Made improvements to the tracking script

camera module/main.py

@@ -2,7 +2,15 @@ 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.
+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)