shamilnabiyev

1. Run commands in Git Bash
   • env PIP_REQUIRE_VIRTUALENV=0 python -m pip install --user pipx
   • python -m pipx ensurepath --force
2. Open a new Git Bash terminal
   • pipx --version
3. If getting an error during the installation of packages using pipx
   • No Python at 'C:\Users\<username>\AppData\Local\Programs\Python\PythonX\python.exe'
   • Then remove the following folder
   • C:\Users\<username>\.local\pipx
4. If still having the same issue

shamilnabiyev

import json
import requests
import pandas as pd
from itertools import chain

def get_sbahn_list(product='suburban', operator='1'):
    """
    Get S-Bahn Line list from VBB Transport API

    S-Bahn: product=suburban

shamilnabiyev

# Credits: 
#   Author: Gabriel Cassimiro 
#   Blog post: https://towardsdatascience.com/transfer-learning-with-vgg16-and-keras-50ea161580b4
#   GitHub Repo: https://github.com/gabrielcassimiro17/object-detection
#
import tensorflow_datasets as tfds
from tensorflow.keras import layers, models
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.callbacks import EarlyStopping

shamilnabiyev

# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# Hyperparameters for low-augmentation COCO training from scratch
# python train.py --batch 64 --cfg yolov5n6.yaml --weights '' --data coco.yaml --img 640 --epochs 300 --linear
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials

lr0: 0.01  # initial learning rate (SGD=1E-2, Adam=1E-3)
lrf: 0.01  # final OneCycleLR learning rate (lr0 * lrf)
momentum: 0.937  # SGD momentum/Adam beta1
weight_decay: 0.0005  # optimizer weight decay 5e-4
warmup_epochs: 3.0  # warmup epochs (fractions ok)

shamilnabiyev

# Source: https://sheldonsebastian94.medium.com/resizing-image-and-bounding-boxes-for-object-detection-7b9d9463125a

import albumentations
from PIL import Image
import numpy as np

sample_img = Image.open("data/img1.jpg")
sample_arr = np.asarray(sample_img)

def resize_image(img_arr, bboxes, h, w):

shamilnabiyev

https://pypi.org/pypi/seaborn/0.11.2/json

shamilnabiyev

import mlflow
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import precision_recall_fscore_support
from sklearn.metrics import accuracy_score
from sklearn.metrics import confusion_matrix
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import StratifiedKFold

shamilnabiyev

import optuna
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_val_score
from sklearn.metrics import classification_report
from sklearn.metrics import precision_recall_fscore_support
from sklearn.metrics import accuracy_score

shamilnabiyev

from sklearn.metrics import precision_recall_fscore_support
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import classification_report
from sklearn.datasets import make_classification
from sklearn.metrics import accuracy_score
import mlflow

shamilnabiyev

pandoc --filter pandoc-citeproc --bibliography=test.bib --citeproc -t docx -o test.docsx