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d426818 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | import cv2
from ultralytics.utils.plotting import colors
class PlotPose:
def __init__(self):
self.skeleton = [
[16, 14],
[14, 12],
[17, 15],
[15, 13],
[12, 13],
[6, 12],
[7, 13],
[6, 7],
[6, 8],
[7, 9],
[8, 10],
[9, 11],
[2, 3],
[1, 2],
[1, 3],
[2, 4],
[3, 5],
[4, 6],
[5, 7],
]
self.limb_color = colors.pose_palette[[9, 9, 9, 9, 7, 7, 7, 0, 0, 0, 0, 0, 16, 16, 16, 16, 16, 16, 16]]
self.kpt_color = colors.pose_palette[[16, 16, 16, 16, 16, 0, 0, 0, 0, 0, 0, 9, 9, 9, 9, 9, 9]]
def plot(self,im,
kpts,
shape=(640, 640),
radius=None,
kpt_line=True,
conf_thres= 0.25,):
"""
Plot keypoints on the image.
Args:
im (numpy array): img to plot keypoints
kpts (numpy arrayr): Keypoints, shape [17, 3] (x, y, confidence).
shape (tuple, optional): Image shape (h, w).
radius (int, optional): Keypoint radius.
kpt_line (bool, optional): Draw lines between keypoints.
conf_thres (float, optional): Confidence threshold.
kpt_color (tuple, optional): Keypoint color (B, G, R).
Note:
- `kpt_line=True` currently only supports human pose plotting.
- Modifies self.im in-place.
- If self.pil is True, converts image to numpy array and back to PIL.
"""
self.lw = 4
radius = radius if radius is not None else self.lw
nkpt, ndim = kpts.shape
is_pose = nkpt == 17 and ndim in {2, 3}
kpt_line &= is_pose # `kpt_line=True` for now only supports human pose plotting
for i, k in enumerate(kpts):
color_k = self.kpt_color[i].tolist()
# color_k = kpt_color or (kpt_color[i].tolist() if is_pose else colors(i))
x_coord, y_coord = k[0], k[1]
if x_coord % shape[1] != 0 and y_coord % shape[0] != 0:
if len(k) == 3:
conf = k[2]
if conf < conf_thres:
continue
cv2.circle(im, (int(x_coord), int(y_coord)), radius, 255, -1, lineType=cv2.LINE_AA)
if kpt_line:
ndim = kpts.shape[-1]
for i, sk in enumerate(self.skeleton):
pos1 = (int(kpts[(sk[0] - 1), 0]), int(kpts[(sk[0] - 1), 1]))
pos2 = (int(kpts[(sk[1] - 1), 0]), int(kpts[(sk[1] - 1), 1]))
if ndim == 3:
conf1 = kpts[(sk[0] - 1), 2]
conf2 = kpts[(sk[1] - 1), 2]
if conf1 < conf_thres or conf2 < conf_thres:
continue
if pos1[0] % shape[1] == 0 or pos1[1] % shape[0] == 0 or pos1[0] < 0 or pos1[1] < 0:
continue
if pos2[0] % shape[1] == 0 or pos2[1] % shape[0] == 0 or pos2[0] < 0 or pos2[1] < 0:
continue
cv2.line(
im,
pos1,
pos2,
self.limb_color[i].tolist(),
thickness=int(self.lw ),
lineType=cv2.LINE_AA,
)
return im
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