spdin

# https://rtyley.github.io/bfg-repo-cleaner/

# check pack size
git count-objects -v -H

# download bfg and move to directory, rename to bfg
wget https://repo1.maven.org/maven2/com/madgag/bfg/1.13.0/bfg-1.13.0.jar

# clone mirror
git clone --mirror git://example.com/some-big-repo.git

spdin

# split file
split -b 500M <<NAMA FILE>> x

# join file
cat x* > <<NAMA FILE>>

spdin

#https://medium.com/@acpanjan/download-google-drive-files-using-wget-3c2c025a8b99

# change FILEID
# https://drive.google.com/file/d/1UibyVC_C2hoT_XEw15gPEwPW4yFyJFeOEA
# FILEID = 1UibyVC_C2hoT_XEw15gPEwPW4yFyJFeOEA

# tools
https://gdrive-wget.glitch.me/

# small file

spdin

ctrl+alt+f1

cd "/Downloads/cuda utils/"

pilih No jika ada yg nanya2 install

sudo service lightdm stop
sudo ./NVIDIA-Linux-x86_64-430.50.run
sudo service lightdm start

spdin

import pickle

# Saving the objects:

with open('test1.pkl', 'wb') as f:  # Python 3: open(..., 'wb')
    pickle.dump([table_bbox, row_bbox, column_bbox], f)

# Getting back the objects:

with open('test1.pkl', 'rb') as f:  # Python 3: open(..., 'rb')

spdin

server {
        listen 80 default_server;
        listen [::]:80 default_server;
        root /var/www/html;
        server_name _;
        index index.html index.htm index.nginx-debian.html;

        location / {
                proxy_read_timeout 600s;
                proxy_connect_timeout 600s;

spdin

gunicorn -w 5 -b 127.0.0.1:8811 api:app -t 120 --reload --max-requests 100 --access-logfile log.txt --access-logformat '%(h)s %(l)s %(u)s %(t)s "%(r)s" %(s)s %(b)s "%(f)s" "%(a)s" %({X-REMOTE-ADDR}i)s %({X-REAL-IP}i)s'

spdin

save_keeping_v2 =  {
        "1_000": None,
        "1_001": {
            "jenis_dokumen": {
                "text": "INVOICE",
            },
            "nomor_dokumen": {
                "text": "cloudmob015",
            },
        }

spdin

flask==1.0.2
opencv-python==4.0.1.23
opencv-python-headless==4.5.1.48
pyyaml==5.3.1
shapely==1.7.0
pandas==0.24.2
requests==2.23.0
albumentations==0.4.5
glog==0.3.1
gunicorn==20.0.4

spdin

import matplotlib.pyplot as plt

training_points = [0, 10, 25, 50, 100, 250, 500]

bert_acc = [0.5310526315789473, 0.5727631578947369, 0.6130263157894736, 0.8502631578947368, 0.8619736842105263, 0.8727631578947368, 0.8660526315789474]

roberta_acc = [0.49236842105263157, 0.6001315789473685, 0.7292105263157894, 0.7705263157894737, 0.8469736842105263, 0.8442105263157895, 0.8730263157894737]

plt.plot(training_points, bert_acc, label="bert-base-uncased")
plt.plot(training_points, roberta_acc, label="roberta-base")