Created
February 14, 2017 05:28
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Edge detection with sobelx and sobely.
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import numpy as np | |
import cv2 | |
import matplotlib.pyplot as plt | |
import matplotlib.image as mpimg | |
import pickle | |
# Read in an image | |
image = mpimg.imread('signs_vehicles_xygrad.png') | |
# Define a function that applies Sobel x and y, | |
# then computes the magnitude of the gradient | |
# and applies a threshold | |
def mag_thresh(img, sobel_kernel=3, mag_thresh=(0, 255)): | |
# Apply the following steps to img | |
# 1) Convert to grayscale | |
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) | |
# 2) Take the gradient in x and y separately | |
sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=sobel_kernel) | |
sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=sobel_kernel) | |
# 3) Calculate the magnitude | |
magnitude = np.sqrt(np.power(sobelx,2) + np.power(sobely, 2)) | |
# 4) Scale to 8-bit (0 - 255) and convert to type = np.uint8 | |
scaled_sobel = np.uint8(255*magnitude/np.max(magnitude)) | |
# 5) Create a binary mask where mag thresholds are met | |
binary = np.zeros_like(scaled_sobel) | |
binary[(scaled_sobel >= mag_thresh[0]) & (scaled_sobel <= mag_thresh[1])] =1 | |
# 6) Return this mask as your binary_output image | |
binary_output = binary | |
return binary_output | |
# Run the function | |
mag_binary = mag_thresh(image, sobel_kernel=3, mag_thresh=(30, 100)) | |
# Plot the result | |
f, (ax1, ax2) = plt.subplots(1, 2, figsize=(24, 9)) | |
f.tight_layout() | |
ax1.imshow(image) | |
ax1.set_title('Original Image', fontsize=50) | |
ax2.imshow(mag_binary, cmap='gray') | |
ax2.set_title('Thresholded Magnitude', fontsize=50) | |
plt.subplots_adjust(left=0., right=1, top=0.9, bottom=0.) |
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