def add_xml_book_data_to_json(book_code, json_obj):
json_data = json_utils.read_json_file(const.JSON_PATH)
books = json_data['books']
if book_code in books.keys():
books[book_code].append(json_obj)
else:
books[book_code] = [json_obj]
json_data['books'] = books
json_utils.write_json_file(const.JSON_PATH, json_data)
def add_xml_book_data_to_json(book_code, json_obj):
json_data = json_utils.read_json_file(const.JSON_PATH)
books = json_data['books']
if book_code in books.keys():
books[book_code].append(json_obj)
else:
books[book_code] = [json_obj]
json_data['books'] = books
json_utils.write_json_file(const.JSON_PATH, json_data)
print(const.BLUE, 'Added XML Book Entry to JSON', const.END)
def test_detect_metrics():
tps, fns, fps = 0, 0, 0
for img_path in glob(test_folder + "/*.jpg"):
json_path = str(img_path)[:-3] + "json"
img = cv2.imread(str(img_path))
results = engine.diff_areas(img)
predictions = [item['bbox'] for item in results]
ground_truths = get_bbox_from_json(read_json_file(json_path))
tp, fn, fp = get_metrics(predictions, ground_truths, iou_thres=0.3)
tps += tp
fns += fn
fps += fp
precision = tps / (tps + fps)
recall = tps / (tps + fns)
f1_score = 2 * precision * recall / (precision + recall)
print(
f"precision: {precision:.4f}, recall: {recall:.4f}, f1_score: {f1_score:.4f}"
)
def validate_all_xml_files():
json_data = json_utils.read_json_file(const.JSON_PATH)
book_schema = get_book_schema(const.XSD_PATH)
books_json = json_data['books']
for book_code in books_json.keys():
books_list = books_json[book_code]
for book in books_list:
if book['is_validated']:
print(const.BLUE, 'Book : ', book['xml_file'], ' is valid',
const.END)
continue
else:
if 'xml_file_path' in book:
result = book_schema.is_valid(book['xml_file_path'])
print('Validating Book : ', book['xml_file'], ' -> ',
result)
book['is_validated'] = result
json_data['books'] = books_json
json_utils.write_json_file(const.JSON_PATH, json_data)
def save_validated_files_to_db():
json_data = json_utils.read_json_file(const.JSON_PATH)
books_json = json_data['books']
for book_code in books_json.keys():
books_list = books_json[book_code]
for book in books_list:
if not book['is_validated']:
print(const.WARNING, 'XML File :: ', book['xml_file'], ' is not validated against XSD', const.END)
continue
if not book['is_saved_to_db']:
print(const.BLUE, 'Adding Book Data : ', book['xml_file'], ' to the DB', const.END)
book_dict = read_xml.parse_xml_file(book['xml_file_path'])
result = adb.add_book_to_db(book_code, book_dict)
book['is_saved_to_db'] = result
w_str = const.WARNING
if result:
w_str = const.BLUE
print(w_str, 'Result :: ', result, const.END, '\n')
else:
print(const.BLUE, "Book Data already added to the Database", const.END)
json_data['books'] = books_json
json_utils.write_json_file(const.JSON_PATH, json_data)
import glob
import os
from PIL import Image
from utils.pascal_utils import write_pascal_annotation_aug
from utils.json_utils import read_json_file
data_dir='/media/milton/ssd1/dataset/pedestrian/caltech_pedestrian/caltech-pedestrian-dataset-converter/data'
images_dir=os.path.join(data_dir,'images')
json_file=os.path.join(data_dir,'annotations.json')
data=read_json_file(json_file)
for set_key in data.keys():
set_data=data[set_key]
for v_key in set_data.keys():
frames=set_data[v_key]['frames']
for frame_key in frames.keys():
for frame_anno in frames[frame_key]:
filename="{}_{}_{}.png".format(set_key.lower(),v_key,frame_key)
file_path=os.path.join(images_dir, filename)
# if not os.path.exists(file_path):
# print("{} not found".format(file_path))
try:
img=Image.open(file_path)
except Exception as e:
continue
pass
def show_ground_gt(img, json_path):
json_data = read_json_file(json_path)
bboxes = get_bbox_from_json(json_data)
for bbox in bboxes:
cv2.rectangle(img, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (255, 0, 0),
3)