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visualization.py
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125 lines (110 loc) · 4.43 KB
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import numpy as np
import cv2
import torch
def draw_detections(img, detections, with_keypoints=True):
if isinstance(detections, torch.Tensor):
detections = detections.cpu().numpy()
if detections.ndim == 1:
detections = np.expand_dims(detections, axis=0)
n_keypoints = detections.shape[1] // 2 - 2
for i in range(detections.shape[0]):
ymin = detections[i, 0]
xmin = detections[i, 1]
ymax = detections[i, 2]
xmax = detections[i, 3]
start_point = (int(xmin), int(ymin))
end_point = (int(xmax), int(ymax))
img = cv2.rectangle(img, start_point, end_point, (255, 0, 0), 1)
if with_keypoints:
for k in range(n_keypoints):
kp_x = int(detections[i, 4 + k*2 ])
kp_y = int(detections[i, 4 + k*2 + 1])
cv2.circle(img, (kp_x, kp_y), 2, (0, 0, 255), thickness=2)
return img
def draw_roi(img, roi):
for i in range(roi.shape[0]):
(x1,x2,x3,x4), (y1,y2,y3,y4) = roi[i]
cv2.line(img, (int(x1), int(y1)), (int(x2), int(y2)), (0,0,0), 2)
cv2.line(img, (int(x1), int(y1)), (int(x3), int(y3)), (0,255,0), 2)
cv2.line(img, (int(x2), int(y2)), (int(x4), int(y4)), (0,0,0), 2)
cv2.line(img, (int(x3), int(y3)), (int(x4), int(y4)), (0,0,0), 2)
def draw_landmarks(img, points, connections=[], color=(0, 255, 0), size=2):
points = points[:,:2]
for point in points:
x, y = point
x, y = int(x), int(y)
cv2.circle(img, (x, y), size, color, thickness=size)
for connection in connections:
x0, y0 = points[connection[0]]
x1, y1 = points[connection[1]]
x0, y0 = int(x0), int(y0)
x1, y1 = int(x1), int(y1)
cv2.line(img, (x0, y0), (x1, y1), (0,0,0), size)
# https://github.com/metalwhale/hand_tracking/blob/b2a650d61b4ab917a2367a05b85765b81c0564f2/run.py
# 8 12 16 20
# | | | |
# 7 11 15 19
# 4 | | | |
# | 6 10 14 18
# 3 | | | |
# | 5---9---13--17
# 2 \ /
# \ \ /
# 1 \ /
# \ \ /
# ------0-
HAND_CONNECTIONS = [
(0, 1), (1, 2), (2, 3), (3, 4),
(5, 6), (6, 7), (7, 8),
(9, 10), (10, 11), (11, 12),
(13, 14), (14, 15), (15, 16),
(17, 18), (18, 19), (19, 20),
(0, 5), (5, 9), (9, 13), (13, 17), (0, 17)
]
POSE_CONNECTIONS = [
(0,1), (1,2), (2,3), (3,7),
(0,4), (4,5), (5,6), (6,8),
(9,10),
(11,13), (13,15), (15,17), (17,19), (19,15), (15,21),
(12,14), (14,16), (16,18), (18,20), (20,16), (16,22),
(11,12), (12,24), (24,23), (23,11)
]
# Vertex indices can be found in
# github.com/google/mediapipe/modules/face_geometry/data/canonical_face_model_uv_visualisation.png
# Found in github.com/google/mediapipe/python/solutions/face_mesh.py
FACE_CONNECTIONS = [
# Lips.
(61, 146), (146, 91), (91, 181), (181, 84), (84, 17),
(17, 314), (314, 405), (405, 321), (321, 375), (375, 291),
(61, 185), (185, 40), (40, 39), (39, 37), (37, 0),
(0, 267), (267, 269), (269, 270), (270, 409), (409, 291),
(78, 95), (95, 88), (88, 178), (178, 87), (87, 14),
(14, 317), (317, 402), (402, 318), (318, 324), (324, 308),
(78, 191), (191, 80), (80, 81), (81, 82), (82, 13),
(13, 312), (312, 311), (311, 310), (310, 415), (415, 308),
# Left eye.
(263, 249), (249, 390), (390, 373), (373, 374), (374, 380),
(380, 381), (381, 382), (382, 362), (263, 466), (466, 388),
(388, 387), (387, 386), (386, 385), (385, 384), (384, 398),
(398, 362),
# Left eyebrow.
(276, 283), (283, 282), (282, 295), (295, 285), (300, 293),
(293, 334), (334, 296), (296, 336),
# Right eye.
(33, 7), (7, 163), (163, 144), (144, 145), (145, 153),
(153, 154), (154, 155), (155, 133), (33, 246), (246, 161),
(161, 160), (160, 159), (159, 158), (158, 157), (157, 173),
(173, 133),
# Right eyebrow.
(46, 53), (53, 52), (52, 65), (65, 55), (70, 63), (63, 105),
(105, 66), (66, 107),
# Face oval.
(10, 338), (338, 297), (297, 332), (332, 284), (284, 251),
(251, 389), (389, 356), (356, 454), (454, 323), (323, 361),
(361, 288), (288, 397), (397, 365), (365, 379), (379, 378),
(378, 400), (400, 377), (377, 152), (152, 148), (148, 176),
(176, 149), (149, 150), (150, 136), (136, 172), (172, 58),
(58, 132), (132, 93), (93, 234), (234, 127), (127, 162),
(162, 21), (21, 54), (54, 103), (103, 67), (67, 109),
(109, 10)
]