def do_classification(sleep_time, n_classes):
output = classification(G["frame"], sleep_time, n_classes)
np.copyto(G["output_classification"], output)
def process(frame, base_sleep_time, n_classes):
rs1 = segmentation1(frame, base_sleep_time * 0.03)
rs2 = segmentation2(frame, base_sleep_time * 0.04)
rs3 = classification(frame, base_sleep_time * 0.05, n_classes)
return rs1, rs2, rs3
def process(self, x):
return classification(x, self.sleep_time, self.n_classes)
def class_target(x):
return classification(x, 0.05 * g_dict["coef"], g_dict["n_classes"])
def class_target(x):
return classification(x, 0.05 * coef, n_classes)