Attorney & software exec John Graves says there's a "very serious problem" with 2024 election security: "If the allegations are true and 2024 voting systems have this [vulnerability]...you can change things and cover your tracks." Tomorrow on Glenn TV, he'll present the solution.
Here Mr. Beck, 71 lines of computer code to count marked paper ballots, tally and report. But it takes Dominion Voting: 2,500,000+. My new code is below where I improved the accuracy of reading the marked ovals by honing in on the aspect ratio. Think how stupid all our govt. officials are who pay millions upon millions to Dominion Voting for junk machines and their garbage code. State of Georgia paid $101 million to Dominion! State of Michigan $82 million! Dummies. And of course a program used in the real world would have more lines, but you get my point of how dumb we all are for dealing with the Dominion crooks whose machines are stealing our elections while taking our tax monies. Dominion has two sets of source code in their machines, like two sets of financial books at a company hiding income from the IRS. My code: import numpy as np import pandas as pd from collections import defaultdict import cv2 def detect_ovals(image): # Convert image to grayscale gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # Apply Gaussian blur to reduce noise blurred = cv2.GaussianBlur(gray, (5, 5), 0) # Detect edges using Canny edge detector edges = cv2.Canny(blurred, 50, 150) # Find contours contours, _ = cv2.findContours(edges.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) ovals = [] for contour in contours: # Check if the shape is a circle or oval using aspect ratio and area (x, y), (MA, ma), angle = cv2.fitEllipse(contour) area = cv2.contourArea(contour) if 0.5 < MA/ma < 1.5 and area > 100: # Adjust these values as needed ovals.append(contour) return ovals def read_marked_ovals(test_sheet_path, answer_key): image = cv2.imread(test_sheet_path) ovals = detect_ovals(image) responses = defaultdict(int) for oval in ovals: x, y, w, h = cv2.boundingRect(oval) oval_center = (x + w // 2, y + h // 2) if is_marked(image[y:y+h, x:x+w]): closest_option = min(answer_key.keys(), key=lambda option: np.linalg.norm(np.array(answer_key[option])-np.array(oval_center))) responses[closest_option] += 1 return responses def is_marked(oval_image): # Use adaptive thresholding to detect markings within the oval gray = cv2.cvtColor(oval_image, cv2.COLOR_BGR2GRAY) thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2) # Calculate the percentage of black pixels in the area to determine if marked black_pixels = np.sum(thresh == 0) total_pixels = thresh.size return black_pixels / total_pixels > 0.2 # Adjust threshold as needed def generate_report(responses): report = pd.DataFrame.from_dict(responses, orient='index', columns=['Count']) report.index.name = 'Option' report.sort_index(inplace=True) return report def process_test_sheets(test_sheets, answer_key): total_responses = defaultdict(int) for test_sheet_path in test_sheets: responses = read_marked_ovals(test_sheet_path, answer_key) for option, count in responses.items(): total_responses[option] += count return total_responses # Example usage answer_key = { 'A': (100, 200), 'B': (200, 200), # Add more options as needed } test_sheet_paths = ['test_sheet_{}.jpg'.format(i) for i in range(1, 11)] # Assuming 10 test sheets for demonstration responses = process_test_sheets(test_sheet_paths, answer_key) report = generate_report(responses) print(report) report.to_csv('test_results.csv') # Save report to a CSV file ----In order to get the statement import to run, install OpenCV using pip. Open your terminal or command prompt and execute the following command: pip install opencv-python After running this command, OpenCV will be installed in your Python environment, and you can run it to get the statement 'import cv2' to run. What I am charging for this open source code: $0 Peter Bernegger
@glennbeck 💯 💯 💯 There are multiple ways to affect our elections. I can name 12 - 15 that haven’t been addressed. See my pinned post for sworn witness testimony.
Nothing has changed or been taken seriously since the last election so why would we expect anything different. Everyone has a story about voting in their own cities, and towns, and people have seen what they’ve seen, and know what they know, so no one has fallen for any of the BS they’ve been trying to feed us. We aren’t the ones that need to hear more proof. The people that need to do something to fix it are.
@glennbeck Voters are anxious because they know 2020 was stolen and if they do it again, shit is going to hit the fan. No one wants that. We want free and fair elections. Unfortunately the dems are setting us up to question everything.
@glennbeck Paper ballots. IDs. This isn’t hard, but leftists want it prone to manipulation and cheating.
@glennbeck I wish every American would watch this interview . You can also follow @mad_liberals He's broken down a ton of his work here on X. Thank you, Mr. Beck for highlighting Mr. Graves' work. IMO he's an American Treasure .