def __init__(self,
number_people_max=-1,
min_size=-1,
openpose_rendering=False,
face_detection=False,
frt=0.4,
hand_detection=False,
debug=False):
"""
openpose_rendering : if True, rendering is made by original Openpose library. Otherwise rendering is to the
responsability of the user (~0.2 fps faster)
"""
self.openpose_rendering = openpose_rendering
self.min_size = min_size
self.debug = debug
self.face_detection = face_detection
self.hand_detection = hand_detection
self.frt = frt
params = dict()
params["model_folder"] = MODEL_FOLDER
params["model_pose"] = "BODY_25"
params["number_people_max"] = number_people_max
if not self.openpose_rendering:
params["render_pose"] = 0
if self.face_detection:
params["face"] = True
params["face_render_threshold"] = self.frt
# if self.hand_detection:
params["hand"] = True
# Starting OpenPose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
self.datum = op.Datum()
def start_openpose():
try:
# Import Openpose (Windows/Ubuntu/OSX)
dir_path = os.path.dirname(os.path.realpath(__file__))
try:
# Windows Import
if platform == "win32":
# Change these variables to point to the correct folder (Release/x64 etc.)
sys.path.append(dir_path + '/../../python/openpose/Release')
os.environ['PATH'] = os.environ[
'PATH'] + ';' + dir_path + '/../../x64/Release;' + dir_path + '/../../bin;'
import pyopenpose as op
else:
# Change these variables to point to the correct folder (Release/x64 etc.)
sys.path.append('/home/natalia/openpose/build/python');
from openpose import pyopenpose as op
except ImportError as e:
print(
'Error: OpenPose library could not be found. Did you enable `BUILD_PYTHON` in CMake and have this Python script in the right folder?')
raise e
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = "/home/natalia/openpose/models"
# params["write_json"] = json_dir
params["hand"] = True
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
return op, opWrapper
except Exception as e:
print(e)
sys.exit(-1)
def set_env(self):
dir_path = r"/mnt/openpose/openpose/build"
try:
# Windows Import
if platform == "win32":
# Change these variables to point to the correct folder (Release/x64 etc.)
sys.path.append(
r"E:\GitHub\openpose\build\python\openpose\Release")
os.environ['PATH'] = os.environ[
'PATH'] + ';' + "E:\\GitHub\\openpose\\build\\x64\\Release;" + 'E:\\GitHub\\openpose\\build\\bin;'
import pyopenpose as op
else:
# Change these variables to point to the correct folder (Release/x64 etc.)
#sys.path.append('D:\\Anaconda\\python');
# If you run `make install` (default path is `/usr/local/python` for Ubuntu), you can also access the OpenPose/python module from there. This will install OpenPose and the python library at your desired installation path. Ensure that this is in your python path in order to use it.
sys.path.append('/usr/local/python')
from openpose import pyopenpose as op
except ImportError as e:
print(
'Error: OpenPose library could not be found. Did you enable `BUILD_PYTHON` in CMake and have this Python script in the right folder?'
)
raise e
params = dict()
params["model_folder"] = "/mnt/openpose/openpose/models"
params['disable_blending'] = False
# Starting OpenPose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
self.datum = op.Datum()
def exec(self):
"""Process the input video using the OpenPose library."""
# We moved import statement here to use preprocessed data without existing OpenPose.
try:
# Windows Import
if platform == "win32":
# Change these variables to point to the correct folder (Release/x64 etc.)
sys.path.append(dir_path + '/../../python/openpose/Release')
os.environ['PATH'] = os.environ[
'PATH'] + ';' + dir_path + '/../../x64/Release;' + dir_path + '/../../bin;'
import pyopenpose as op
else:
# Change these variables to point to the correct folder (Release/x64 etc.)
sys.path.append('../../python')
# If you run `make install` (default path is `/usr/local/python` for Ubuntu), you can also access
# the OpenPose/python module from there. This will install OpenPose and the python library at your
# desired installation path. Ensure that this is in your python path in order to use it.
# sys.path.append('/usr/local/python')
from openpose import pyopenpose as op
except ImportError as e:
print(
'Error: OpenPose library could not be found. Did you enable `BUILD_PYTHON`'
' in CMake and have this Python script in the right folder?')
