<jupyter_start><jupyter_text>First Big Thing<jupyter_code>import cv2
import numpy as np

def first_big_thing(image):
    # Convert image to grayscale
    
    
    # Clean up image using Guassian Blur of kernel 5x5
    
    
    # Extract edges using canny edge detection with t1 = 10 and t2 = 70
    
    
    # Do an invert binarize the image with thres = 50 , max = 255 (mostly) and threshold type = cv2.THRESH_BINARY_INV
    
    
    return "<the manipulated img>"

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    cv2.imshow('First Big Thing', first_big_thing(frame))
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
        
# Release camera and close windows
cap.release()
cv2.destroyAllWindows()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08650065530799476, 'fraction_numerical': 0.028833551769331587, 'mean_word_length': 2.9791666666666665, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 6, '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': '614803', 'license': 'MIT', 'n_tokens_mistral': 276, 'n_tokens_neox': 257, 'n_words': 78, 'path': '03 - first big thing/First Big Thing.ipynb', 'repo_name': 'Joish/opencv', 'size': '763'}