A package for reading id and name on KTP and SIM
Project description
Indo OCR Army
This is a package for OCR Identity card in Indonesia. This packages build on top of detectron2 so you should install detectron2 first and some requirements need to install separately before you run this packages, for quick tutorial run this:
conda install
for comprehensive use, you can do this:
import os
import cv2
import matplotlib.pyplot as plt
from IndoOCRArmy.modelOCR import defaultConfig, DrawOCR, numericalDetectron2, boundingBoxesDetectron2, alphabeticalDetectron2, easypredict
# load classes
cfg = defaultConfig()
for key in cfg.keys():
if 'list_cuda' in cfg[key]:
cfg[key]['list_cuda'] = [0]
drawer_ocr = DrawOCR(cfg['drawOCR'])
bBoxDet = boundingBoxesDetectron2(cfg['boundingBoxesDetectron2'])
numDet = numericalDetectron2(cfg['numericalDetectron2'])
alphaDet = alphabeticalDetectron2(cfg['alphabeticalDetectron2'])
# load image
image_ktp = cv2.imread("assets/ktp_example.jpg")
image_sim = cv2.imread("assets/sim_example.jpg")
# detect boundingboxes
crops, boxes, labels = bBoxDet.predict(image_ktp, input_type='ktp')
# detect number and alphabet
dict_ID = numDet.predict_ensemble(crops[0])
dict_Name = alphaDet.predict_ensemble(crops[1])
# choose `weighted_hardvote_word` for the best result according to our benchmark
ID = dict_ID.get("weighted_hardvote_word")
Name = dict_Name.get("weighted_hardvote_word")
# parse NIK to get information about : location, gender, and birthdate
parse_NIK = numDet.parse_nik(ID)
# create listdata and listlabel for visualization later
listdata = [ID, Name]
listlabel = [x for x in list(labels.values()) if x is not None]
for label, data in parse_NIK.items():
listdata.append(data)
listlabel.append(label)
print(ID)
print(Name)
drawer_ocr.show_list_images(list_img=crops.values())
For visuzlize comprehensive result, use this:
drawer_ocr.show_desc(image_ktp, boxes, labels, listdata, listlabel)
For quick result, use this:
image_ktp = cv2.imread("assets/ktp_example.jpg")
easypredict(image_ktp, bBoxDet, numDet, alphaDet, input_type='ktp')
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
indOCRArmy-0.1.9.tar.gz
(11.4 kB
view hashes)
Built Distribution
indOCRArmy-0.1.9-py3-none-any.whl
(12.2 kB
view hashes)
Close
Hashes for indOCRArmy-0.1.9-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 535cd5a11bda0c93413f48b412dd3fbad519e3eb50160d1b5c78a73fec733785 |
|
MD5 | e9e2f4e6a3527525898d9dbd7f56a5cd |
|
BLAKE2b-256 | e6de409018c7d6d2c53c2f03ad939b87c9634e61dd48035ca9e3c26c7a7ead02 |