raise e
params = dict()
params["model_folder"] = "models/"
params['number_people_max'] = 1
params['render_pose'] = 0
op_wrapper = op.WrapperPython()
op_wrapper.configure(params)
op_wrapper.start()
self.video_processor.process_video_with_net(op_wrapper)
def get_keypoints(filename):
params = dict()
params["model_folder"] = "/home/ubuntu/openpose/models"
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
datum = op.Datum()
imageToProcess = cv2.imread(filename)
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
keypoints = datum.poseKeypoints[0]
filename_annotated = filename + "_annotated.jpg"
cv2.imwrite(filename_annotated, datum.cvOutputData)
xi = keypoints[:, 0]
yi = keypoints[:, 1]
opWrapper.stop()
#xi, yi, c = np.loadtxt(filename).T
x_test = (np.hstack((xi, yi)) / max(np.hstack((xi, yi))))
x_new_test = np.zeros(x_test.shape[0] + 1)
x_new_test[:-1] = x_test
x_new_test[-1] = (x_test[14] - x_test[11]) / (x_test[5] - x_test[2])
x_new_test[np.isinf(x_new_test)] = 0.0
#return x_new_test,filename_annotated
return x_test, filename_annotated
def main():
try:
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# Read frames on directory
imagePaths = op.get_images_on_directory(args[0].image_dir)
start = time.time()
# Process and display images
for imagePath in imagePaths:
datum = op.Datum()
imageToProcess = cv2.imread(imagePath)
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
print("Body keypoints: \n" + str(datum.poseKeypoints))
#cv2.imshow("OpenPose 1.4.0 - Tutorial Python API", datum.cvOutputData)
cv2.imwrite("/home/lburget/Pictures/Webcam/test.jpg",
datum.cvOutputData)
end = time.time()
print("OpenPose demo successfully finished. Total time: " +
str(end - start) + " seconds")
except Exception as e:
print(e)
def __init__(self, thresh=0.1, visualize=False):
params = dict()
params['model_pose'] = 'MPI'
params['model_folder'] = "/home/user/kji/openpose_model/"
self.openpose = op.WrapperPython()
self.openpose.configure(params)
self.openpose.start()
self.thresh = thresh
self.visualize = visualize
# MPI model
self.body_dict = {
"Head": 0,
"Neck": 1,
"RShoulder": 2,
"RElbow": 3,
"RWrist": 4,
"LShoulder": 5,
"LElbow": 6,
"LWrist": 7,
"RHip": 8,
"RKnee": 9,
"RAnkle": 10,
"LHip": 11,
"LKnee": 12,
"LAnkle": 13,
"Chest": 14,
"Background": 15
}
return
def get_sample_heatmaps():
# These parameters are globally set. You need to unset variables set here if you have a new OpenPose object. See *
params = dict()
params["model_folder"] = "../../../models/"
params["heatmaps_add_parts"] = True
params["heatmaps_add_bkg"] = True
params["heatmaps_add_PAFs"] = True
params["heatmaps_scale"] = 3
params["upsampling_ratio"] = 1
params["body"] = 1
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# Process Image and get heatmap
datum = op.Datum()
imageToProcess = cv2.imread(args[0].image_path)
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
poseHeatMaps = datum.poseHeatMaps.copy()
opWrapper.stop()
return poseHeatMaps
def pose_detection():
dir_path = os.path.dirname(os.path.realpath(__file__))
sys.path.append(dir_path + '/python/openpose/Release')
os.environ['PATH'] = os.environ[
'PATH'] + ';' + dir_path + '/x64/Release;' + dir_path + '/bin;'
import pyopenpose as op
params = dict()
params["model_folder"] = "./models/"
img_path = './media/COCO_val2014_000000000474.jpg'
try:
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
datum = op.Datum()
imageToProcess = cv2.imread(img_path)
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
points = datum.poseKeypoints
#cv2.imshow("Pose", datum.cvOutputData)
#cv2.waitKey(0)
except Exception as e:
sys.exit(-1)
return points
def __init__(self):
params = dict()
params[
"model_folder"] = "/home/mghuang/gastronomy_web_cam_analysis/openpose/models/"
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
def main(session):
# Nao
motion_service = session.service("ALMotion")
posture_service = session.service("ALRobotPosture")
motion_service.wakeUp()
# posture_service.goToPosture("StandInit", 0.5)
params = dict()
params[
"model_folder"] = "/home/anton/Documents/hci-project/openpose/models"
# params["model_pose"] = "COCO"
params["net_resolution"] = "160x80"
params["body"] = 1
