def plot_encoded_gestures():
dataset = OpportunityDatasetEncoded()
templates, labels = dataset.load_isolated_dataset()
templates = [templates[t] for t in np.where(labels > 0)[0]]
labels = labels[np.where(labels > 0)[0]]
plot_creator.plot_gestures(templates, labels)
plt.show()
def plot_isolate_gestures(plot=True, save=False):
dataset = HCIGuided()
if plot:
templates, labels = dataset.load_isolated_dataset()
labels = np.array(labels)
templates = [templates[t] for t in np.where(labels > 0)[0]]
labels = labels[np.where(labels > 0)[0]]
plot_creator.plot_gestures(templates, labels)
plt.show()
def plot_isolate_gestures(sensor_no=67, annotation_column=249):
dataset = OpportunityDataset()
data = dataset.load_data()
stream_labels = data[:, annotation_column]
tmp_data = data[:, sensor_no]
templates, labels = Dataset.segment_data(tmp_data, stream_labels)
labels = np.array(labels)
templates = [templates[t] for t in np.where(labels > 0)[0]]
labels = labels[np.where(labels > 0)[0]]
plot_creator.plot_gestures(templates, labels)
plt.show()
def plot_isolate_gestures():
dataset = WetlabDataset()
data = dataset.load_data()
timestamps = data[:, 0]
stream_labels = data[:, -1]
tmp_data = np.sqrt(data[:, 1]**2 + data[:, 2]**2 + data[:, 3]**2)
# tmp_data = data[:, 2]
templates, labels = Dataset.segment_data(tmp_data, stream_labels)
labels = np.array(labels)
templates = [templates[t] for t in np.where(labels > 0)[0]]
labels = labels[np.where(labels > 0)[0]]
plot_creator.plot_gestures(templates, labels)
# subplt_1.plot(timestamps, data[:, sensor_no], linewidth=0.5)
# subplt_2.plot(timestamps, data[:, 249], '.')
plt.show()
import matplotlib.pyplot as plt
from data_processing import data_loader as dl
from utils.plots import plot_creator as plt_creator
if __name__ == '__main__':
plot_choice = 41
input_file = "/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/beachvolleyball_encoded/variable_templates/zeus_templates_2021-01-20_16-37-08"
dataset_choice = 'beachvolleyball_encoded'
classes = [1001, 1002, 1003, 1004]
if plot_choice == 0:
templates, streams, streams_labels = dl.load_training_dataset(
dataset_choice, classes=classes, use_quick_loader=True)
plt_creator.plot_gestures(streams, streams_labels, classes=classes)
elif plot_choice == 1:
data = dl.load_continuous_dataset(dataset_choice)
plt_creator.plot_continuous_data(data, classes=classes)
elif plot_choice == 2:
input_files = [
"/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/hci_guided/params/zeus_param_thres_2020-08-10_15-14-30"
]
plt_creator.plot_gascores(input_files)
elif plot_choice == 21:
# input_files = [
# '/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/hci_guided/params/poseidon_param_thres_2020-08-19_14-51-38',
# '/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/hci_guided/params/poseidon_param_thres_2020-08-19_14-57-07',
# '/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/hci_guided/params/poseidon_param_thres_2020-08-19_15-02-46',
# '/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/hci_guided/params/poseidon_param_thres_2020-08-19_15-12-43',
# '/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/hci_guided/params/poseidon_param_thres_2020-08-19_15-19-31']
input_files = [
"/home/mathias/Documents/Academic/PhD/Research/WLCSSTraining/training/cuda/opportunity_encoded/params_perclass/poseidon_param_thres_2020-12-08_18-57-59",
def plot_isolate_gestures():
dataset = SkodaMini()
templates, labels = dataset.load_isolated_from_mat()
plot_creator.plot_gestures(templates, labels)
plt.show()
def plot_isolated_gestures():
dataset = BeachVolleyball()
templates, labels = dataset.load_isolated_dataset()
plot_creator.plot_gestures(templates, labels)
plt.show()
def plot_isolated_gestures_quick_loader():
dataset = HCITable()
templates, streams, labels = dataset.quick_load_training_dataset()
plot_creator.plot_gestures(streams, labels)
plt.show()
def plot_isolate_gestures(plot=True, save=False):
dataset = HCITable()
streams, labels = dataset.load_isolated_dataset()
plot_creator.plot_gestures(streams, labels)
plt.show()
def plot_isolated_gestures(plot_null=False):
dataset = UWaveGestureLibraryX()
templates, labels = dataset.load_isolated_dataset()
plot_creator.plot_gestures(templates, labels)
plt.show()
def plot_isolated_gestures():
dataset = SHLPreview()
streams, labels = dataset.load_isolated_dataset()
plot_creator.plot_gestures(streams, labels)
plt.show()
def plot_isolate_gestures():
dataset = UTDMhad()
templates, labels = dataset.load_isolated_dataset()
plot_creator.plot_gestures(templates, labels)
plt.show()