<jupyter_start><jupyter_text><jupyter_code>!pip install cvlib
import cv2
import matplotlib.pyplot as plt
import cvlib as cv
from cvlib.object_detection import draw_bbox


im = cv2.imread('/content/drive/MyDrive/data/cars.JPG')

img_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY) 
img_rgb = cv2.cvtColor(im, cv2.COLOR_BGR2RGB) 
bbox, label, conf = cv.detect_common_objects(im)
output_image = draw_bbox(im, bbox, label, conf)
plt.imshow(output_image)
plt.show()

#### EXtract Gif Images 

import imageio
import urllib.request
url = "http://rebloggy.com/post/my-gif-gif-cars-jaguar-drift-v8-jaguar-f-type/99677904600"
fname = "tmp.gif" 

imdata = urllib.request.urlopen(url).read()
imbytes = bytearray(imdata)
open(fname,"wb+").write(imdata)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.134640522875817, 'fraction_numerical': 0.026143790849673203, 'mean_word_length': 6.027522935779817, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, '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': '651925', 'license': 'MIT', 'n_tokens_mistral': 334, 'n_tokens_neox': 317, 'n_words': 52, 'path': 'simple_box_detection.ipynb', 'repo_name': 'Reet1992/Deep_learning_R', 'size': '765'}