params["display"] = 1
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# Process Videao
datum = op.Datum()
cam = cv2.VideoCapture(0) # modify here for camera number
while (cv2.waitKey(1) != 27):
# Get camera frame
ret, frame = cam.read()
datum.cvInputData = frame
opWrapper.emplaceAndPop([datum])
frame = datum.cvOutputData
cv2.imshow("Webcam", frame) # datum.cvOutputData)
leftRight, theta, phi = [], [], []
userArmArticular(motion_service)
# Always clean up
cam.release()
cv2.destroyAllWindows()
def __init__(self):
self.model = load_model(
'/home/cornell.edu/nst45/hanabi_project/Hanabi/vision/gesture/gesture_data/pointing.h5'
)
self.params = dict()
self.params[
"model_folder"] = "/home/cornell.edu/nst45/hanabi_project/openpose/models/"
self.params["hand"] = True
# Starting OpenPose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(self.params)
self.opWrapper.start()
self.datum = op.Datum()
self.cap = cv2.VideoCapture(0)
self.timing = False
self.noposeTiming = False
self.nopose = False
self.noposeStart = time.time()
self.curpose = -1
self.start_time = time.time()
self.indices = []
def create_openpose_instance(model_dir):
"""
creating openpose instance
"""
print("creating instance")
try:
params = dict()
params["logging_level"] = 3
params["output_resolution"] = "-1x-1"
params["net_resolution"] = "-1x368"
params["model_pose"] = "BODY_25"
params["alpha_pose"] = 0.6
params["scale_gap"] = 0.3
params["scale_number"] = 1
params["render_threshold"] = 0.05
# If GPU version is built, and multiple GPUs are available, set the ID here
params["num_gpu_start"] = 0
params["disable_blending"] = False
# Ensure you point to the correct path where models are located
params["model_folder"] = model_dir
# Construct OpenPose object allocates GPU memory
openpose = op.WrapperPython()
openpose.configure(params)
openpose.start()
return openpose
except Exception as err:
print(err)
print(type(err))
raise err
def __init__(self, debug=False):
#from openpose import *
params = dict()
params["model_folder"] = Constants.openpose_modelfolder
params["net_resolution"] = "-1x320"
self.openpose = op.WrapperPython()
self.openpose.configure(params)
self.openpose.start()
max_cosine_distance = Constants.max_cosine_distance
nn_budget = Constants.nn_budget
self.nms_max_overlap = Constants.nms_max_overlap
max_age = Constants.max_age
n_init = Constants.n_init
model_filename = 'model_data/mars-small128.pb'
self.encoder = gdet.create_box_encoder(model_filename, batch_size=1)
metric = nn_matching.NearestNeighborDistanceMetric(
"cosine", max_cosine_distance, nn_budget)
self.tracker = DeepTracker(metric, max_age=max_age, n_init=n_init)
# self.capture = cv2.VideoCapture('D:/walk_tour-edit.mp4')
self.capture = cv2.VideoCapture('D:/walk_tour.mp4')
if self.capture.isOpened(): # Checks the stream
self.frameSize = (int(self.capture.get(cv2.CAP_PROP_FRAME_HEIGHT)),
int(self.capture.get(cv2.CAP_PROP_FRAME_WIDTH)))
Constants.SCREEN_HEIGHT = self.frameSize[0]
Constants.SCREEN_WIDTH = self.frameSize[1]
self.cnt = 1
def __init__(self, event, progress, gui):
threading.Thread.__init__(self)
self.stopped = event
self.progress = progress
self.data = (gui.open_data, gui.closed_data)
self.length = len(self.data[0]) + len(self.data[1])
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
if platform == 'win32':
self.writer_open = cv2.VideoWriter(
'output/processed_output_open_eyes.mp4', fourcc, 30,
(gui.vid_width, gui.vid_height))
self.writer_closed = cv2.VideoWriter(
'output/processed_output_closed_eyes.mp4', fourcc, 30,
(gui.vid_width, gui.vid_height))
# OpenPose setup
params = dict()
params['model_folder'] = 'openpose/models/'
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
self.datum = op.Datum()
else:
self.writer_open = cv2.VideoWriter('output/output_open_eyes.mp4',
fourcc, 30,
(gui.vid_width, gui.vid_height))
self.writer_closed = cv2.VideoWriter(
'output/output_closed_eyes.mp4', fourcc, 30,
(gui.vid_width, gui.vid_height))
def __init__(self):
parser = argparse.ArgumentParser()
#parser.add_argument("--image_path", default="./media/COCO_val2014_000000000192.jpg", help="Process an image. Read all standard formats (jpg, png, bmp, etc.).")
