import utils
import numpy as np
import sys
fileName = sys.argv[1]
oldArray = utils.read_image_as_bw(fileName)
newArray = np.copy(oldArray)
shape = oldArray.shape
height = shape[0]
width = shape[1]
for i in range(height):
for j in range(width):
newArray[i][j] = oldArray[-i][j]
outPath = 'images/output/' + fileName
utils.show_image(newArray)
utils.save_bw_image(newArray, outPath)
elif blur.startswith("mean"):
n = blur[4:]
n = int(n)
img = mean_blur(img, n)
if method == 'sobel':
X_edges, Y_edges = sobel_edges_x_and_y(img)
elif method == 'central_difference':
X_edges, Y_edges = central_diff_edges_x_and_y(img)
magnitudes = compute_edge_magnitudes(X_edges, Y_edges)
directions = compute_edge_directions(X_edges, Y_edges)
img = suppress_edges(magnitudes, directions)
magnitudes[img == 1] = 0
magnitudes = magnitudes * (255.0 / magnitudes.max())
threshImg = np.copy(magnitudes)
threshImg[threshImg > t] = 255
threshImg[threshImg < t] = 0
return threshImg
path = r'C:\Users\Blake\Desktop\Vision\Lab 4\images\input\Piano.jpg'
img = utils.read_image_as_bw(path)
img = find_edges(img, 'sobel', 'gaussian3', 40)
utils.show_image(img)
#savePath = path = r'C:\Users\Blake\Desktop\Vision\Lab 4\images\output\Piano_edges.jpg'
#utils.save_bw_image(img, savePath)
#number is 9 - right side
final.append(9)
elif currSegment == [0, 0, 0, 255, 255, 0, 255]:
#number is 0 - right side
final.append(0)
else:
a = a
#print('broke')
final.append('broke')
#print(currSegment)
currSegment = []
if flipped == True:
final.reverse()
return final
imgPath = r'C:\Users\Blake\Desktop\Vision\Lab 6\images\easy.jpg'
img = utils.read_image_as_bw(imgPath)
img = np.rot90(img, 3)
barcode = find_barcode(img)
connComp = getLargestCC(barcode)
bar = getBarcode(img, connComp)
print(readBarcode(bar))