""" ************************************************************************* // Example program using OpenCV library // python >3.7 - OpenCV 4.5 // @file e5b.py // @author Luis M. Jimenez // @date 2022 // // @brief Course: Computer Vision (1782) // Dept. of Systems Engineering and Automation // Automation, Robotics and Computer Vision Lab (ARVC) // http://arvc.umh.es // University Miguel Hernandez // // @note Description: // - This example captures images from a camera, shows them in a window and... // - Enables a handler for mouse events // - Enables a trackbar // - Shows RGB color value under cursor in overlay // - Segments a region by color using Hue channel // - Calculates ConvexHull and convexDefects // - Draws convexHull // ************************************************************************* """ # Import libraries import cv2 as cv import numpy as np import argparse # ----------------------------------------- # Functions # ----------------------------------------- """ //---------------------------------------------------------------------- // Mouse events handler for image window //---------------------------------------------------------------------- // event: event type sent to the handler -> cv.EVENT_MOUSEMOVE, // cv.EVENT_LBUTTONDOWN, cv.EVENT_LBUTTONUP, cv.EVENT_LBUTTONDBLCLK, // cv.EVENT_RBUTTONDOWN, cv.EVENT_RBUTTONUP, cv.EEVENT_RBUTTONDBLCLK, // cv.EVENT_MBUTTONDOWN, cv.EVENT_MBUTTONUP, cv.EEVENT_MBUTTONDBLCLK, // cv.EVENT_MOUSEWHEEL, cv.EVENT_MOUSEHWHEEL // x: X-coordinate position of the mouse in window // y: Y-coordinate position of the mouse in window // flags: aditional flags sent to the handler -> // cv.EVENT_FLAG_SHIFTKEY, cv.EVENT_FLAG_CTRLKEY, cv.EVENT_FLAG_ALTKEY, // cv.EVENT_FLAG_LBUTTON, cv.EVENT_FLAG_RBUTTON, cv.EVENT_FLAG_MBUTTON, // param: set in cv.SetMouseCallback //---------------------------------------------------------------------- """ def onMouse(event, x, y, flags, param): global capture, ID_FILE # global variables used in the mouse handler global CURSOR_POS, EXIT, BUTTON_POS, BUTTON_SIZE # print(f"{event=}, {x=}, {y=}, {flags=}, {param=}") # on click left mouse button and SHIFT key, saves image if event==cv.EVENT_LBUTTONDOWN and (flags & cv.EVENT_FLAG_SHIFTKEY): filename = f"Image{ID_FILE}.jpg" print(f"Saving image window in file: {filename}") cv.imwrite(filename, capture) # save window image ID_FILE += 1 # on moving the cursor over the image if event == cv.EVENT_MOUSEMOVE: CURSOR_POS = (y, x) # save new cursor position in global variable cursorPos (row,col) # on click left mouse button if event == cv.EVENT_LBUTTONDOWN: # checks if Exit button is clicked if (x > BUTTON_POS[0] and x < (BUTTON_POS[0] + BUTTON_SIZE[0]) and y > BUTTON_POS[1] and y < (BUTTON_POS[1] + BUTTON_SIZE[1]) ): EXIT = True #---------------------------------------------------------------------- # Trackbar events handler # x: trackbar position #---------------------------------------------------------------------- def onTrackbar(x): global ALPHA ALPHA = x def onTrackbarNull(x): pass """ //---------------------------------------------------------------------- // make a copy of input image as background (converts it to color if necessary) // Draws in overlay color information (under cursor) of input image // blends two images: disp image with overlay (24 bits BGR) and returns background image // alpha -> 0-1 (0 means only background, 1: only overlay) [0.6 default] // imageQuery: optional, peeks the color from this matrix instead of image //---------------------------------------------------------------------- """ def drawOverlay(image, alpha=0.6, imageQuery=None): global CURSOR_POS, BUTTON_POS, BUTTON_SIZE global IMAGE_ID # 0: capture, 1:HSV, 2:Hue, 3:RES background = image.copy() # creates a copy to preserve original image # Allocates memory for overlay image of the same size as input image overlay = np.zeros((image.shape[0], image.shape[1], 3), dtype=np.uint8) # if input image is not BGR, it is converted to BGR if image.ndim < 3: background = cv.cvtColor(background, cv.COLOR_GRAY2BGR) # Drawing the overlay image # draw button cv.rectangle(overlay, BUTTON_POS, BUTTON_POS + BUTTON_SIZE, (0, 120, 120), cv.FILLED) cv.rectangle(overlay, BUTTON_POS, BUTTON_POS + BUTTON_SIZE, (0, 255, 255), 1) # text with the pixel color under the cursor if imageQuery is None: color = image[CURSOR_POS] else: color = imageQuery[CURSOR_POS] if np.ndim(color) == 0: # color is scalar if IMAGE_ID == 3 and imageQuery is None: cursorColor = f"Sat[{color}]" elif IMAGE_ID == 4 and imageQuery is None: cursorColor = f"Gray[{color}]" else: cursorColor = f"Hue[{color}]" # Gray scale level else: if IMAGE_ID == 1: cursorColor = f"HSV{color}" else: cursorColor = f"RGB{color[::-1]}" # reverse BGR tuple # print(cursorColor) # offset to draw text centered in the rectangle textsize, baseline = cv.getTextSize(cursorColor, cv.FONT_HERSHEY_DUPLEX, 0.4, 1) offset = BUTTON_SIZE * 0.5 + np.array(textsize) * [-0.5, 0.5] cv.putText(overlay, cursorColor, BUTTON_POS + offset.astype(int), cv.FONT_HERSHEY_DUPLEX, 0.4, (255, 255, 255), 1, cv.LINE_AA) # blending both images mask = (overlay != 0).any(axis=2) # logical mask with non black pixels (0,0,0) in overlay background[mask] = cv.addWeighted(background[mask], 1 - alpha, overlay[mask], alpha, 0) return background # End drawOverlay function # ----------------------------------------- # Global variables # ----------------------------------------- WINDOW_CAMERA1 = '(W1) Camera 1' # window id WINDOW_RES = '(W2) Result' # window id CAMERA_ID = 0 # default camera KEY_F5 = 7602176 # F5 unicode key code ID_FILE = 1 # filename id # Trackbar variables ALPHA = 60 # % level of transparency IMAGE_ID = 0 # Select image to visualize -> 0:capture, 1:HSV, 2:Hue, 3:Sat, 4:Int AREA_MIN = 1000 # min area HSV_THRESHOLD_LOW = [110, 30, 30] # Low and High HSV threshold HSV_THRESHOLD_HIGH = [130, 255, 255] # Low and High HSV threshold HUE_CENTER = 10 # Hue valued to be centered in HUE normalization EXIT = False # exit the program CURSOR_POS = (0, 0) # current position of the cursor over the window (row,col) BUTTON_SIZE = np.array((160, 25)) # Overlay button Size (width,heigth) BUTTON_POS = np.array((0, 0)) # overlay button upper left corner position (x,y) # check command line parameters (camera id) parser = argparse.ArgumentParser(description='OpenCV example: captures images from a camera') parser.add_argument('-c', dest='cameraID', type=int, default=CAMERA_ID, metavar='id', help='camera id') CAMERA_ID = parser.parse_args().cameraID # ----------------------------------------- # Put here the code to Initialize objets # ----------------------------------------- # Open camera object camera = cv.VideoCapture(CAMERA_ID) if not camera.isOpened(): print("you need to connect a camera, sorry.") exit() # Getting camera resolution cameraWidth = int(camera.get(cv.CAP_PROP_FRAME_WIDTH)) cameraHeight = int(camera.get(cv.CAP_PROP_FRAME_HEIGHT)) # Creating visualization windows cv.namedWindow(WINDOW_CAMERA1, cv.WINDOW_AUTOSIZE) cv.namedWindow(WINDOW_RES, cv.WINDOW_AUTOSIZE) # enable a trackbar associated to variable ALPHA cv.createTrackbar("Transp", WINDOW_CAMERA1, ALPHA, 100, onTrackbar) cv.createTrackbar("c/HS/H/S/I", WINDOW_CAMERA1, IMAGE_ID, 4, onTrackbarNull) cv.createTrackbar("(p)Im/Hue", WINDOW_CAMERA1, 0, 1, onTrackbarNull) cv.createTrackbar("HueLowThr", WINDOW_RES, HSV_THRESHOLD_LOW[0], 255, onTrackbarNull) cv.createTrackbar("HueHighThr", WINDOW_RES, HSV_THRESHOLD_HIGH[0], 255, onTrackbarNull) cv.createTrackbar("SatLowThr", WINDOW_RES, HSV_THRESHOLD_LOW[1], 255, onTrackbarNull) cv.createTrackbar("SatHighThr", WINDOW_RES, HSV_THRESHOLD_HIGH[1], 255, onTrackbarNull) cv.createTrackbar("Min. Area", WINDOW_RES, AREA_MIN, 5000, onTrackbarNull) cv.createTrackbar("Hue Center", WINDOW_RES, HUE_CENTER, 255, onTrackbarNull) # Setting Mouse Handler cv.setMouseCallback(WINDOW_CAMERA1, onMouse) print(f"Capturing images from camera {CAMERA_ID} ({cameraWidth},{cameraHeight})") print("...Hit F5 or Space bar to capture and save the image") print("...Hit q/Q/Esc to exit.") # ----------------------------------------- # Main Loop # while there are images ... # ----------------------------------------- while True: # Capture frame-by-frame ret, capture = camera.read() # if frame is read correctly ret is