Multiple Color Detection Project

Multiple Color Detection Project

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+# Python code for Multiple Color Detection 
+
+
+import numpy as np 
+import cv2 
+
+
+# Capturing video through webcam 
+webcam = cv2.VideoCapture(0) 
+
+# Start a while loop 
+while(1): 
+
+	# Reading the video from the 
+	# webcam in image frames 
+	_, imageFrame = webcam.read() 
+
+	# Convert the imageFrame in 
+	# BGR(RGB color space) to 
+	# HSV(hue-saturation-value) 
+	# color space 
+	hsvFrame = cv2.cvtColor(imageFrame, cv2.COLOR_BGR2HSV) 
+
+	# Set range for red color and 
+	# define mask 
+	red_lower = np.array([136, 87, 111], np.uint8) 
+	red_upper = np.array([180, 255, 255], np.uint8) 
+	red_mask = cv2.inRange(hsvFrame, red_lower, red_upper) 
+
+	# Set range for green color and 
+	# define mask 
+	green_lower = np.array([25, 52, 72], np.uint8) 
+	green_upper = np.array([102, 255, 255], np.uint8) 
+	green_mask = cv2.inRange(hsvFrame, green_lower, green_upper) 
+
+	# Set range for blue color and 
+	# define mask 
+	blue_lower = np.array([94, 80, 2], np.uint8) 
+	blue_upper = np.array([120, 255, 255], np.uint8) 
+	blue_mask = cv2.inRange(hsvFrame, blue_lower, blue_upper) 
+
+	# Morphological Transform, Dilation 
+	# for each color and bitwise_and operator 
+	# between imageFrame and mask determines 
+	# to detect only that particular color 
+	kernal = np.ones((5, 5), "uint8") 
+
+	# For red color 
+	red_mask = cv2.dilate(red_mask, kernal) 
+	res_red = cv2.bitwise_and(imageFrame, imageFrame, 
+							mask = red_mask) 
+
+	# For green color 
+	green_mask = cv2.dilate(green_mask, kernal) 
+	res_green = cv2.bitwise_and(imageFrame, imageFrame, 
+								mask = green_mask) 
+
+	# For blue color 
+	blue_mask = cv2.dilate(blue_mask, kernal) 
+	res_blue = cv2.bitwise_and(imageFrame, imageFrame, 
+							mask = blue_mask) 
+
+	# Creating contour to track red color 
+	contours, hierarchy = cv2.findContours(red_mask, 
+										cv2.RETR_TREE, 
+										cv2.CHAIN_APPROX_SIMPLE) 
+
+	for pic, contour in enumerate(contours): 
+		area = cv2.contourArea(contour) 
+		if(area > 300): 
+			x, y, w, h = cv2.boundingRect(contour) 
+			imageFrame = cv2.rectangle(imageFrame, (x, y), 
+									(x + w, y + h), 
+									(0, 0, 255), 2) 
+
+			cv2.putText(imageFrame, "Red Colour", (x, y), 
+						cv2.FONT_HERSHEY_SIMPLEX, 1.0, 
+						(0, 0, 255))	 
+
+	# Creating contour to track green color 
+	contours, hierarchy = cv2.findContours(green_mask, 
+										cv2.RETR_TREE, 
+										cv2.CHAIN_APPROX_SIMPLE) 
+
+	for pic, contour in enumerate(contours): 
+		area = cv2.contourArea(contour) 
+		if(area > 300): 
+			x, y, w, h = cv2.boundingRect(contour) 
+			imageFrame = cv2.rectangle(imageFrame, (x, y), 
+									(x + w, y + h), 
+									(0, 255, 0), 2) 
+
+			cv2.putText(imageFrame, "Green Colour", (x, y), 
+						cv2.FONT_HERSHEY_SIMPLEX, 
+						1.0, (0, 255, 0)) 
+
+	# Creating contour to track blue color 
+	contours, hierarchy = cv2.findContours(blue_mask, 
+										cv2.RETR_TREE, 
+										cv2.CHAIN_APPROX_SIMPLE) 
+	for pic, contour in enumerate(contours): 
+		area = cv2.contourArea(contour) 
+		if(area > 300): 
+			x, y, w, h = cv2.boundingRect(contour) 
+			imageFrame = cv2.rectangle(imageFrame, (x, y), 
+									(x + w, y + h), 
+									(255, 0, 0), 2) 
+
+			cv2.putText(imageFrame, "Blue Colour", (x, y), 
+						cv2.FONT_HERSHEY_SIMPLEX, 
+						1.0, (255, 0, 0)) 
+
+	# Program Termination 
+	cv2.imshow("Multiple Color Detection in Real-TIme", imageFrame) 
+	if cv2.waitKey(10) & 0xFF == ord('q'): 
+		cap.release() 
+		cv2.destroyAllWindows() 
+		break