<jupyter_start><jupyter_text>Car Number Plate Detection using OpenCV This code template is for car number plate detection using OpenCV  Required Packages<jupyter_code>import cv2
import numpy as np
import matplotlib.pyplot as plt<jupyter_output><empty_output><jupyter_text>Importing our Classifier**Link:** [classifier used in this template](https://drive.google.com/file/d/15o6VctOvVgySRoQMigPIRly9oBnU4Q1L/view)<jupyter_code>cascade = cv2.CascadeClassifier('')<jupyter_output><empty_output><jupyter_text>Reading our image OpenCV-Python is a library of Python bindings designed to solve computer vision problems.We use the the **"cv2.imread()"** method to load an image from the specified file path.<jupyter_code>cars = cv2.imread('')<jupyter_output><empty_output><jupyter_text>Converting Image to Gray<jupyter_code>gray = cv2.cvtColor(cars, cv2.COLOR_BGR2GRAY)<jupyter_output><empty_output><jupyter_text>Converting image to colored image<jupyter_code>def converToRGB(image):
    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)<jupyter_output><empty_output><jupyter_text>Drawing bounding boxes<jupyter_code>cars_detected = cascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(20,20))
print('Found Numbers', len(cars_detected))
for (x, y, w, h) in cars_detected:
    cv2.rectangle(cars, (x,y), (x+w,y+h),(145,60,255), 5)<jupyter_output><empty_output><jupyter_text>Final Image<jupyter_code>plt.figure(figsize=(20,20))
plt.imshow(converToRGB(cars));<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11394891944990176, 'fraction_numerical': 0.024230517354289455, 'mean_word_length': 7.935672514619883, 'pattern_counts': {'":': 0, '<': 29, '<?xml version=': 0, '>': 29, 'https://': 1, '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': '7', 'dir': 'jupyter-structured-clean-dedup', 'id': '493456', 'license': 'Apache-2.0', 'n_tokens_mistral': 587, 'n_tokens_neox': 551, 'n_words': 102, 'path': 'Audio Visual/Problems/CarNumberPlateDetection_OpenCV.ipynb', 'repo_name': 'shreepad-nade/ds-seed', 'size': '1527'}