def set_params(face=False,
body=1,
hand=True,
hand_detector=0,
hand_opti=False,
write_json="",
nb_people_max=1,
num_gpu=0,
model_folder='/home/conte/openpose/models',
tracking=-1):
"""
face : bool, calcul des keypoints du visage
body : int, calcul des keypoints du corps
hand : bool, calcul des keypoints des mains
hand_detector : int, Select 0 to select OpenPose body detector (most accurate
one and fastest one if body is enabled), 2 to indicate that it will be
provided by the user, 3 to also apply hand tracking (only for hand)
hand_opti : bool, paramètres optimaux pour l'efficacité, perte de rapidité
write_json : str, endroit où enregistrer fichiers JSON des keypoints, ""
pour ne pas enregistrer
nb_people_max : int, nombre de personne max à chercher sur la frame/photo
num_gpu : int, si l'on souhaite travailler manuellement sur les gpu, 0
pour ne pas s'en préoccuper
"""
params = dict()
params["model_folder"] = model_folder
# Noyau plante si face = True
params["face"] = face
params["hand"] = hand
params["hand_detector"] = hand_detector
params["body"] = body
# On fixe le nombre de personne
params["number_people_max"] = nb_people_max
# Best results found with 6 scales
# --hand_scale_number 6 --hand_scale_range 0.4
if hand_opti:
params["hand_scale_number"] = 6
#params["hand_scale_range"] = float(0.4)
# Save results in JSON format
if write_json:
params["write_json"] = write_json
if num_gpu:
params["num_gpu"] = int(op.get_gpu_number())
params["tracking"] = tracking
# Pour calcul multi-GPU :
# https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/examples/tutorial_api_python/05_keypoints_from_images_multi_gpu.py
return params
)
raise e
# Flags
parser = argparse.ArgumentParser()
parser.add_argument(
"--image_dir",
default="../examples/media/",
help=
"Process a directory of images. Read all standard formats (jpg, png, bmp, etc.)."
)
parser.add_argument("--no_display",
default=False,
help="Enable to disable the visual display.")
parser.add_argument("--num_gpu",
default=op.get_gpu_number(),
help="Number of GPUs.")
args = parser.parse_known_args()
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = "../models/"
params["num_gpu"] = int(vars(args[0])["num_gpu"])
numberGPUs = int(params["num_gpu"])
# 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:
if key not in params: params[key] = next_item
# Construct it from system arguments
# op.init_argv(args[1])
# oppython = op.OpenposePython()
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# Read frames on directory
imagePaths = op.get_images_on_directory(args[0].image_dir)
# Read number of GPUs in your system
numberGPUs = op.get_gpu_number()
start = time.time()
# Process and display images
for imageBaseId in range(0, len(imagePaths), numberGPUs):
# Create datums
datums = []
# Read and push images into OpenPose wrapper
for gpuId in range(0, numberGPUs):
imageId = imageBaseId + gpuId
if imageId < len(imagePaths):
imagePath = imagePaths[imageBaseId + gpuId]
def num_gpus(self):
"""Return the number of GPUs."""
return pyopenpose.get_gpu_number()
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
# Flags
parser = argparse.ArgumentParser()
parser.add_argument("--image_dir", default="../../../examples/media/", help="Process a directory of images. Read all standard formats (jpg, png, bmp, etc.).")
parser.add_argument("--no_display", default=False, help="Enable to disable the visual display.")
parser.add_argument("--num_gpu", default=op.get_gpu_number(), help="Number of GPUs.")
args = parser.parse_known_args()
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = dict()
params["model_folder"] = "../../../models/"
params["num_gpu"] = int(vars(args[0])["num_gpu"])
numberGPUs = int(params["num_gpu"])
# 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('-','')