From 81c830d8b908377950e1fb746f09151f4150445a Mon Sep 17 00:00:00 2001 From: SunAhong1993 <48579383+SunAhong1993@users.noreply.github.com> Date: Wed, 3 Jul 2019 19:03:45 +0800 Subject: [PATCH] Update DATA.md (#2704) --- PaddleCV/PaddleDetection/docs/DATA.md | 28 +++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/PaddleCV/PaddleDetection/docs/DATA.md b/PaddleCV/PaddleDetection/docs/DATA.md index 73f821f3..c55562ee 100644 --- a/PaddleCV/PaddleDetection/docs/DATA.md +++ b/PaddleCV/PaddleDetection/docs/DATA.md @@ -10,16 +10,16 @@ im_info, im_id, gt_bbox, gt_class, is_crowd), (...)]`. The data pipeline consists of four sub-systems: data parsing, image pre-processing, data conversion and data feeding APIs. -Data samples are collected to form `dataset.Dataset`s, usually 3 sets are +Data samples are collected to form `data.Dataset`s, usually 3 sets are needed for training, validation, and testing respectively. -First, `dataset.source` loads the data files into memory, then -`dataset.transform` processes them, and lastly, the batched samples -are fetched by `dataset.Reader`. +First, `data.source` loads the data files into memory, then +`data.transform` processes them, and lastly, the batched samples +are fetched by `data.Reader`. Sub-systems details: 1. Data parsing -Parses various data sources and creates `dataset.Dataset` instances. Currently, +Parses various data sources and creates `data.Dataset` instances. Currently, following data sources are supported: - COCO data source @@ -104,19 +104,19 @@ python ./tools/generate_data_for_training.py ``` 2. Image preprocessing -the `dataset.transform.operator` module provides operations such as image +the `data.transform.operator` module provides operations such as image decoding, expanding, cropping, etc. Multiple operators are combined to form larger processing pipelines. 3. Data transformer -Transform a `dataset.Dataset` to achieve various desired effects, Notably: the -`dataset.transform.paralle_map` transformer accelerates image processing with +Transform a `data.Dataset` to achieve various desired effects, Notably: the +`data.transform.paralle_map` transformer accelerates image processing with multi-threads or multi-processes. More transformers can be found in -`dataset.transform.transformer`. +`data.transform.transformer`. 4. Data feeding apis -To facilitate data pipeline building, we combine multiple `dataset.Dataset` to -form a `dataset.Reader` which can provide data for training, validation and +To facilitate data pipeline building, we combine multiple `data.Dataset` to +form a `data.Reader` which can provide data for training, validation and testing respectively. Users can simply call `Reader.[train|eval|infer]` to get the corresponding data stream. Many aspect of the `Reader`, such as storage location, preprocessing pipeline, acceleration mode can be configured with yaml @@ -126,13 +126,13 @@ The main APIs are as follows: 1. Data parsing - - `source/coco_loader.py`: COCO dataset parser. [source](https://github.com/PaddlePaddle/models/blob/develop/PaddleCV/object_detection/ppdet/data/source/coco_loader.py) - - `source/voc_loader.py`: Pascal VOC dataset parser. [source](https://github.com/PaddlePaddle/models/blob/develop/PaddleCV/object_detection/ppdet/data/source/voc_loader.py) + - `source/coco_loader.py`: COCO dataset parser. [source](../ppdet/data/source/coco_loader.py) + - `source/voc_loader.py`: Pascal VOC dataset parser. [source](../ppdet/data/source/voc_loader.py) [Note] To use a non-default label list for VOC datasets, a `label_list.txt` file is needed, one can use the provided label list (`data/pascalvoc/ImageSets/Main/label_list.txt`) or generate a custom one (with `tools/generate_data_for_training.py`). Also, `use_default_label` option should be set to `false` in the configuration file - - `source/loader.py`: Roidb dataset parser. [source](https://github.com/PaddlePaddle/models/blob/develop/PaddleCV/object_detection/ppdet/data/source/loader.py) + - `source/loader.py`: Roidb dataset parser. [source](../ppdet/data/source/loader.py) 2. Operator `transform/operators.py`: Contains a variety of data enhancement methods, including: -- GitLab