easycv.models.pose package

Subpackages

• easycv.models.pose.heads package
  • Submodules
  • easycv.models.pose.heads.topdown_heatmap_base_head module
  • easycv.models.pose.heads.topdown_heatmap_simple_head module

Submodules

easycv.models.pose.top_down module

class easycv.models.pose.top_down.TopDown(backbone, neck=None, keypoint_head=None, train_cfg=None, test_cfg=None, pretrained=None, loss_pose=None)

Bases: easycv.models.base.BaseModel

Top-down pose detectors.

Parameters

• backbone (dict) – Backbone modules to extract feature.

• keypoint_head (dict) – Keypoint head to process feature.

• train_cfg (dict) – Config for training. Default: None.

• test_cfg (dict) – Config for testing. Default: None.

• pretrained (str) – Path to the pretrained models.

• loss_pose (None) – Deprecated arguments. Please use loss_keypoint for heads instead.

__init__(backbone, neck=None, keypoint_head=None, train_cfg=None, test_cfg=None, pretrained=None, loss_pose=None)

Initializes internal Module state, shared by both nn.Module and ScriptModule.

property with_neck

Check if has keypoint_head.

property with_keypoint

Check if has keypoint_head.

init_weights()

Weight initialization for model.

forward_train(img, target, target_weight, img_metas, **kwargs)

Defines the computation performed at every call when training.

forward_test(img, img_metas, return_heatmap=False, **kwargs)

Defines the computation performed at every call when testing.

forward_export(img, img_metas, return_heatmap=False)

show_result(img, result, skeleton=None, kpt_score_thr=0.3, bbox_color='green', pose_kpt_color=None, pose_link_color=None, text_color='white', radius=4, thickness=1, font_scale=0.5, bbox_thickness=1, win_name='', show=False, show_keypoint_weight=False, wait_time=0, out_file=None)

Draw result over img.

Parameters

• img (str or Tensor) – The image to be displayed.

• result (list[dict]) – The results to draw over img (bbox_result, pose_result).

• skeleton (list[list]) – The connection of keypoints. skeleton is 0-based indexing.

• kpt_score_thr (float, optional) – Minimum score of keypoints to be shown. Default: 0.3.

• bbox_color (str or tuple or Color) – Color of bbox lines.

• pose_kpt_color (np.array[Nx3]`) – Color of N keypoints. If None, do not draw keypoints.

• pose_link_color (np.array[Mx3]) – Color of M links. If None, do not draw links.

• text_color (str or tuple or Color) – Color of texts.

• radius (int) – Radius of circles.

• thickness (int) – Thickness of lines.

• font_scale (float) – Font scales of texts.

• win_name (str) – The window name.

• show (bool) – Whether to show the image. Default: False.

• show_keypoint_weight (bool) – Whether to change the transparency using the predicted confidence scores of keypoints.

• wait_time (int) – Value of waitKey param. Default: 0.

• out_file (str or None) – The filename to write the image. Default: None.

Returns

Visualized img, only if not show or out_file.

Return type

Tensor

training: bool