<jupyter_start><jupyter_text>Environment Setup<jupyter_code>from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
from google.colab import auth
from oauth2client.client import GoogleCredentials

from google.colab import drive as dv
from google.colab import files
from google.colab import drive
drive.mount('/content/drive')
!git clone https://github.com/omni-us/squeezedet-keras.git
%cd 'squeezedet-keras'
!pip install -r requirements.txt
import os
import shutil
import zipfile
import urllib
import xml.etree.ElementTree as ET
import numpy as np
import csv
import pandas
from PIL import Image<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.06697819314641744, 'fraction_numerical': 0.001557632398753894, 'mean_word_length': 6.224719101123595, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 1}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '636178', 'license': 'MIT', 'n_tokens_mistral': 207, 'n_tokens_neox': 199, 'n_words': 65, 'path': '.ipynb_checkpoints/SqueezeDet-checkpoint.ipynb', 'repo_name': 'mattwells19/USRoadSignRecognition', 'size': '642'}