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import cv2 | |
import numpy as np | |
import random | |
numSnowflakes = 2000 | |
xSize, ySize = 1080, 1920 | |
#cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN) | |
#cv2.setWindowProperty("window",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN) |
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import cv2 | |
import numpy as np | |
import math | |
imgSize = 600,600, 3 | |
coreCenter = 300,300 | |
coreSize = 50 | |
beltThickness = .045 | |
beltLength = 5025 | |
segmentStart = coreCenter[0], coreCenter[1] + coreSize |
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import numpy as np | |
import cv2 | |
import pandas as pd | |
import numpy.polynomial.polynomial as poly | |
import math | |
# Read Source Data | |
cap = cv2.VideoCapture('/home/stephen/Desktop/ss5_id_412.MP4') | |
df = pd.read_csv('/home/stephen/Desktop/ss5_id_412.csv') | |
#Write Video Out |
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import cv2 | |
import numpy as np | |
# Define the multiverse parameter | |
multiverse_parameter = 3 | |
# Define the temporal seperation in frames | |
temporal_seperation = 24 | |
# Define path to source video |
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import cv2 | |
import numpy as np | |
# Read in image | |
img = cv2.imread('/home/stephen/Desktop/test.png',0) | |
img = 255 - img | |
img = cv2.resize(img, (6000,6000)) | |
h,w = img.shape | |
cutter_size = 20 | |
buffer = int(cutter_size * 1.25) |
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from mrcnn.config import Config | |
from mrcnn import model as modellib | |
from mrcnn import visualize | |
import cv2, os, numpy as np | |
# Make Model: https://github.com/matterport/Mask_RCNN/blob/master/samples/demo.ipynb | |
class Config(Config): | |
NAME = "deep_segment" | |
GPU_COUNT = 1 | |
IMAGES_PER_GPU = 1 |
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import numpy as np | |
import cv2 | |
from matplotlib import pyplot as plt | |
# Load image and mask | |
img = cv2.imread('/home/stephen/Downloads/bird.jpg') | |
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) | |
h,w,_ = img.shape | |
deep_mask = cv2.imread('/home/stephen/Downloads/bird_mask.png',0) | |
deep_mask = cv2.resize(deep_mask, (w,h)) |
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# This script will only work if the post it | |
# notes are on a really white background. | |
# | |
# You will have to change the paths to: | |
# 1. Path to source image | |
# 2. Path to desktop (or folder to save images) | |
# https://stackoverflow.com/questions/55832414/extract-a-fixed-number-of-squares-from-an-image-with-python-opencv/55834299?noredirect=1#comment98366082_55834299 | |
import cv2 | |
import numpy as np |
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import cv2 | |
import numpy as np | |
src = 255 - cv2.imread('/home/stephen/Desktop/I7Ykpbs.jpg',0) | |
scores = [] | |
h,w = src.shape | |
small_dimention = min(h,w) | |
src = src[:small_dimention, :small_dimention] |
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import cv2, numpy as np, random, math | |
# Find contour edges | |
# Find the edge that is torn | |
# use the hough line transform | |
# create a mask image where the lines and white on a black background | |
# check if the point is in a white or black region | |
# Rotate the torn edges | |
# Measure how much they overlap | |
# The rotation with the maximum overlap will be how they should align |
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