import numpy as np import cv2 import random class Printer: #print the labels and show the images #pathRootImgs = path to the root directory containing the images #dictImgsLabels = dictionary relating the path of each image and the annotations def print(self,pathRootImgs, dictImgsLabels, subset_filenames): for key in sorted(dictImgsLabels): if subset_filenames and key not in subset_filenames: continue path = pathRootImgs + '/' + key masks = dictImgsLabels[key].masks occupied = dictImgsLabels[key].occupiedRRs empty = dictImgsLabels[key].emptyRRs unknown = dictImgsLabels[key].unknownRRs print(path) print('\tMasks: ', len(masks), ' Parking Spaces: ', len(occupied) + len(empty) + len(unknown), ' Occupied: ', len(occupied), ' Empty: ', len(empty), ' Unknown: ', len(unknown)) img = cv2.imread(path) original = img.copy() self._printBorders(img, dictImgsLabels[key].annotationsRectangleP1, dictImgsLabels[key].annotationsRectangleP2) self._printPoligons(img, masks) ret, mosaicOccupied, mosaicEmpty, mosaicUnknown = self._printParkingSpaces(original, occupied, empty, unknown) cv2.imshow('Image',img) cv2.imshow('Empty',mosaicEmpty) cv2.imshow('Occupied',mosaicOccupied) cv2.imshow('Unknown',mosaicUnknown) k = cv2.waitKey(0) if k == ord('q'): # wait for 's' key to save and exit break self._printBorders(ret, dictImgsLabels[key].annotationsRectangleP1, dictImgsLabels[key].annotationsRectangleP2) cv2.imshow('Image',ret) k = cv2.waitKey(0) if k == ord('q'): # wait for 's' key to save and exit break def _printBorders(self, img, annotationsRectangleP1, annotationsRectangleP2): cv2.rectangle(img, annotationsRectangleP1, annotationsRectangleP2, (180, 105, 255), 4) def _printPoligons(self, img, poligonsList): imgMask = img.copy() for polys in poligonsList:#one instance may have multiple polygons demarcating it (due of occlusions) for p in polys: pts = np.array(p, np.int32) pts = pts.reshape((1,-1,2)) cv2.drawContours(img, pts, -1, (255,0,0), 2) cv2.drawContours(imgMask, pts, -1, (255,0,0), 2) cv2.drawContours(imgMask, pts, -1, (random.randint(127, 255), random.randint(127, 255), random.randint(127, 255)), -1) cv2.addWeighted(img, 0.5, imgMask, 0.5, 0.0,img) return def _printParkingSpaces(self, img, occupiedRRs, emptyRRs, unknownRRs = []): ret = img.copy() occupiedImgs = list() emptyImgs = list() unknownImgs = list() imgsWidth = 96 imgsHeight = 96 for rro in occupiedRRs: occupiedImgs.append(self.crop_minAreaRect(img, ((rro[0], rro[1]),(rro[2], rro[3]), rro[4]), imgsWidth)) box = cv2.boxPoints(((rro[0], rro[1]),(rro[2], rro[3]), rro[4])) box = np.int0(box) cv2.drawContours(ret, [box], -1, (0,0,255), 2) for rre in emptyRRs: emptyImgs.append(self.crop_minAreaRect(img, ((rre[0], rre[1]),(rre[2], rre[3]), rre[4]), imgsWidth)) box = cv2.boxPoints(((rre[0], rre[1]),(rre[2], rre[3]), rre[4])) box = np.int0(box) cv2.drawContours(ret, [box], -1, (0,255,0), 2) for rru in unknownRRs: unknownImgs.append(self.crop_minAreaRect(img, ((rru[0], rru[1]),(rru[2], rru[3]), rru[4]), imgsWidth)) box = cv2.boxPoints(((rru[0], rru[1]),(rru[2], rru[3]), rru[4])) box = np.int0(box) cv2.drawContours(ret, [box], -1, (255,0,0), 2) mosaicOccupied = self._drawMosaic(occupiedImgs, imgsWidth, imgsHeight, mosaicWidth = 576) mosaicEmpty = self._drawMosaic(emptyImgs, imgsWidth, imgsHeight, mosaicWidth = 576) mosaicUnknown = self._drawMosaic(unknownImgs, imgsWidth, imgsHeight, mosaicWidth = 576) return ret, mosaicOccupied, mosaicEmpty, mosaicUnknown def _drawMosaic(self, images, imgsWidth, imgsHeight ,mosaicWidth = 576): numImgs = len(images) imgsByLine = mosaicWidth/imgsWidth numCols = numImgs/imgsByLine if numImgs % imgsByLine != 0: numCols = numCols + 1; if numCols == 0: numCols = 1 mosaic = np.zeros((int(numCols*imgsHeight), mosaicWidth,3), np.uint8) y_offset = 0 x_offset = 0; for img in images: mosaic[y_offset:y_offset+img.shape[0], x_offset:x_offset+img.shape[1]] = img x_offset = x_offset + imgsWidth if mosaicWidth - x_offset < imgsWidth: x_offset = 0 y_offset = y_offset + imgsHeight return mosaic def crop_minAreaRect(self, img, rr, size): box = cv2.boxPoints(rr) box = np.int0(box) width = int(rr[1][0]) height = int(rr[1][1]) srcPts = box.astype("float32") dstPts = np.array([[0, height-1], [0, 0], [width-1, 0], [width-1, height-1]], dtype="float32") M = cv2.getPerspectiveTransform(srcPts, dstPts) warped = cv2.warpPerspective(img, M, (width, height)) mx = max(width,height) result = np.zeros((mx,mx,3),np.uint8) cx,cy = (mx - width)//2,(mx - height)//2 result[cy:warped.shape[0]+cy,cx:cx+warped.shape[1]] = warped result = cv2.resize(result, (size,size), interpolation = cv2.INTER_AREA) return result