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import math
import numpy as np
import matplotlib
import cv2
eps = 0.01
def alpha_blend_color(color, alpha):
"""blend color according to point conf
"""
return [int(c * alpha) for c in color]
def draw_bodypose(canvas, candidate, subset, score):
H, W, C = canvas.shape
candidate = np.array(candidate)
subset = np.array(subset)
stickwidth = 4
limbSeq = [[2, 3], [2, 6], [3, 4], [4, 5], [6, 7], [7, 8], [2, 9], [9, 10], \
[10, 11], [2, 12], [12, 13], [13, 14], [2, 1], [1, 15], [15, 17], \
[1, 16], [16, 18], [3, 17], [6, 18]]
colors = [[255, 0, 0], [255, 85, 0], [255, 170, 0], [255, 255, 0], [170, 255, 0], [85, 255, 0], [0, 255, 0], \
[0, 255, 85], [0, 255, 170], [0, 255, 255], [0, 170, 255], [0, 85, 255], [0, 0, 255], [85, 0, 255], \
[170, 0, 255], [255, 0, 255], [255, 0, 170], [255, 0, 85]]
for i in range(17):
for n in range(len(subset)):
index = subset[n][np.array(limbSeq[i]) - 1]
conf = score[n][np.array(limbSeq[i]) - 1]
if conf[0] < 0.3 or conf[1] < 0.3:
continue
Y = candidate[index.astype(int), 0] * float(W)
X = candidate[index.astype(int), 1] * float(H)
mX = np.mean(X)
mY = np.mean(Y)
length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5
angle = math.degrees(math.atan2(X[0] - X[1], Y[0] - Y[1]))
polygon = cv2.ellipse2Poly((int(mY), int(mX)), (int(length / 2), stickwidth), int(angle), 0, 360, 1)
cv2.fillConvexPoly(canvas, polygon, alpha_blend_color(colors[i], conf[0] * conf[1]))
canvas = (canvas * 0.6).astype(np.uint8)
for i in range(18):
for n in range(len(subset)):
index = int(subset[n][i])
if index == -1:
continue
x, y = candidate[index][0:2]
conf = score[n][i]
x = int(x * W)
y = int(y * H)
cv2.circle(canvas, (int(x), int(y)), 4, alpha_blend_color(colors[i], conf), thickness=-1)
return canvas
def draw_handpose(canvas, all_hand_peaks, all_hand_scores):
H, W, C = canvas.shape
edges = [[0, 1], [1, 2], [2, 3], [3, 4], [0, 5], [5, 6], [6, 7], [7, 8], [0, 9], [9, 10], \
[10, 11], [11, 12], [0, 13], [13, 14], [14, 15], [15, 16], [0, 17], [17, 18], [18, 19], [19, 20]]
for peaks, scores in zip(all_hand_peaks, all_hand_scores):
for ie, e in enumerate(edges):
x1, y1 = peaks[e[0]]
x2, y2 = peaks[e[1]]
x1 = int(x1 * W)
y1 = int(y1 * H)
x2 = int(x2 * W)
y2 = int(y2 * H)
score = int(scores[e[0]] * scores[e[1]] * 255)
if x1 > eps and y1 > eps and x2 > eps and y2 > eps:
cv2.line(canvas, (x1, y1), (x2, y2),
matplotlib.colors.hsv_to_rgb([ie / float(len(edges)), 1.0, 1.0]) * score, thickness=2)
for i, keyponit in enumerate(peaks):
x, y = keyponit
x = int(x * W)
y = int(y * H)
score = int(scores[i] * 255)
if x > eps and y > eps:
cv2.circle(canvas, (x, y), 4, (0, 0, score), thickness=-1)
return canvas
def draw_facepose(canvas, all_lmks, all_scores):
H, W, C = canvas.shape
for lmks, scores in zip(all_lmks, all_scores):
for lmk, score in zip(lmks, scores):
x, y = lmk
x = int(x * W)
y = int(y * H)
conf = int(score * 255)
if x > eps and y > eps:
cv2.circle(canvas, (x, y), 3, (conf, conf, conf), thickness=-1)
return canvas
def draw_pose(pose, H, W, ref_w=2160):
"""vis dwpose outputs
Args:
pose (List): DWposeDetector outputs in dwpose_detector.py
H (int): height
W (int): width
ref_w (int, optional) Defaults to 2160.
Returns:
np.ndarray: image pixel value in RGB mode
"""
bodies = pose['bodies']
faces = pose['faces']
hands = pose['hands']
candidate = bodies['candidate']
subset = bodies['subset']
sz = min(H, W)
sr = (ref_w / sz) if sz != ref_w else 1
########################################## create zero canvas ##################################################
canvas = np.zeros(shape=(int(H*sr), int(W*sr), 3), dtype=np.uint8)
########################################### draw body pose #####################################################
canvas = draw_bodypose(canvas, candidate, subset, score=bodies['score'])
########################################### draw hand pose #####################################################
canvas = draw_handpose(canvas, hands, pose['hands_score'])
########################################### draw face pose #####################################################
canvas = draw_facepose(canvas, faces, pose['faces_score'])
return cv2.cvtColor(cv2.resize(canvas, (W, H)), cv2.COLOR_BGR2RGB).transpose(2, 0, 1)
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