args = parser.parse_known_args()
params = dict()
params["model_folder"] = './../models/' # 具体情况
params["number_people_max"] = 1
params["model_pose"] = "BODY_25"
# Add others in path?
for i in range(0, len(args[1])):
curr_item = args[1][i]
if i != len(args[1]) - 1:
next_item = args[1][i + 1]
else:
next_item = "1"
if "--" in curr_item and "--" in next_item:
key = curr_item.replace('-', '')
if key not in params:
params[key] = "1"
elif "--" in curr_item and "--" not in next_item:
key = curr_item.replace('-', '')
if key not in params:
params[key] = next_item
# 初始化openpose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
self.datum = op.Datum()
def openpose_init():
try:
if platform == "win32":
sys.path.append('./OpenPose/Release')
import pyopenpose as op
else:
sys.path.append('./OpenPose')
from Release import pyopenpose as op
except ImportError as e:
print(
'Error: OpenPose library could not be found. Did you enable `BUILD_PYTHON` in CMake and have this Python script in the right folder?'
)
raise e
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = "./OpenPose/models"
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# Process Image
datum = op.Datum()
return datum, opWrapper
def __init__(self):
self.onoff = False
self.channel = [1,2,4,5,6,7,8,9]
self.now = 0
self.vol = 10
self.volcon = 0
self.range = 0
self.params = dict()
self.params["model_folder"] = "../../../models/"
self.params["hand"] = True
# Starting OpenPose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(self.params)
self.opWrapper.start()
self.cap = cv2.VideoCapture(0) #0だったり1だったり
self.cap.set(3,1920)
self.cap.set(4,1080)
self.before_form = []
self.current_form = []
self.counter = 0
pyxel.init(60, 45)
pyxel.run(self.update,self.draw)
def openPose(img, gamma=1.0, ui=False):
params = dict()
model_folder = ('' if ui else '../') + 'models'
params["model_folder"] = model_folder
params["number_people_max"] = 1
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
datum = op.Datum()
# hyunho gamma
if gamma != 1.0:
img2 = adjust_gamma(img, gamma=gamma)
datum.cvInputData = img2
else:
datum.cvInputData = img
opWrapper.emplaceAndPop([datum])
mydata = datum.poseKeypoints[0]
joints = np.zeros((14, 2))
conf = np.zeros(14)
joints[0] = mydata[11, :2]
joints[1] = mydata[10, :2]
joints[2] = mydata[9, :2]
joints[3] = mydata[12, :2]
joints[4] = mydata[13, :2]
joints[5] = mydata[14, :2]
joints[6] = mydata[4, :2]
joints[7] = mydata[3, :2]
joints[8] = mydata[2, :2]
joints[9] = mydata[5, :2]
joints[10] = mydata[6, :2]
joints[11] = mydata[7, :2]
joints[12] = mydata[1, :2]
joints[13] = mydata[0, :2]
conf[0] = mydata[11, 2]
conf[1] = mydata[10, 2]
conf[2] = mydata[9, 2]
conf[3] = mydata[12, 2]
conf[4] = mydata[13, 2]
conf[5] = mydata[14, 2]
conf[6] = mydata[4, 2]
conf[7] = mydata[3, 2]
conf[8] = mydata[2, 2]
conf[9] = mydata[5, 2]
conf[10] = mydata[6, 2]
conf[11] = mydata[7, 2]
conf[12] = mydata[1, 2]
conf[13] = mydata[0, 2]
# head joint estimate
# joints[13] += 0.5 * (joints[13] - joints[12])
return joints, conf
def __init__(self, net_resolution="320x160"):
params = dict()
params["model_folder"] = "openpose/models/"
params["net_resolution"] = net_resolution
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
def __init__(self, model_folder="/openpose/models/", **kwargs):
print("initializing poser")
params = dict()
params["model_folder"] = model_folder
params.update(kwargs)
self._opWrapper = op.WrapperPython()
self._opWrapper.configure(params)
self._opWrapper.start()
def __init__(self):
params = dict()
params["model_folder"] = "models/"
params["hand"] = True
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
self.datum = op.Datum()
def start(self):
self.params["face"] = True
self.params["hand"] = True
self.add_path()
pprint.pprint(self.params)
opWrapper = op.WrapperPython(3)
opWrapper.configure(self.params)
opWrapper.execute()
def __initOpenPose(self, opParams):
