From 2c28ff02fab1f20dbbdfc225cf536e59702b7dd6 Mon Sep 17 00:00:00 2001 From: pinto0309 Date: Tue, 14 Nov 2023 18:00:31 +0900 Subject: [PATCH] =?UTF-8?q?Z=E8=BB=B8=E3=81=AE=E5=9B=9E=E8=BB=A2=E3=81=AB?= =?UTF-8?q?=E5=AF=BE=E5=BF=9C=E3=81=97=E3=81=9F=E3=83=A1=E3=82=BD=E3=83=83?= =?UTF-8?q?=E3=83=89=E3=82=92=E8=BF=BD=E5=8A=A0=E3=80=81Z=E8=BB=B8?= =?UTF-8?q?=E3=81=AE=E5=8F=82=E8=80=83=E5=80=A4=E3=82=92=E8=BF=BD=E8=A8=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .vscode/launch.json | 8 ++++ README.md | 18 ++++++++ demo_goldyolo_onnx.py | 68 ++++++++++++++++++++++++------- output_image_20231114_173009.png | Bin 0 -> 328640 bytes output_image_20231114_173017.png | Bin 0 -> 336797 bytes output_image_20231114_173022.png | Bin 0 -> 352040 bytes output_image_20231114_173026.png | Bin 0 -> 336749 bytes output_image_20231114_173031.png | Bin 0 -> 321470 bytes output_image_20231114_174046.png | Bin 0 -> 320504 bytes output_image_20231114_174311.png | Bin 0 -> 331730 bytes 10 files changed, 80 insertions(+), 14 deletions(-) create mode 100644 output_image_20231114_173009.png create mode 100644 output_image_20231114_173017.png create mode 100644 output_image_20231114_173022.png create mode 100644 output_image_20231114_173026.png create mode 100644 output_image_20231114_173031.png create mode 100644 output_image_20231114_174046.png create mode 100644 output_image_20231114_174311.png diff --git a/.vscode/launch.json b/.vscode/launch.json index 39bc221..04308bb 100644 --- a/.vscode/launch.json +++ b/.vscode/launch.json @@ -15,6 +15,14 @@ // "-v", "output_image_20231027_222428.png", // "-v", "output_image_20231027_231123.png", // "-v", "output_image_20231030_152302.png", + + // "-v", "output_image_20231114_173009.png", + // "-v", "output_image_20231114_173017.png", + // "-v", "output_image_20231114_173022.png", + // "-v", "output_image_20231114_173026.png", + // "-v", "output_image_20231114_173031.png", + // "-v", "output_image_20231114_174046.png", + // "-v", "output_image_20231114_174311.png", ] } ] diff --git a/README.md b/README.md index 258402c..c5c56e9 100644 --- a/README.md +++ b/README.md @@ -9,3 +9,21 @@ https://github.com/PINTO0309/PINTO_model_zoo - demo https://github.com/PINTO0309/hand_landmark/assets/33194443/9e4e188b-5c44-46fc-8328-21ae8a122971 + + +``` +z: + - 手首のキーポイントの位置を0.0とした数値 (ほぼ0.0だが0.0よりほんの少し大きい値になる) + - カメラ方向がマイナス、奥方向がプラス + - 正規化されていない + - 実測してみた結果 -80.0 〜 +80.0 の範囲で推移する (なお、ほぼ水平の手は検出不可能) + - カメラからの距離や対象の手のひらのサイズ感には影響を受けない (224x224の固定サイズに伸縮して推論しているため) + + output_image_20231114_173009.png 手首z[0]: 0.0001862049102783203, 中指先端z[12]: 45.90625 + output_image_20231114_173017.png 手首z[0]: 0.00020122528076171875, 中指先端z[12]: 61.59375 + output_image_20231114_173022.png 手首z[0]: 0.0001690387725830078, 中指先端z[12]: 1.0263671875 + output_image_20231114_173026.png 手首z[0]: 0.00021648406982421875, 中指先端z[12]: -73.5625 + output_image_20231114_173031.png 手首z[0]: 0.0002181529998779297, 中指先端z[12]: -65.8125 + output_image_20231114_174046.png 手首z[0]: 0.0002727508544921875, 中指先端z[12]: -79.875 + output_image_20231114_174311.png 手首z[0]: 0.00013566017150878906, 中指先端z[12]: 63.75 +``` \ No newline at end of file diff --git a/demo_goldyolo_onnx.py b/demo_goldyolo_onnx.py index 969af52..22e5049 100644 --- a/demo_goldyolo_onnx.py +++ b/demo_goldyolo_onnx.py @@ -10,6 +10,12 @@ from typing import Tuple, Optional, List from dataclasses import dataclass +RED="\033[31m" +YELLOW="\033[33m" +GREEN="\033[32m" +BLUE="\033[34m" +RESET="\033[0m" + @dataclass(frozen=False) class PaddingsAndScale(): padding_height: int # 224x224へリサイズするときに足された合計パディング幅(奇数になることがある) @@ -880,14 +886,13 @@ def __postprocess( image_width = image.shape[1] xyz_x21s = xyz_x21s.reshape([-1, 21, 3]) # [N, 65] -> [N, 21, XYZ] - xy_x21s = xyz_x21s[..., 0:2] # 奥行き情報Zを捨てる, [N, 21, XYZ] -> [N, 21, XY] keep = hand_scores[:, 0] > self.class_score_th hand_224x224_images = [ hand_224x224_image \ for idx, hand_224x224_image in enumerate(hand_224x224_images) if