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