def main(args):
code = wrnchAI.license_check_string(args.license_key) if args.license_key \
else wrnchAI.license_check()
if code != 0:
raise RuntimeError(wrnchAI.returncode_describe(code))
frame = cv2.imread(args.image)
if frame is None:
raise RuntimeError('could not read image at {}'.format(args.image))
print('Initializing networks...')
estimator = wrnchAI.PoseEstimator(models_path=args.models_dir,
license_string=args.license_key)
print('Initialization done')
options = wrnchAI.PoseEstimatorOptions()
print('Inferring ...')
estimator.process_frame(frame, options)
num_persons = len(estimator.humans_2d())
print('Inference done! Found ', num_persons, ' humans')
def main(args):
code = wrnchAI.license_check_string(args.license_key) if args.license_key \
else wrnchAI.license_check()
if code != 0:
raise RuntimeError(wrnchAI.returncode_describe(code))
params = wrnchAI.PoseParams()
params.bone_sensitivity = wrnchAI.Sensitivity.high
params.joint_sensitivity = wrnchAI.Sensitivity.high
params.enable_tracking = True
# Default Model resolution
params.preferred_net_width = 328
params.preferred_net_height = 184
output_format = wrnchAI.JointDefinitionRegistry.get('j23')
print('Initializing networks...')
estimator = wrnchAI.PoseEstimator(models_path=args.models_dir,
license_string=args.license_key,
params=params,
gpu_id=0,
output_format=output_format)
print('Initialization done!')
options = wrnchAI.PoseEstimatorOptions()
print('Opening webcam...')
with videocapture_context(args.webcam_index) as cap:
visualizer = Visualizer()
joint_definition = estimator.human_2d_output_format()
bone_pairs = joint_definition.bone_pairs()
while True:
_, frame = cap.read()
if frame is not None:
estimator.process_frame(frame, options) ### passing in frame
humans2d = estimator.humans_2d()
### visualizer is using opencv: using frame and draws over it
visualizer.draw_image(frame) ### overlaying skeleton
for human in humans2d:
joints = human.joints()
visualizer.draw_points(joints)
visualizer.draw_lines(joints, bone_pairs)
visualizer.show()
key = cv2.waitKey(1)
if key & 255 == 27:
break
def main(args):
code = wrnchAI.license_check_string(args.license_key) if args.license_key \
else wrnchAI.license_check()
if code != 0:
raise RuntimeError(wrnchAI.returncode_describe(code))
print('Initializing networks...')
estimator = wrnchAI.PoseEstimator(models_path=args.models_dir,
license_string=args.license_key)
estimator.initialize_head(args.models_dir)
print('Initialization done!')
options = wrnchAI.PoseEstimatorOptions()
options.estimate_heads = True
options.estimate_face_poses = True
print('Opening webcam...')
with videocapture_context(args.webcam_index) as cap:
visualizer = Visualizer()
while True:
_, frame = cap.read()
if frame is not None:
estimator.process_frame(frame, options)
heads = estimator.heads()
faces = estimator.faces()
visualizer.draw_image(frame)
for head in heads:
bounding_box = head.bounding_box
visualizer.draw_box(bounding_box.min_x, bounding_box.min_y,
bounding_box.width,
bounding_box.height)
for face in faces:
landmarks = face.landmarks()
arrow = face.arrow()
visualizer.draw_points(landmarks, joint_size=2)
visualizer.draw_arrow(arrow)
visualizer.show()
key = cv2.waitKey(1)
if key & 255 == 27: # escape key
break
def main(args):
code = wrnchAI.license_check_string(args.license_key) if args.license_key \
else wrnchAI.license_check()
if code != 0:
raise RuntimeError(wrnchAI.returncode_describe(code))
print("Initializing networks...")
estimator = wrnchAI.PoseEstimator(models_path=args.models_dir,
license_string=args.license_key)
estimator.initialize_3d(args.models_dir)
print("Initialization done!")
options = wrnchAI.PoseEstimatorOptions()
options.estimate_3d = True
visualizer = Visualizer()
print("Opening webcam...")
with videocapture_context(args.webcam_index) as cap:
while True:
_, frame = cap.read()
if frame is not None:
estimator.process_frame(frame, options)
humans3d = estimator.raw_humans_3d()
visualizer.draw_image(frame)
for human in humans3d:
positions = human.positions()
visualizer.draw_points3d(positions)
visualizer.show()
key = cv2.waitKey(1)
if key & 255 == 27:
break
def wrnch_func(args):
print("Inside wrnch_func...")
print(args.pose_estimator, " = selected pose estimator")
print(args.license_key, " = license key")
reset_camera()
input_handler()
# from /usr/src/wrnchAI/wrSamples/python/pose3d_sample.py
code = wrnchAI.license_check_string(args.license_key) if args.license_key \
else wrnchAI.license_check()
if code != 0:
raise RuntimeError(wrnchAI.returncode_describe(code))
# params
params = wrnchAI.PoseParams()
params.bone_sensitivity = wrnchAI.Sensitivity.high
params.joint_sensitivity = wrnchAI.Sensitivity.high
params.enable_tracking = True
# Default Model resolution
params.preferred_net_width = 328
params.preferred_net_height = 184
# model
output_format = wrnchAI.JointDefinitionRegistry.get('j23')
try:
print('Initializing PoseEstimator...')
estimator = wrnchAI.PoseEstimator(models_path=args.models_dir,
license_string=args.license_key,
params=params,
gpu_id=0,
output_format=output_format)
# which type to process frame
options = wrnchAI.PoseEstimatorOptions()
options.estimate_3d = True
print('Initialization done!')
except:
print_exc()
print('Opening webcam...')
with cv2.VideoCapture(-1) as cap:
visualizer = Visualizer()
joint_definition = estimator.human_3d_output_format()
# bone_pairs = joint_definition.bone_pairs()
while True:
# capture frame by frame
_, frame = cap.read()
if frame is not None:
# passing in frame
estimator.process_frame(frame, options)
# get the pose3d's last estimation by PoseEstimator, returns list of Pose2d <<<
humans3d = estimator.humans_3d()
# visualizer is using opencv: using frame and draws over it
visualizer.draw_image(frame) ### overlaying skeleton
for human in humans3d:
joints = human.joints()
visualizer.draw_points(joints)
visualizer.draw_lines(joints)
visualizer.show()
key = cv2.waitKey(1)
if key & 255 == 27:
break
# Copyright (c) 2019 Wrnch Inc.
# All rights reserved
from __future__ import print_function, division
import sys
import cv2
import wrnchAI
from visualizer import Visualizer
if not wrnchAI.license_check():
sys.exit('A valid license is required to run the samples')
num_args = len(sys.argv)
if num_args < 2 or num_args > 3:
sys.exit(
'Usage: python pose2d_sample.py <model path> [camera index {0}]')
if num_args == 3:
webcam_index = int(sys.argv[2])
else:
webcam_index = 0
params = wrnchAI.PoseParams()
params.bone_sensitivity = wrnchAI.Sensitivity.high
params.joint_sensitivity = wrnchAI.Sensitivity.high
params.enable_tracking = True
# Default Model resolution
params.preferred_net_width = 328