content: from pycocotools.coco import COCO
  from write_xml import write_to_file
  import numpy as np
  import skimage.io as io
  import matplotlib.pyplot as plt
  import os
  import shutil
  
  dataDir='..'
  dataType='val2014'
  annFile='%s/annotations/instances_%s.json'%(dataDir,dataType)
  
  coco=COCO(annFile)	# load database
  cats=coco.loadCats(coco.getCatIds())
  print cats
  
  foodCategory = []
  foodCategoryId = []
  foodImageId = []
  
  for cat in cats:
  	if cat['supercategory'] == 'food':
  		foodCategory.append(cat['name'])
  		print cat['name']
  
  foodCategoryId = coco.getCatIds(foodCategory)
  foodImageId = coco.getImgIds(catIds=foodCategoryId) #must add catIds=
  #print len(foodImageId)
  
  dstdir = './JPEGImages/'
  
  # Get all food images and copy them to JPEGImages folders.(#JPEGImage#)
  for cat in range(0, len(foodImageId)):
  	img = coco.loadImgs(foodImageId[cat])[0]
  	img_name = '%s/images/%s/%s'%(dataDir,dataType,img['file_name'])
  	#print img_name
  	shutil.copy(img_name, dstdir)
  
  
  # Generate the SegmentationObject/SegmentationClass (#Segmentation#)
  dstdir = './SegmentationClass'
  dstdir_2 = './SegmentationObject'
  
  # Generate the configuration files for Annotation folders(#Annotation#)
  # Move to the above the share the loop of image_names.
  for cat in range(0, len(foodImageId)):
  	img = coco.loadImgs(foodImageId[cat])[0]
  	img_name = os.path.splitext(img['file_name'])[0]
  	img_annotation_xml_name ='./Annotations/%s.xml'%(img_name)
  	img_annotation_jpg_name ='./JPEGImages/%s.jpg'%(img_name)
  #	print img_annotation_xml_name
  	file = open(img_annotation_xml_name, "wb")
  	# def write_to_file(img_name,food_type, file_name, img_width, img_height,left_x, left_y, right_x, right_y):
  	img_width = img['width']
  	img_height = img['height']
  	
  	## Now load annotation in order to get bbox, food type
  	ann_id = coco.getAnnIds(imgIds=img['id'])
  	print "ann_id" 
  	print ann_id
  	
  	## Note: for one image, there are multiple labels, find the food_label
  	ann = coco.loadAnns(ann_id)
  
  	for ann_food in ann:
  		ann_cat_id = ann_food['category_id']
  		ann_cat = coco.loadCats(ann_cat_id)[0]
  		if ann_cat['supercategory'] == 'food':
  			print ann_cat['name']	
  			food_ann = ann_food
  			break
  	
  	print "annotation"
  	print ann_food
  	bbox = ann_food['bbox']
  	catId = ann_food['category_id']
  	cat = coco.loadCats(catId)[0]
  	left_x = bbox[0]
  	left_y = bbox[1]
  	right_x = left_x + bbox[2]
  	right_y = left_y + bbox[3]
  	food_type = cat['name']
  
  
  	print img_annotation_jpg_name
  
  	if food_type == 'donut':
  		shutil.copy(img_annotation_jpg_name, "./donut/")
  	elif food_type == 'cake':
  		shutil.copy(img_annotation_jpg_name, "./cake/")
  	elif food_type == 'hot dog':
  		shutil.copy(img_annotation_jpg_name, "./hotdog/")
  	elif food_type == 'sandwich':
  		shutil.copy(img_annotation_jpg_name, "./sandwich/")
  	elif food_type == 'carrot':
  		shutil.copy(img_annotation_jpg_name, "./carrot/")
  	elif food_type == 'apple':
  		shutil.copy(img_annotation_jpg_name, "./apple/")
  	elif food_type == 'orange':
  		shutil.copy(img_annotation_jpg_name, "./orange/")
  	elif food_type == 'banana':
  		shutil.copy(img_annotation_jpg_name, "./banana/")
  	elif food_type == 'pizza':
  		shutil.copy(img_annotation_jpg_name, "./pizza/")
  
   	write_to_file(img_annotation_jpg_name, food_type, img_annotation_xml_name, str(img_width), str(img_height), str(left_x), str(left_y), str(right_x), str(right_y))
  	file.close()
  
  ### ?????? 
  
  # Generat the configuration for ImageSet
  
  
  img = coco.loadImgs(foodImageId[5])[0]
  img_name = '%s/images/%s/%s'%(dataDir,dataType,img['file_name'])
  I = io.imread(img_name)
  #plt.figure()
  #plt.imshow(I)
  #plt.show()
  
  # JUST FOR DEBUGGING
  print foodCategory
  print foodCategoryId	
  print foodImageId
  print img_name
  