# starting OpenPose
if not opParams:
opParams = dict()
opParams["model_folder"] = "../../externals/openpose/models/"
opParams["render_threshold"] = c.keypointThreshold
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(opParams)
self.opWrapper.start()
def __init__(self, path: str, webcam_mode: bool = False):
parser = argparse.ArgumentParser()
parser.add_argument("--no_display", default=False)
parser.add_argument("--model_pose",
action='store',
type=str,
default="BODY_25")
parser.add_argument("--tracking", action='store', type=int, default=1)
parser.add_argument("--number_people_max",
action='store',
type=int,
default=1)
params = dict()
params["model_folder"] = "models/"
params["net_resolution"] = "320x176"
params["face_net_resolution"] = "320x320"
params["render_pose"] = "1"
params["model_pose"] = "BODY_25"
params["tracking"] = "5"
params["number_people_max"] = "1"
args = parser.parse_known_args()
#parse command line argument
# Add others in path?
for i in range(0, len(args[1])):
curr_item = args[1][i]
if i != len(args[1]) - 1: next_item = args[1][i + 1]
else: next_item = "1"
if "--" in curr_item and "--" in next_item:
key = curr_item.replace('-', '')
params[key] = "1"
elif "--" in curr_item and "--" not in next_item:
key = curr_item.replace('-', '')
params[key] = next_item
#Start OpenPose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
#Add image path here
#Video path
#path = dir_path + '\\test_data\\test.mkv'
# Image Path
media_path = dir_path + path
if webcam_mode is True:
self.cap = cv2.VideoCapture(0)
else:
#Capture from path
self.cap = cv2.VideoCapture(media_path)
if (self.cap.isOpened() == False):
print("Error opening Video: ", path)
def initOpenPose():
# starting OpenPose
params = dict()
params["model_folder"] = "../../externals/openpose/models/"
params["render_threshold"] = c.keypointThreshold
getOpenPoseArgs(params)
wrapper = op.WrapperPython()
wrapper.configure(params)
wrapper.start()
return wrapper
def set_params():
params = dict()
params['model_folder'] = 'mod_code/openpose/models'
params['model_pose'] = 'BODY_25'
params['number_people_max'] = 1
params["net_resolution"] = '128x192'
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
def set_params():
params = dict()
params["model_folder"] = "openpose/models/"
params["face"] = True
params["hand"] = True
params["disable_blending"] = False
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
return opWrapper
def openpose_demo(canvas):
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = "../../../models/"
params["hand"] = True
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
cap = cv2.VideoCapture(0)
before_form = []
current_form = []
counter = 0
global rootFlag
while (True):
ret, frame = cap.read()
# Process Image
datum = op.Datum()
imageToProcess = frame
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
cv2.imshow("OpenPose 1.5.0 - Tutorial Python API", datum.cvOutputData)
#print(datum.handKeypoints[1][0])
right_hand, flag = hm.is_hand_recog(datum.handKeypoints[1][0])
if flag == True:
current_form = hm.check_handform2(right_hand)
#print(current_form,counter)
if current_form == before_form: #1フレーム前の形と現在の形を比較する
counter = counter + 1 #同じだったらカウントを１増やす
if (counter == 10): #カウントが10になったら（10回連続して同じ形を認識したら）
canvas.delete("all")
n = hm.list_to_num(current_form) #手の形から番号を決定
try:
canvas.create_text(300, 300, text=n, font=('', 350))
except Exception as e:
break
else:
counter = 0 #違ったらカウントをリセットする
before_form = current_form
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if rootFlag == False:
break
cap.release()
cv2.destroyAllWindows()
def __init__(self, model_path="./models/"):
# load models
params = dict()
params["model_folder"] = model_path
print("[*] success loading model from", model_path)
# Starting OpenPose
self.opWrapper = op.WrapperPython()
self.opWrapper.configure(params)
self.opWrapper.start()
print("[*] openpose start!")
