Skip to main content

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.

for comprehensive use, you can do this:

import os
import cv2
import matplotlib.pyplot as plt

from IndoOCRArmy.modelOCR import numericalDetectron2, boundingBoxesDetectron2, alphabeticalDetectron2, easypredict
from IndoOCRArmy.drawer import DrawOCR

from config import cfg

# load classes
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 comprehensive result, visualize this:

drawer_ocr.show_desc(image_ktp, boxes, labels, listdata, listlabel)

For quick result, use this:

from IndoOCRArmy.modelOCR import numericalDetectron2, boundingBoxesDetectron2, alphabeticalDetectron2, easypredict
import cv2

# load classes
drawer_ocr = DrawOCR(cfg['drawOCR'])
bBoxDet = boundingBoxesDetectron2(cfg['boundingBoxesDetectron2'])
numDet = numericalDetectron2(cfg['numericalDetectron2'])
alphaDet = alphabeticalDetectron2(cfg['alphabeticalDetectron2'])

image_ktp = cv2.imread("assets/ktp_example.jpg")
easypredict(image_ktp, bBoxDet, numDet, alphaDet, input_type='ktp')

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

indOCRArmy-0.1.2.tar.gz (11.0 kB view hashes)

Uploaded Source

Built Distribution

indOCRArmy-0.1.2-py3-none-any.whl (11.7 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page