""" Supporting Functions for Computer vision using OpenCV By: Computer Vision Zone Website: https://www.computervision.zone/ """ import cv2 import numpy as np import copy def stackImages(_imgList, cols, scale): """ Stack Images together to display in a single window :param _imgList: list of images to stack :param cols: the num of img in a row :param scale: bigger~1+ ans smaller~1- :return: Stacked Image """ imgList = copy.deepcopy(_imgList) # make the array full by adding blank img, otherwise the openCV can't work totalImages = len(imgList) rows = totalImages // cols if totalImages // cols * cols == totalImages else totalImages // cols + 1 blankImages = cols * rows - totalImages width = imgList[0].shape[1] height = imgList[0].shape[0] imgBlank = np.zeros((height, width, 3), np.uint8) imgList.extend([imgBlank] * blankImages) # resize the images for i in range(cols * rows): imgList[i] = cv2.resize(imgList[i], (0, 0), None, scale, scale) if len(imgList[i].shape) == 2: imgList[i] = cv2.cvtColor(imgList[i], cv2.COLOR_GRAY2BGR) # put the images in a board hor = [imgBlank] * rows for y in range(rows): line = [] for x in range(cols): line.append(imgList[y * cols + x]) hor[y] = np.hstack(line) ver = np.vstack(hor) return ver def cornerRect(img, bbox, l=30, t=5, rt=1, colorR=(255, 0, 255), colorC=(0, 255, 0)): """ :param img: Image to draw on. :param bbox: Bounding box [x, y, w, h] :param l: length of the corner line :param t: thickness of the corner line :param rt: thickness of the rectangle :param colorR: Color of the Rectangle :param colorC: Color of the Corners :return: """ x, y, w, h = bbox x1, y1 = x + w, y + h if rt != 0: cv2.rectangle(img, bbox, colorR, rt) # Top Left x,y cv2.line(img, (x, y), (x + l, y), colorC, t) cv2.line(img, (x, y), (x, y + l), colorC, t) # Top Right x1,y cv2.line(img, (x1, y), (x1 - l, y), colorC, t) cv2.line(img, (x1, y), (x1, y + l), colorC, t) # Bottom Left x,y1 cv2.line(img, (x, y1), (x + l, y1), colorC, t) cv2.line(img, (x, y1), (x, y1 - l), colorC, t) # Bottom Right x1,y1 cv2.line(img, (x1, y1), (x1 - l, y1), colorC, t) cv2.line(img, (x1, y1), (x1, y1 - l), colorC, t) return img def findContours(img, imgPre, minArea=1000, sort=True, filter=0, drawCon=True, c=(255, 0, 0)): """ Finds Contours in an image :param img: Image on which we want to draw :param imgPre: Image on which we want to find contours :param minArea: Minimum Area to detect as valid contour :param sort: True will sort the contours by area (biggest first) :param filter: Filters based on the corner points e.g. 4 = Rectangle or square :param drawCon: draw contours boolean :return: Foudn contours with [contours, Area, BoundingBox, Center] """ conFound = [] imgContours = img.copy() contours, hierarchy = cv2.findContours(imgPre, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) for cnt in contours: area = cv2.contourArea(cnt) if area > minArea: peri = cv2.arcLength(cnt, True) approx = cv2.approxPolyDP(cnt, 0.02 * peri, True) # print(len(approx)) if len(approx) == filter or filter == 0: if drawCon: cv2.drawContours(imgContours, cnt, -1, c, 3) x, y, w, h = cv2.boundingRect(approx) cx, cy = x + (w // 2), y + (h // 2) cv2.rectangle(imgContours, (x, y), (x + w, y + h), c, 2) cv2.circle(imgContours, (x + (w // 2), y + (h // 2)), 5, c, cv2.FILLED) conFound.append({"cnt": cnt, "area": area, "bbox": [x, y, w, h], "center": [cx, cy]}) if sort: conFound = sorted(conFound, key=lambda x: x["area"], reverse=True) return imgContours, conFound def overlayPNG(imgBack, imgFront, pos=[0, 0]): hf, wf, cf = imgFront.shape hb, wb, cb = imgBack.shape *_, mask = cv2.split(imgFront) maskBGRA = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGRA) maskBGR = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR) imgRGBA = cv2.bitwise_and(imgFront, maskBGRA) imgRGB = cv2.cvtColor(imgRGBA, cv2.COLOR_BGRA2BGR) imgMaskFull = np.zeros((hb, wb, cb), np.uint8) imgMaskFull[pos[1]:hf + pos[1], pos[0]:wf + pos[0], :] = imgRGB imgMaskFull2 = np.ones((hb, wb, cb), np.uint8) * 255 maskBGRInv = cv2.bitwise_not(maskBGR) imgMaskFull2[pos[1]:hf + pos[1], pos[0]:wf + pos[0], :] = maskBGRInv imgBack = cv2.bitwise_and(imgBack, imgMaskFull2) imgBack = cv2.bitwise_or(imgBack, imgMaskFull) return imgBack def rotateImage(img, angle, scale=1): h, w = img.shape[:2] center = (w / 2, h / 2) rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=angle, scale=scale) img = cv2.warpAffine(src=img, M=rotate_matrix, dsize=(w, h)) return img def putTextRect(img, text, pos, scale=3, thickness=3, colorT=(255, 255, 255), colorR=(255, 0, 255), font=cv2.FONT_HERSHEY_PLAIN, offset=10, border=None, colorB=(0, 255, 0)): """ Creates Text with Rectangle Background :param img: Image to put text rect on :param text: Text inside the rect :param pos: Starting position of the rect x1,y1 :param scale: Scale of the text :param thickness: Thickness of the text :param colorT: Color of the Text :param colorR: Color of the Rectangle :param font: Font used. Must be cv2.FONT.... :param offset: Clearance around the text :param border: Outline around the rect :param colorB: Color of the outline :return: image, rect (x1,y1,x2,y2) """ ox, oy = pos (w, h), _ = cv2.getTextSize(text, font, scale, thickness) x1, y1, x2, y2 = ox - offset, oy + offset, ox + w + offset, oy - h - offset cv2.rectangle(img, (x1, y1), (x2, y2), colorR, cv2.FILLED) if border is not None: cv2.rectangle(img, (x1, y1), (x2, y2), colorB, border) cv2.putText(img, text, (ox, oy), font, scale, colorT, thickness) return img, [x1, y2, x2, y1] def main(): cap = cv2.VideoCapture(0) while True: success, img = cap.read() img, bbox = putTextRect(img, "CVZone", [50, 50], 2, 2, offset=10, border=5) imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) imgList = [img, img, imgGray, img, imgGray] imgStacked = stackImages(imgList, 2, 0.5) cv2.imshow("stackedImg", imgStacked) cv2.waitKey(1) if __name__ == "__main__": main()