# Facial Keypoint Detection — Data

来源：https://www.kaggle.com/competitions/facial-keypoint-detection/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

<p>&nbsp;</p>
<p>Each keypoint to be predicted is specified by an (x,y) real-valued pair in the space of pixel indices. There are 15 keypoints, which represent the following elements of the face:</p>
<p>left_eye_center,&nbsp;<span>right_eye_center, left_eye_inner_corner, left_eye_outer_corner, right_eye_inner_corner, right_eye_outer_corner, left_eyebrow_inner_end, left_eyebrow_outer_end, right_eyebrow_inner_end, right_eyebrow_outer_end, nose_tip, mouth_left_corner,
 mouth_right_corner, mouth_center_top_lip, mouth_center_bottom_lip</span></p>
<p>Left and right here refers to the point of view of the subject, i.e, our right in the images.</p>
<p>In some examples, some of the target keypoint positions are misssing (encoded as missing entries in the csv, i.e., with nothing betwen two commas).</p>
<p>The input image is given in the last field of the data files, and consists of a list of pixels (ordered by row), as integers in (0,255). The images are 96x96 pixels.</p>
<p><strong>Data files</strong></p>
<ul>
<li><strong>training.csv:</strong>&nbsp;list of training 7049 images. Each row contains the (x,y) coordinates for 15 keypoints, and image data as row-ordered list of pixels.
</li><li><strong>test.csv:</strong>&nbsp;list of 1783 test images. Each row contains ImageId and image data as row-ordered list of pixels
</li><li><strong>submissionFileFormat.csv:</strong>&nbsp;list of 27124 keypoints to predict. Each row contains a RowId, ImageId, FeatureName, Location. FeatureName are &quot;left_eye_center_x,&quot; &quot;right_eyebrow_outer_end_y,&quot; etc. Location is what you need to predict.&nbsp;
</li></ul>