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Made improvements to the tracking script

master
Stelios Giakoumidis 5 years ago
parent
commit
9d50892eb1
  1. 44
      camera module/main.py

44
camera module/main.py

@ -1,8 +1,16 @@
import cv2
# Constant variables definition.
DESIRED_HEIGHT = 480 # The input image will be resized to this height, preserving its aspect ratio.
BLUE_THRESHOLD = 128 # If the blue channel is bigger than this, it is considered background and removed.
DESIRED_HEIGHT = 480 # The input image will be resized to this height, preserving its aspect ratio.
BLUE_THRESHOLD = 150 # If the blue channel is bigger than this, it is considered background and removed.
BINARY_THRESHOLD = 1 # If the pixel is not brighter than this, it is removed before detection.
# Colors (assuming BGR order).
RED = (0, 0, 255)
GREEN = (0, 255, 0)
BLUE = (255, 0, 0)
YELLOW = (0, 255, 255)
# Function definitions
@ -17,8 +25,7 @@ def resizeImage(img):
#####################################################################################
# Read image from source
img = cv2.imread('/home/stelios/Desktop/IoT/drone.jpg', cv2.IMREAD_COLOR)
img = cv2.imread('/home/stelios/Desktop/IoT/Talos_Drones_Tracking_and_Telemetry/camera module/drone.jpg', cv2.IMREAD_COLOR)
# Resize image to the desired height.
img = resizeImage(img)
@ -35,22 +42,29 @@ for i in range(p[0]):
# Convert to grayscale.
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
#####################################################################
thres1, img2 = cv2.threshold(img, 1, 255, cv2.THRESH_BINARY)
im2, contours, hierarchy = cv2.findContours(img2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# Threshold the image and find its contours.
thres, imgThres = cv2.threshold(img, BINARY_THRESHOLD, 255, cv2.THRESH_BINARY)
img2, contours, hierarchy = cv2.findContours(imgThres, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# Find the biggest contour.
maxContour = max(contours, key = cv2.contourArea)
cv2.drawContours(imgOriginal, maxContour, -1, (0,0,255), 1)
print(len(maxContour))
'''
hull = cv2.convexHull(maxContour)
cv2.drawContours(imgOriginal, maxContour, -1, (0,0,255), 3)
cv2.drawContours(imgOriginal, hull, -1, (255,0,0), 3)
'''
# Get the bounding rectangle of the contour.
x,y,w,h = cv2.boundingRect(maxContour)
# draw the biggest contour (c) in green
cv2.rectangle(imgOriginal,(x,y),(x+w,y+h),(0,20,255),2)
# Get the centroid of the rectangle.
centerX = int( (x + x + w) / 2)
centerY = int( (y + y + h) / 2)
cv2.imshow('Test', imgOriginal)
cv2.waitKey(0)
# Draw the bounding rectangle and its centroid to the image.
cv2.circle(imgOriginal, (centerX, centerY), 5, YELLOW, 2)
cv2.rectangle(imgOriginal, (x,y), (x+w,y+h), RED, 2)
cv2.imshow('Output', imgOriginal)
cv2.waitKey(0)
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