** 模式，可视化 `CIFAR100` 验证集中的100张原始图片，显示并保存在 `./tmp` 文件夹下： - ```shell - python ./tools/visualizations/vis_pipeline.py ./configs/resnet/resnet50_8xb32_in1k.py --show --mode pipeline - ``` + ```shell + python ./tools/visualizations/vis_pipeline.py configs/resnet/resnet50_8xb16_cifar100.py --phase val --output-dir tmp --mode original --number 100 --show --adaptive --bgr2rgb + ``` -
+
-2. 可视化 `ImageNet` 训练集的10张原始图片与预处理后图片对比图，保存在 `./tmp` 文件夹下： +2. **'transformed'** 模式，可视化 `ImageNet` 训练集的所有经过预处理的图片，并以弹窗形式显示： - ```shell - python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --output-dir tmp --number 10 --adaptive - ``` + ```shell + python ./tools/visualizations/vis_pipeline.py ./configs/resnet/resnet50_8xb32_in1k.py --show --mode transformed + ``` -
+
-3. 可视化 `CIFAR100` 验证集中的100张原始图片，显示并保存在 `./tmp` 文件夹下： +3. **'concat'** 模式，可视化 `ImageNet` 训练集的10张原始图片与预处理后图片对比图，保存在 `./tmp` 文件夹下： - ```shell - python ./tools/visualizations/vis_pipeline.py configs/resnet/resnet50_8xb16_cifar100.py --phase val --output-dir tmp --mode original --number 100 --show --adaptive --bgr2rgb - ``` + ```shell + python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --output-dir tmp --number 10 --adaptive + ``` -
+
+ +4. **'pipeline'** 模式，可视化 `ImageNet` 训练集经过数据流水线的过程图像： + + ```shell + python ./tools/visualizations/vis_pipeline.py configs/swin_transformer/swin_base_224_b16x64_300e_imagenet.py --phase train --adaptive --mode pipeline --show + ``` + +
## 学习率策略可视化 ```bash python tools/visualizations/vis_lr.py \ ${CONFIG_FILE} \ - --dataset-size ${Dataset_Size} \ - --ngpus ${NUM_GPUs} - --save-path ${SAVE_PATH} \ - --title ${TITLE} \ - --style ${STYLE} \ - --window-size ${WINDOW_SIZE} - --cfg-options + [--dataset-size ${Dataset_Size}] \ + [--ngpus ${NUM_GPUs}] \ + [--save-path ${SAVE_PATH}] \ + [--title ${TITLE}] \ + [--style ${STYLE}] \ + [--window-size ${WINDOW_SIZE}] \ + [--cfg-options ${CFG_OPTIONS}] \ ``` **所有参数的说明**： - `config` : 模型配置文件的路径。 -- `dataset-size` : 数据集的大小。如果指定，`build_dataset` 将被跳过并使用这个大小作为数据集大小，默认使用 `build_dataset` 所得数据集的大小。 -- `ngpus` : 使用 GPU 的数量。 -- `save-path` : 保存的可视化图片的路径，默认不保存。 -- `title` : 可视化图片的标题，默认为配置文件名。 -- `style` : 可视化图片的风格，默认为 `whitegrid`。 -- `window-size`: 可视化窗口大小，如果没有指定，默认为 `12*7`。如果需要指定，按照格式 `'W*H'`。 -- `cfg-options` : 对配置文件的修改，参考[教程 1：如何编写配置文件](https://mmclassification.readthedocs.io/zh_CN/latest/tutorials/config.html)。 +- `--dataset-size` : 数据集的大小。如果指定，`build_dataset` 将被跳过并使用这个大小作为数据集大小，默认使用 `build_dataset` 所得数据集的大小。 +- `--ngpus` : 使用 GPU 的数量。 +- `--save-path` : 保存的可视化图片的路径，默认不保存。 +- `--title` : 可视化图片的标题，默认为配置文件名。 +- `--style` : 可视化图片的风格，默认为 `whitegrid`。 +- `--window-size`: 可视化窗口大小，如果没有指定，默认为 `12*7`。如果需要指定，按照格式 `'W*H'`。 +- `--cfg-options` : 对配置文件的修改，参考[教程 1：如何编写配置文件](https://mmclassification.readthedocs.io/zh_CN/latest/tutorials/config.html)。 ```{note} diff --git a/tools/visualizations/vis_pipeline.py b/tools/visualizations/vis_pipeline.py index ed64802f..ffb9b183 100644 --- a/tools/visualizations/vis_pipeline.py +++ b/tools/visualizations/vis_pipeline.py @@ -1,18 +1,27 @@ # Copyright (c) OpenMMLab. All rights reserved. import argparse +import copy import itertools import os import re import sys +import warnings from pathlib import Path +from typing import List +import cv2 import mmcv import numpy as np from mmcv import Config, DictAction, ProgressBar from mmcls.core import visualization as vis -from mmcls.datasets.builder import build_dataset -from mmcls.datasets.pipelines import Compose +from mmcls.datasets.builder import PIPELINES, build_dataset, build_from_cfg +from mmcls.models.utils import to_2tuple + +# text style +bright_style, reset_style = '\x1b[1m', '\x1b[0m' +red_text, blue_text = '\x1b[31m', '\x1b[34m' +white_background = '\x1b[107m' def parse_args(): @@ -48,11 +57,12 @@ def parse_args(): '--mode', default='concat', type=str, - choices=['original', 'pipeline', 'concat'], + choices=['original', 'transformed', 'concat', 'pipeline'], help='display mode; display original pictures or transformed pictures' - ' or comparison pictures. "original" means show images load from disk;' - ' "pipeline" means to show images after pipeline; "concat" means show ' - 'images stitched