ADVERTISEMENT

NEVER FORGET: Not a Single Election Expert Has Been Able to Explain the “Drop and Roll” Phenomenon that Flipped the 2020 Election to Joe Biden

50086787-0-image-a-8_1636079400841.jpg
Go get professional help for your mental problems.
 
  • Haha
Reactions: dpic73
This has to be blatant fraud. People are catching it but i would bet dollars to doughnuts nothing will happen.



Is the Biden regime weaponizing the Social Security Administration to hand out fake/temporary social security numbers to illegals and automatically registering them to vote in key swing states?

Over 2 million in TX, AZ, and PA alone in just the past 3 months - that’s insanity

There needs to be a national injunction to stop this takeover before it’s too late

All of these voter registrations need to be removed if they are illegal aliens

Red state attorneys general need to be all over this

========

Now you're catching on. The tell was so-called "conservative" governors gaslighting us about illegal aliens allegedly not getting driver's license (spoiler alert, they are). And they get DLs because the OBiden Regime is unlawfully granting millions of illegal "parolee" status, thereby automatically sending them work permits and social security cards. So DeSantis pretends this isn't happening by drawing the false distinction that these aliens are technically "legal." Every single conservative governor should have sued the OBiden Regime and appealed all the way to SCOUTS for this unlawful scheme to facilitate an invasion of the USA.
 
This is just another incident where Bill Barr and the DOJ facilitated the coverup of the election steal.



In the disbarment trial of Trump's former DOJ official Jeffrey Clark, operational security expert Harry Houry is discussing how he was present when Bill Barr called Tony Shaffer of the Amistad Project all irate and told them to stand down on looking into the USPS contractor who drove ballots from NY to PA.
 


And your overthrown government,

• +42,000 people voted more than once

• +1,500 votes cast, Social Security death records confirm resurrection of the dead

• +19,000 non residents cast, confirmed by U.S. Postal Service National Change of Address,

• +8,000 from non existent addresses

• +15,000 commercial or vacant addresses, confirmed by U.S. Postal Service

• +4000 cast by illegal aliens,

And the DOJ and the FBI confirms Joe Biden sexually molested his own daughter on regular basis in the shower,

“Our evidence has never been refuted only ignored.”
 


When they say that “undocumented migrants can’t vote in the U.S. elections,” think again.

Imagine with million of illegals pouring into our country how many will be able to vote in upcoming 2024 presidential elections.

10,000 illegal aliens using the same exact social security number voted on November 3, 2020 in AZ.
 



Surprise ending: the Dominion Voting Co. source code I viewed has over 2.5 million lines of code. Instantly that told me Dominion is using their machines to cheat and steal elections. From a recent conversation with the extraordinary Jeff O'Donnell (The Lone Racoon), quoting "If I ever take more than 50,000 lines of code to do anything, fire me". I went ahead and did it; below is my coding using Python language. This code reads the marked ovals on a scanned paper ballot image. It can process up to 100,000 ballots, tally up the responses, and generate a report summarizing the results. It uses the pandas' library to create a DataFrame for the report and then saves it to a CSV file. Then I would adjust the answer_key dictionary according to test sheet layout and provide the paths to the test sheet images in the test_sheet_paths list. Here is the code, (mine, not Dominion's):
import cv2
import numpy as np
import pandas as pd
from collections import defaultdict
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 = []
# Loop over contours
for contour in contours:
# Approximate the contour to a polygon
peri = cv2.arcLength(contour, True)
approx = cv2.approxPolyDP(contour, 0.02 * peri, True)
# If the contour has 4 vertices (approximation for oval) if len(approx) == 4:
ovals.append(approx.reshape(-1, 2))
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)
# Check if the oval is marked
# Assuming marked ovals are detected by some thresholding technique
if is_marked(image[y:y+h, x:x+w]):
# Find the closest answer option based on the center of the oval
closest_option = min(answer_key.keys(), key=lambda option: abs(answer_key[option][0] - oval_center[0]))
# Increment the count for the selected option
responses[closest_option] += 1
return responses
def is_marked(oval_image):
# Perform some thresholding or other technique to determine if the oval is marked
# For simplicity, let's assume if the oval area is not too bright, it's marked
return cv2.mean(oval_image)[0] < 200
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), # Coordinates of the center of the oval representing option A
'B': (200, 200), # Coordinates of the center of the oval representing option B
# Add more options as needed } test_sheet_paths = ['test_sheet_{}.jpg'.format(i) for i in range(1, 100001)] # Example test sheet paths
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 You know how many lines of code these tasks took? 77 lines. I did it in 77 lines yet Dominion has 2,500,000+ lines of code in its software/firmware. Citizens: send a question in writing to your local, county and state level election clerks/Sec. of States. Ask them if they have ever seen the source code for their tabulators, for their voting machines, for their EMS (Election Management System at the county). 100% guaranteed none of them - repeat none - of them have. So private companies are counting our votes who won't let us see the source code. (side comment: a few states require source code testing such as Texas, California - at least the did). But here is the real truth: ES&S and Dominion have several sets of source code. Which one do you think they supply to the states who require testing by outside IT people? Yep, the source code they WANT the outside IT experts to see. A very important word which will be at the center of attention in the future: lab.
 
ADVERTISEMENT
ADVERTISEMENT