boxp = 0.2 f_loss = False minL = False print('boxp= {}\n pre_model= {}\n config= {}\n focal_loss={}\n minL={}\n '. format(boxp, model_n, conf, f_loss, minL)) params = process_config(conf) print('--Creating Dataset') dataset = DataGenerator(minL, boxp, params['joint_list'], params['img_directory'], params['training_txt_file'], remove_joints=params['remove_joints']) dataset._create_train_table() dataset._create_val_table() dataset._randomize() dataset._create_sets() config = tf.ConfigProto(allow_soft_placement=True) config.gpu_options.allow_growth = True modif = True model = HourglassModel(f_loss=f_loss, nFeat=params['nfeats'], nStack=params['nstacks'], nModules=params['nmodules'], nLow=params['nlow'], outputDim=params['num_joints'], batch_size=params['batch_size'], attention=params['mcam'],