by "original" and "pipeline" images. Default concat.') + ' or comparison pictures. "original" means show images load from disk' + '; "transformed" means to show images after transformed; "concat" ' + 'means show images stitched by "original" and "output" images. ' + '"pipeline" means show all the intermediate images. Default concat.') parser.add_argument( '--show', default=False, @@ -71,7 +81,7 @@ def parse_args(): '"--adaptive" is true. Default 200.') parser.add_argument( '--max-edge-length', - default=1000, + default=800, type=int, help='the max edge length when visualizing images, used when ' '"--adaptive" is true. Default 1000.') @@ -130,7 +140,7 @@ def retrieve_data_cfg(config_path, skip_type, cfg_options, phase): return cfg -def build_dataset_pipeline(cfg, phase): +def build_dataset_pipelines(cfg, phase): """build dataset and pipeline from config. Separate the pipeline except 'LoadImageFromFile' step if @@ -144,43 +154,103 @@ def build_dataset_pipeline(cfg, phase): origin_pipeline = data_cfg.pipeline data_cfg.pipeline = loadimage_pipeline dataset = build_dataset(data_cfg) - pipeline = Compose(origin_pipeline) + pipelines = { + pipeline_cfg['type']: build_from_cfg(pipeline_cfg, PIPELINES) + for pipeline_cfg in origin_pipeline + } - return dataset, pipeline + return dataset, pipelines -def put_img(board, img, center): - """put a image into a big board image with the anchor center.""" - center_x, center_y = center - img_h, img_w, _ = img.shape - xmin, ymin = int(center_x - img_w // 2), int(center_y - img_h // 2) - board[ymin:ymin + img_h, xmin:xmin + img_w, :] = img +def prepare_imgs(args, imgs: List[np.ndarray], steps=None): + """prepare the showing picture.""" + ori_shapes = [img.shape for img in imgs] + # adaptive adjustment to rescale pictures + if args.adaptive: + for i, img in enumerate(imgs): + imgs[i] = adaptive_size(img, args.min_edge_length, + args.max_edge_length) + else: + # if src image is too large or too small, + # warning a "--adaptive" message. + for ori_h, ori_w, _ in ori_shapes: + if (args.min_edge_length > ori_h or args.min_edge_length > ori_w + or args.max_edge_length < ori_h + or args.max_edge_length < ori_w): + msg = red_text + msg += 'The visualization picture is too small or too large to' + msg += ' put text information on it, please add ' + msg += bright_style + red_text + white_background + msg += '"--adaptive"' + msg += reset_style + red_text + msg += ' to adaptively rescale the showing pictures' + msg += reset_style + warnings.warn(msg) + + if len(imgs) == 1: + return imgs[0] + else: + return concat_imgs(imgs, steps, ori_shapes) + + +def concat_imgs(imgs, steps, ori_shapes): + """Concat list of pictures into a single big picture, align height here.""" + show_shapes = [img.shape for img in imgs] + show_heights = [shape[0] for shape in show_shapes] + show_widths = [shape[1] for shape in show_shapes] + + max_height = max(show_heights) + text_height = 20 + font_size = 0.5 + pic_horizontal_gap = min(show_widths) // 10 + for i, img in enumerate(imgs): + cur_height = show_heights[i] + pad_height = max_height - cur_height + pad_top, pad_bottom = to_2tuple(pad_height // 2) + # handle instance that the pad_height is an odd number + if pad_height % 2 == 1: + pad_top = pad_top + 1 + pad_bottom += text_height * 3 # keep pxs to put step information text + pad_left, pad_right = to_2tuple(pic_horizontal_gap) + # make border + img = cv2.copyMakeBorder( + img, + pad_top, + pad_bottom, + pad_left, + pad_right, + cv2.BORDER_CONSTANT, + value=(255, 255, 255)) + # put transform phase information in the bottom + imgs[i] = cv2.putText( + img=img, + text=steps[i], + org=(pic_horizontal_gap, max_height + text_height // 2), + fontFace=cv2.FONT_HERSHEY_TRIPLEX, + fontScale=font_size, + color=(255, 0, 0), + lineType=1) + # put image size information in the bottom + imgs[i] = cv2.putText( + img=img, + text=str(ori_shapes[i]), + org=(pic_horizontal_gap, max_height + int(text_height * 1.5)), + fontFace=cv2.FONT_HERSHEY_TRIPLEX, + fontScale=font_size, + color=(255, 0, 0), + lineType=1) + + # Height alignment for concatenating + board = np.concatenate(imgs, axis=1) return