keep[idx] ] - xy_x21s = xy_x21s[keep, ...] + xyz_x21s = xyz_x21s[keep, ...] hand_scores = hand_scores[keep, ...] lefthand_0_or_righthand_1s = lefthand_0_or_righthand_1s[keep, ...] rec_size_difference_rotation_angles = [ @@ -903,8 +908,8 @@ def __postprocess( for kidx, kvalue in enumerate(keep) if kvalue ] - for idx, (hand_224x224_image, kidx, xy_x21, lefthand_0_or_righthand_1, paddings_and_scale) \ - in enumerate(zip(hand_224x224_images, keeps, xy_x21s, lefthand_0_or_righthand_1s, paddings_and_scales)): + for idx, (hand_224x224_image, kidx, xyz_x21, lefthand_0_or_righthand_1, paddings_and_scale) \ + in enumerate(zip(hand_224x224_images, keeps, xyz_x21s, lefthand_0_or_righthand_1s, paddings_and_scales)): # 入力画像のスケールに戻す # 1. 224x224画像を使用して推論したキーポイントの座標情報は、パディングとスケールが反映された値になっている @@ -920,10 +925,10 @@ def __postprocess( # 224x224の座標系に対して、224x224へ変更するときに適用したパディングとリサイズの影響を取り除く # 座標値は全体画像の座標系ではなく、パディングとリサイズを元に戻した手のひらの部分だけの座標系 - xy_x21[:, 0] = xy_x21[:, 0] - paddings_and_scale.padding_width // 2 - xy_x21[:, 0] = xy_x21[:, 0] / paddings_and_scale.scale_width - xy_x21[:, 1] = xy_x21[:, 1] - paddings_and_scale.padding_height // 2 - xy_x21[:, 1] = xy_x21[:, 1] / paddings_and_scale.scale_height + xyz_x21[:, 0] = xyz_x21[:, 0] - paddings_and_scale.padding_width // 2 + xyz_x21[:, 0] = xyz_x21[:, 0] / paddings_and_scale.scale_width + xyz_x21[:, 1] = xyz_x21[:, 1] - paddings_and_scale.padding_height // 2 + xyz_x21[:, 1] = xyz_x21[:, 1] / paddings_and_scale.scale_height cx = 112 - paddings_and_scale.padding_width // 2 cx = cx / paddings_and_scale.scale_width cy = 112 - paddings_and_scale.padding_height // 2 @@ -945,23 +950,40 @@ def __postprocess( temp_image = image_rotation_without_crop(images=[temp_image], angles=[-hand_info.palm.degree]) # パディングとリサイズを元に戻した手のひら画像に対して回転角を元に戻す - rotated_xy_x21 = \ - rotate_points_around_center( - points_xy=xy_x21, + rotated_xyz_x21 = \ + rotate_points_around_center_3d( + points_xyz=xyz_x21, degree=hand_info.palm.degree, cx=temp_image_cx, cy=temp_image_cy, + cz=0.0, ) + # z: + # 手首のキーポイントの位置を0.0とした数値 (ほぼ0.0だが0.0よりほんの少し大きい値になる) + # 手前方向がマイナス値、奥方向がプラス値 + # 正規化されていないうえに数値の下限と上限は不明 + # + # output_image_20231114_173009.png 手首z: 0.0001862049102783203, 中指先端z: 45.90625 + # output_image_20231114_173017.png 手首z: 0.00020122528076171875, 中指先端z: 61.59375 + # output_image_20231114_173022.png 首z: 0.0001690387725830078, 中指先端z: 1.0263671875 + # output_image_20231114_173026.png 手首z: 0.00021648406982421875, 中指先端z: -73.5625 + # output_image_20231114_173031.png 手首z: 0.0002181529998779297, 中指先端z: -65.8125 + # output_image_20231114_174046.png 手首z: 0.0002727508544921875, 中指先端z: -79.875 + # output_image_20231114_174311.png 手首z: 0.00013566017150878906, 中指先端z: 63.75 hand_info.keypoints = [ Point3D( x=(x + hand_info.x1 * image_width - rec_size_difference_rotation_angles[idx][0] / 2) / image_width, y=(y + hand_info.y1 * image_height - rec_size_difference_rotation_angles[idx][1] / 2) / image_height, - z=None, + z=z, depth=None, - ) for x, y in rotated_xy_x21 + ) for x, y, z in rotated_xyz_x21 ] + # debug + if len(hand_infos) > 0 and hand_infos[0].keypoints is not None and len(hand_infos[0].keypoints) > 0: + print(f'{GREEN}手首z:{RESET} {hand_infos[0].keypoints[0].z}, {YELLOW}中指先端z:{RESET} {hand_infos[0].keypoints[12].z}') + # 元画像スケールの手のひら位置情報 return hand_infos @@ -1481,6 +1503,24 @@ def rotate_points_around_center(*, points_xy: np.ndarray, degree: float, cx: flo rotated_points: np.ndarray = rotated_translated + np.array([cx, cy]) return rotated_points +def rotate_points_around_center_3d(*, points_xyz: np.ndarray, degree: float, cx: float, cy: float, cz: float) -> np.ndarray: + # 角度をラジアンに変換 + theta = np.radians(degree) + + # Z軸周りの3次元回転行列を作成 + rotation_matrix = np.array([ + [np.cos(theta), -np.sin(theta), 0], + [np.sin(theta), np.cos(theta), 0], + [0, 0, 1] + ]) + # 中心点を原点に移動 + xyz_translated = points_xyz - np.array([cx, cy, cz]) + # 移動した点を回転 + rotated_translated = 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