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import json
import os
import random
import shutil
images_path = '/Users/ryo/Desktop/test_annotations/raccoon_dataset-master/images';
coco_json_path = '/Users/ryo/Desktop/test_annotations/raccoon_dataset-master/annotations.json'
sagemaker_json_path = '/Users/ryo/Desktop/test_annotations/raccoon_dataset-master/sagemaker_tmp';
to_be_uploaded_to_s3_path = '/Users/ryo/Desktop/test_annotations/raccoon_dataset-master/sagemaker';
sagemaker_images_path_train = to_be_uploaded_to_s3_path + '/train';
sagemaker_images_path_val = to_be_uploaded_to_s3_path + '/validation';
sagemaker_json_path_train = to_be_uploaded_to_s3_path + '/train_annotation';
sagemaker_json_path_val = to_be_uploaded_to_s3_path + '/validation_annotation';
def makedir(path):
if not os.path.isdir(path):
os.mkdir(path)
makedir(sagemaker_json_path)
makedir(to_be_uploaded_to_s3_path)
makedir(sagemaker_images_path_train)
makedir(sagemaker_images_path_val)
makedir(sagemaker_json_path_train)
makedir(sagemaker_json_path_val)
def fixCategoryId(category_id):
return category_id - 1;
with open(coco_json_path) as f:
js = json.load(f)
images = js['images']
categories = js['categories']
annotations = js['annotations']
for i in images:
jsonFile = i['file_name']
jsonFile = jsonFile.split('.')[0] + '.json'
line = {}
line['file'] = i['file_name']
line['image_size'] = [{
'width': int(i['width']),
'height': int(i['height']),
'depth': 3
}]
line['annotations'] = []
line['categories'] = []
for j in annotations:
if j['image_id'] == i['id'] and len(j['bbox']) > 0:
line['annotations'].append({
'class_id': fixCategoryId(int(j['category_id'])),
'top': int(j['bbox'][1]),
'left': int(j['bbox'][0]),
'width': int(j['bbox'][2]),
'height': int(j['bbox'][3])
})
class_name = ''
for k in categories:
if int(j['category_id']) == k['id']:
class_name = str(k['name'])
assert class_name is not ''
line['categories'].append({
'class_id': fixCategoryId(int(j['category_id'])),
'name': class_name
})
if line['annotations']:
with open(os.path.join(sagemaker_json_path, jsonFile), 'w') as p:
json.dump(line, p)
jsons = os.listdir(sagemaker_json_path)
num_annotated_files = len(jsons)
train_split_pct = 0.90
num_train_jsons = int(num_annotated_files * train_split_pct)
random.seed(0)
random.shuffle(jsons)
train_jsons = jsons[:num_train_jsons]
val_jsons = jsons[num_train_jsons:]
count_train = 0
for i in train_jsons:
file_name = i.split('.')[0]
if len(file_name) == 0:
continue
image_file_path = images_path + '/' + file_name + '.jpg'
shutil.copy(image_file_path, sagemaker_images_path_train)
shutil.copy(sagemaker_json_path + '/'+i, sagemaker_json_path_train)
count_train += 1
count_val = 0
for i in val_jsons:
file_name = i.split('.')[0]
if len(file_name) == 0:
continue
image_file_path = images_path + '/' + file_name + '.jpg'
shutil.copy(image_file_path, sagemaker_images_path_val)
shutil.copy(sagemaker_json_path + '/'+i, sagemaker_json_path_val)
count_val += 1
print ('train_jsons {}'.format(count_train))
print ('val_jsons {}'.format(count_val))