ahmedbilal

from datetime import datetime
from zoneinfo import ZoneInfo
from dateutil import tz
from dateutil.rrule import rrule, SA, SU, DAILY

start_date = datetime(2023, 3, 4, 2, 10, tzinfo=ZoneInfo("America/New_York"))

for dt in rrule(freq=DAILY, count=10, byweekday=[SA, SU], dtstart=start_date):
    print(dt, tz.datetime_exists(dt))
    

ahmedbilal

Print SQL Queries in Jupyterlab
Connect Jupyter lab with Django Extensions Kernel

ahmedbilal

Title

<Additional information about your API call. Try to use verbs that match both request type (fetching vs modifying) and plurality (one vs multiple).>

Method & URL

GET | POST | DELETE | PUT <The URL Structure (path only, no root url)>

<For Example: POST /api/search/fastsearch/>

ahmedbilal

0
0
0
0
0
0
0
0
0
0

ahmedbilal

0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0
0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,9,0,0,0,0,0,30,0,0,0,0

ahmedbilal

import keras
import numpy as np
from os.path import isfile as is_file_exists

from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.optimizers import Adam
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import train_test_split

ahmedbilal

{
  "embeddings": [
    {
      "tensorName": "My tensor",
      "tensorShape": [
        1000,
        50
      ],
      "tensorPath": "https://gist.githubusercontent.com/ahmedbilal/5d9804d5821dd7ef634d67d27d69a211/raw/aa197ef9f61f0fb304e23e8165bbfc6171c31043/X_Values.tsv",
      "metadataPath": "https://gist.githubusercontent.com/ahmedbilal/5d9804d5821dd7ef634d67d27d69a211/raw/aa197ef9f61f0fb304e23e8165bbfc6171c31043/labels.tsv"

ahmedbilal

ahmedbilal

import cv2
import os
import argparse

arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("--input", type=str, help="Input annotation[.txt] file path",
                        dest="input_file", required=True)
args = arg_parser.parse_args()

with open(args.input_file, "r") as f:

ahmedbilal

import argparse
from collections import namedtuple

ROI = namedtuple("ROI", ["xa", "ya", "xb", "yb"])

arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("--input", type=str, help="Input annotation[.txt] file path", dest="input_file",
                        required=True)
arg_parser.add_argument("--output", type=str, help="Output/Filtered annotation[.txt] file path",
                        dest="output_file", required=True)