True if not ret: print("Can't receive frame (stream end?). Exiting ...") break # ----------------------------------------- # Put your image processing code here # ----------------------------------------- # update trackbar variables IMAGE_ID = cv.getTrackbarPos("c/HS/H/S/I", WINDOW_CAMERA1) HSV_THRESHOLD_LOW[0] = cv.getTrackbarPos("HueLowThr", WINDOW_RES) HSV_THRESHOLD_HIGH[0] = cv.getTrackbarPos("HueHighThr", WINDOW_RES) HSV_THRESHOLD_LOW[1] = cv.getTrackbarPos("SatLowThr", WINDOW_RES) HSV_THRESHOLD_HIGH[1] = cv.getTrackbarPos("SatHighThr", WINDOW_RES) AREA_MIN = cv.getTrackbarPos("Min. Area", WINDOW_RES) HUE_CENTER = cv.getTrackbarPos("Hue Center", WINDOW_RES) hsv = cv.cvtColor(capture, cv.COLOR_BGR2HSV_FULL) # color transform to HSV (Hue scaled 180ยบ -> 255) hue, sat, intensity = cv.split(hsv) # Normalize HUE channel (selected hue value in the middle(128)) lookUpTable = np.zeros(256, dtype=np.uint8) for i in range(len(lookUpTable)): lookUpTable[i] = (i+128-HUE_CENTER) % 256 hue = cv.LUT(hue, lookUpTable) hsv = cv.merge((hue, sat, intensity)) # Hue shifted HSV image for inRange segmentation res = cv.inRange(hsv, tuple(HSV_THRESHOLD_LOW), tuple(HSV_THRESHOLD_HIGH)) # morphological filter(opening / closing) kernel = cv.getStructuringElement(cv.MORPH_CROSS, (3, 3)) # [[0,1,0], [1,1,1], [0,1,0]] res = cv.morphologyEx(res, cv.MORPH_OPEN, kernel, iterations=2) res = cv.morphologyEx(res, cv.MORPH_CLOSE, kernel, iterations=2) # find contours edge_image = cv.Canny(res, threshold1=50, threshold2=200) # find contours contours, hierarchy = cv.findContours(edge_image, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE) # Filter small contours contours_filtered = list() # empty list (remember tuples are immutable) # search for the biggest area contour id_max = 0; area_max = 0.0 contours_filtered = list() for idx, cnt in enumerate(contours): area = cv.contourArea(cnt) if area > AREA_MIN: contours_filtered.append(cnt) if area > area_max: id_max = idx; area_max = area # Calculates Convex Hull of the bigest contour (if any) if len(contours_filtered) > 0: # Convex Hull indexes clockwise convexhull = cv.convexHull(contours[id_max], clockwise=True, returnPoints=False) convexitydefects = cv.convexityDefects(contours[id_max], convexhull) # calculates mean of convexity defects convexity = 0.0 # covexity shape descriptor (mean of convexitydefects) for item in convexitydefects: convexity += item[0,3]/256.0 convexity /= len(convexitydefects) print(f"Convexity Defect: {convexity}") # ----------------------------------------- # Put your visualization code here # ----------------------------------------- if IMAGE_ID == 1: dispImage = hsv elif IMAGE_ID == 2: dispImage = hue elif IMAGE_ID == 3: dispImage = sat elif IMAGE_ID == 4: dispImage = intensity else: dispImage = capture # And Select here the image to be used to query the Gray/RGB value under cursor if cv.getTrackbarPos("(p)Im/Hue", WINDOW_CAMERA1) == 1: queryImage = hue else: queryImage = None # draws overlay with pixel color under cursor on capture image dispImage = drawOverlay(dispImage, alpha=float(ALPHA) / 100, imageQuery=queryImage) # Bold Draw bigger contour and convexhull if len(contours_filtered)>0: cv.drawContours(dispImage, contours, id_max, (0, 255, 0), thickness=1, lineType=cv.LINE_AA) # Draws convex hull for the biggest contour for id in convexhull[:-1,0]: cv.line(dispImage, tuple(contours[id_max][id,0,:]), tuple(contours[id_max][id+1,0,:]), (0, 0, 255), thickness=2, lineType=cv.LINE_AA) cv.imshow(WINDOW_CAMERA1, dispImage) # Display the resulting frame cv.imshow(WINDOW_RES, res) # Display the processed frame # check keystroke to exit (image window must be on focus) key = cv.pollKey() if key == ord('q') or key == ord('Q') or key == 27 or EXIT: break elif key == KEY_F5 or key == ord(' '): filename = f"Image{ID_FILE}.jpg" print(f"Saving image window in file: {filename}") cv.imwrite(filename, capture) # save window image ID_FILE += 1 # End while (main loop) # ----------------------------------------- # free windows and camera resources # ----------------------------------------- cv.destroyAllWindows() if camera.isOpened(): camera.release()