Customize datasets by reorganizing data to COCO format. The simplest way to use the custom dataset is to convert your annotation format to COCO dataset format. |
In this document, we will give a guide on the process of preparing datasets for the MMPose. Various aspects of dataset preparation will be discussed. |
Detectors pre-trained on the COCO dataset can serve as a good pre-trained model for other datasets, e.g., COCO-WholeBody Dataset. |
I'm attempting to train MMPose on a custom dataset of body keypoints. As per documentation I have: created a dataset config file which lists all keypoints ... |
Download person detection result of COCO val2017 from OneDrive. Download and extract them under $MMPOSE/data, and make them look like this: mmpose ├── mmpose ... |
COCO-WholeBody is an extension of COCO dataset with whole-body annotations. There are 4 types of bounding boxes (person box, face box, left-hand box, and right ... |
The simplest way to use the custom dataset is to convert your annotation format to existing COCO dataset format. The annotation json files in COCO format has ... |
The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. COCO minival · Microsoft COCO · Instance Segmentation · Videos |
We first download the demo dataset, which contains 100 samples (75 for training and 25 for validation) selected from COCO train2017 dataset. The annotations are ... |
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