board -def concat(left_img, right_img): - """Concat two pictures into a single big picture, accepts two images with - diffenert shapes.""" - GAP = 10 - left_h, left_w, _ = left_img.shape - right_h, right_w, _ = right_img.shape - # create a big board to contain images with shape (board_h, board_w*2+10) - board_h, board_w = max(left_h, right_h), max(left_w, right_w) - board = np.ones([board_h, 2 * board_w + GAP, 3], np.uint8) * 255 - - put_img(board, left_img, (int(board_w // 2), int(board_h // 2))) - put_img(board, right_img, - (int(board_w // 2) + board_w + GAP // 2, int(board_h // 2))) - return board - - -def adaptive_size(mode, image, min_edge_length, max_edge_length): - """rescale image if image is too small to put text like cifra.""" +def adaptive_size(image, min_edge_length, max_edge_length, src_shape=None): + """rescale image if image is too small to put text like cifar.""" assert min_edge_length >= 0 and max_edge_length >= 0 assert max_edge_length >= min_edge_length - - image_h, image_w, *_ = image.shape - image_w = image_w // 2 if mode == 'concat' else image_w + src_shape = image.shape if src_shape is None else src_shape + image_h, image_w, _ = src_shape if image_h < min_edge_length or image_w < min_edge_length: image = mmcv.imrescale( @@ -191,49 +261,58 @@ def adaptive_size(mode, image, min_edge_length, max_edge_length): return image -def get_display_img(item, pipeline, mode, bgr2rgb): +def get_display_img(args, item, pipelines): """get image to display.""" - if bgr2rgb: + # srcs picture could be in RGB or BGR order due to different backends. + if args.bgr2rgb: item['img'] = mmcv.bgr2rgb(item['img']) src_image = item['img'].copy() - # get transformed picture - if mode in ['pipeline', 'concat']: - item = pipeline(item) - trans_image = item['img'] - trans_image = np.ascontiguousarray(trans_image, dtype=np.uint8) + pipeline_images = [src_image] + + # get intermediate images through pipelines + if args.mode in ['transformed', 'concat', 'pipeline']: + for pipeline in pipelines.values(): + item = pipeline(item) + trans_image = copy.deepcopy(item['img']) + trans_image = np.ascontiguousarray(trans_image, dtype=np.uint8) + pipeline_images.append(trans_image) + + # concatenate images to be showed according to mode + if args.mode == 'original': + image = prepare_imgs(args, [src_image], ['src']) + elif args.mode == 'transformed': + image = prepare_imgs(args, [pipeline_images[-1]], ['transformed']) + elif args.mode == 'concat': + steps = ['src', 'transformed'] + image = prepare_imgs(args, [pipeline_images[0], pipeline_images[-1]], + steps) + elif args.mode == 'pipeline': + steps = ['src'] + list(pipelines.keys()) + image = prepare_imgs(args, pipeline_images, steps) - if mode == 'concat': - image = concat(src_image, trans_image) - elif mode == 'original': - image = src_image - elif mode == 'pipeline': - image = trans_image return image def main(): args = parse_args() wind_w, wind_h = args.window_size.split('*') - wind_w, wind_h = int(wind_w), int(wind_h) + wind_w, wind_h = int(wind_w), int(wind_h) # showing windows size cfg = retrieve_data_cfg(args.config, args.skip_type, args.cfg_options, args.phase) - dataset, pipeline = build_dataset_pipeline(cfg, args.phase) + dataset, pipelines = build_dataset_pipelines(cfg, args.phase) CLASSES = dataset.CLASSES display_number = min(args.number, len(dataset)) progressBar = ProgressBar(display_number) with vis.ImshowInfosContextManager(fig_size=(wind_w, wind_h)) as manager: for i, item in enumerate(itertools.islice(dataset, display_number)): - image = get_display_img(item, pipeline, args.mode, args.bgr2rgb) - if args.adaptive: - image = adaptive_size(args.mode, image, args.min_edge_length, - args.max_edge_length) + image = get_display_img(args, item, pipelines) - # dist_path is None as default, means not save pictures + # dist_path is None as default, means not saving pictures dist_path = None if args.output_dir: - # some datasets do not have filename, such as cifar, use id + # some datasets don't have filenames, such as cifar src_path = item.get('filename', '{}.jpg'.format(i)) dist_path = os.path.join(args.output_dir, Path(src_path).name)