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data_pardigm.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 21 17:40:06 2019
@author: manoj
"""
from voc_loader import VOC
def train_test_full():
num_classes = 21 # 20 classes + background for VOC
classes = list(range(0,21))
print ("{} classes: {}".format(num_classes,classes))
dataset = VOC('07', 'edgeboxes', 'trainval')
dataset_test = VOC('07', 'edgeboxes', 'test')
print('data prepared, train data: {}'.format(len(dataset)))
print('data prepared, test data: {}'.format(len(dataset_test)))
yield num_classes, dataset, dataset_test
def train_test_half():
num_classes = 11 # first 10 classes + background for VOC
included = [1,2,3,4,5,6,7,8,9,10]
print ("{} classes: {}".format(num_classes,included))
dataset = VOC('07', 'edgeboxes', 'trainval',included=included)
dataset_test = VOC('07', 'edgeboxes', 'test',included=included)
print('data prepared, train data: {}'.format(len(dataset)))
print('data prepared, test data: {}'.format(len(dataset_test)))
yield num_classes, dataset, dataset_test
def half_batch():
classes = [[0,1,2,3,4,5,6,7,8,9,10]] + [list(range(11,21))]
included = []
num_classes = 0
for c in classes:
included += c
num_classes = len(included)
print ("{} classes: {}".format(num_classes,c))
dataset = VOC('07', 'edgeboxes', 'trainval',included=c)
dataset_test = VOC('07', 'edgeboxes', 'test',included=included)
print('data prepared, train data: {}'.format(len(dataset)))
print('data prepared, test data: {}'.format(len(dataset_test)))
yield num_classes, dataset, dataset_test
def half_offlines():
classes = [ list(range(0,11))] + [[i] for i in range(11,21)]
included = []
num_classes = 0
for c in classes:
included += c
num_classes = len(included)
print ("{} classes: {}".format(num_classes,included))
dataset = VOC('07', 'edgeboxes', 'trainval',included = included)
dataset_test = VOC('07', 'edgeboxes', 'test',included = included)
print('data prepared, train data: {}'.format(len(dataset)))
print('data prepared, test data: {}'.format(len(dataset_test)))
yield num_classes, dataset, dataset_test
def half_incr():
classes = [ list(range(0,11))] + [[i] for i in range(11,21)]
included = []
num_classes = 0
for c in classes:
included += c
num_classes = len(included)
print ("{} classes: {}".format(num_classes,c))
dataset = VOC('07', 'edgeboxes', 'trainval',included=c)
dataset_test = VOC('07', 'edgeboxes', 'test',included=included)
print('data prepared, train data: {}'.format(len(dataset)))
print('data prepared, test data: {}'.format(len(dataset_test)))
yield num_classes, dataset, dataset_test
data_dict = {}
data_dict['full_voc'] = train_test_full
data_dict['half_voc'] = train_test_half
data_dict['half_offlines'] = half_offlines
data_dict['half_finteune'] = half_offlines
data_dict['halfbatch_voc'] = half_batch
data_dict['incr_voc'] = half_incr