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import sys
from math import sqrt
import logging
import numpy as np
import cv2 as cv
log = logging.getLogger('swimmer')
# ---------------------------------------------------------------------------
# 3D landmark drawing utilities
# ---------------------------------------------------------------------------
end_list = np.array([17, 22, 27, 42, 48, 31, 36, 68], dtype=np.int32) - 1
def plot_keypoints(im, kpts):
'''Draw 68 key points
:param im: the input im
:param kpts: (68, 3). flattened list
'''
im = im.copy()
kpts = np.round(kpts).astype(np.int32)
for i in range(kpts.shape[0]):
st = kpts[i, :2]
im = cv.circle(im, (st[0], st[1]), 1, (0, 0, 255), 2)
if i in end_list:
continue
ed = kpts[i + 1, :2]
im = cv.line(im, (st[0], st[1]), (ed[0], ed[1]), (255, 255, 255), 1)
return im
def calc_hypotenuse(pts):
bbox = [min(pts[0, :]), min(pts[1, :]), max(pts[0, :]), max(pts[1, :])]
center = [(bbox[0] + bbox[2]) / 2, (bbox[1] + bbox[3]) / 2]
radius = max(bbox[2] - bbox[0], bbox[3] - bbox[1]) / 2
bbox = [center[0] - radius, center[1] - radius, center[0] + radius, center[1] + radius]
llength = sqrt((bbox[2] - bbox[0]) ** 2 + (bbox[3] - bbox[1]) ** 2)
return llength / 3
def build_camera_box(rear_size=90):
point_3d = []
rear_depth = 0
point_3d.append((-rear_size, -rear_size, rear_depth))
point_3d.append((-rear_size, rear_size, rear_depth))
point_3d.append((rear_size, rear_size, rear_depth))
point_3d.append((rear_size, -rear_size, rear_depth))
point_3d.append((-rear_size, -rear_size, rear_depth))
front_size = int(4 / 3 * rear_size)
front_depth = int(4 / 3 * rear_size)
point_3d.append((-front_size, -front_size, front_depth))
point_3d.append((-front_size, front_size, front_depth))
point_3d.append((front_size, front_size, front_depth))
point_3d.append((front_size, -front_size, front_depth))
point_3d.append((-front_size, -front_size, front_depth))
point_3d = np.array(point_3d, dtype=np.float).reshape(-1, 3)
return point_3d
def plot_pose_box(im, Ps, pts68s, color=(40, 255, 0), line_width=2):
'''Draw a 3D box as annotation of pose.
ref: https://github.com/yinguobing/head-pose-estimation/blob/master/pose_estimator.py
:param image: the input image
:param P: (3, 4). Affine Camera Matrix.
:param kpts: (2, 68) or (3, 68)
'''
im_draw = im.copy()
if not isinstance(pts68s, list):
pts68s = [pts68s]
if not isinstance(Ps, list):
Ps = [Ps]
for i in range(len(pts68s)):
pts68 = pts68s[i]
llength = calc_hypotenuse(pts68)
point_3d = build_camera_box(llength)
P = Ps[i]
# Map to 2d im points
point_3d_homo = np.hstack((point_3d, np.ones([point_3d.shape[0], 1]))) # n x 4
point_2d = point_3d_homo.dot(P.T)[:, :2]
point_2d[:, 1] = - point_2d[:, 1]
point_2d[:, :2] = point_2d[:, :2] - np.mean(point_2d[:4, :2], 0) + np.mean(pts68[:2, :27], 1)
point_2d = np.int32(point_2d.reshape(-1, 2))
# Draw all the lines
cv.polylines(im_draw, [point_2d], True, color, line_width, cv.LINE_AA)
cv.line(im_draw, tuple(point_2d[1]), tuple(point_2d[6]), color, line_width, cv.LINE_AA)
cv.line(im_draw, tuple(point_2d[2]), tuple(point_2d[7]), color, line_width, cv.LINE_AA)
cv.line(im_draw, tuple(point_2d[3]), tuple(point_2d[8]), color, line_width, cv.LINE_AA)
return im_draw
# ---------------------------------------------------------------------------
#
# OpenCV drawing functions
#
# ---------------------------------------------------------------------------
pose_types = {'pitch': (0,0,255), 'roll': (255,0,0), 'yaw': (0,255,0)}
def draw_landmarks2D(im, points_norm, radius=3, color=(0,255,0)):
'''Draws facial landmarks, either 5pt or 68pt
'''
im_dst = im.copy()
dim = im.shape[:2][::-1]
for x,y in points_norm:
pt = (int(x*dim[0]), int(y*dim[1]))
cv.circle(im_dst, pt, radius, color, -1, cv.LINE_AA)
return im_dst
def draw_landmarks3D(im, points, radius=3, color=(0,255,0)):
'''Draws 3D facial landmarks
'''
im_dst = im.copy()
for x,y,z in points:
cv.circle(im_dst, (x,y), radius, color, -1, cv.LINE_AA)
return im_dst
def draw_bbox(im, bbox_norm, color=(0,255,0), stroke_weight=2):
'''Draws BBox onto cv image
'''
im_dst = im.copy()
bbox_dim = bbox_norm.to_bbox_dim(im.shape[:2][::-1])
cv.rectangle(im_dst, bbox_dim.p1.xy, bbox_dim.p2.xy, color, stroke_weight, cv.LINE_AA)
return im_dst
def draw_pose(im, pt_nose, image_pts):
'''Draws 3-axis pose over image
TODO: normalize point data
'''
im_dst = im.copy()
log.debug(f'pt_nose: {pt_nose}')
log.debug(f'image_pts pitch: {image_pts["pitch"]}')
cv.line(im_dst, pt_nose, tuple(image_pts['pitch']), pose_types['pitch'], 3)
cv.line(im_dst, pt_nose, tuple(image_pts['yaw']), pose_types['yaw'], 3)
cv.line(im_dst, pt_nose, tuple(image_pts['roll']), pose_types['roll'], 3)
return im_dst
def draw_text(im, pt_norm, text, size=1.0, color=(0,255,0)):
'''Draws degrees as text over image
'''
im_dst = im.copy()
dim = im.shape[:2][::-1]
pt = tuple(map(int, (pt_norm[0]*dim[0], pt_norm[1]*dim[1])))
cv.putText(im_dst, text, pt, cv.FONT_HERSHEY_SIMPLEX, size, color, thickness=1, lineType=cv.LINE_AA)
return im_dst
def draw_degrees(im, pose_data, color=(0,255,0)):
'''Draws degrees as text over image
'''
im_dst = im.copy()
for i, pose_type in enumerate(pose_types.items()):
k, clr = pose_type
v = pose_data[k]
t = '{}: {:.2f}'.format(k, v)
origin = (10, 30 + (25 * i))
cv.putText(im_dst, t, origin, cv.FONT_HERSHEY_SIMPLEX, 0.5, clr, thickness=2, lineType=2)
return im_dst
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