Mercurial Hosting > traffic-intelligence
view scripts/polytracktopdtv.py @ 807:52aa03260f03 opencv3
reversed all code to OpenCV 2.4.13
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Fri, 10 Jun 2016 15:26:19 -0400 |
parents | 3058e00887bc |
children | 933670761a57 |
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#! /usr/bin/env python from pdtv import TsaiCamera, ZipVideo, SyncedVideos, TrackSet, Track, State import sys, os, datetime, argparse import shutil import sqlite3 import zipfile import utils import cvutils import cv2 def zipFolder(inputFolder, outputFile): '''Method to compress the content of the inputFolder in the outputFile''' zip = zipfile.ZipFile(outputFile, 'w') for root, dirs, files in os.walk(inputFolder): for file in files: zip.write(root+file, file) zip.close() def getTypeDict(cursor): '''Return a dictionnary with integer key and associated type string i.e.: "0" -> "unknown" "1" -> "car" "2" -> "pedestrians" "3" -> "motorcycle" "4" -> "bicycle" "5" -> "bus" "6" -> "truck" ... and other type if the objects_type table is defined in SQLite''' typeDict = dict() cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='objects_type'") data = cursor.fetchone() if(data is None): typeDict["0"] = "unknown" typeDict["1"] = "car" typeDict["2"] = "pedestrians" typeDict["3"] = "motorcycle" typeDict["4"] = "bicycle" typeDict["5"] = "bus" typeDict["6"] = "truck" else: cursor.execute("SELECT road_user_type, type_string FROM objects_type") for row in cursor: typeDict[row[0]]= row[1] return typeDict def extractFrames(videoFile, framePath, fps, time, firstFrameNum = 0, lastFrameNum = None): '''Method to extract all the frames of the video''' print('Extracting frame') deltaTimestamp = 1000.0/float(fps); time+=datetime.timedelta(microseconds=firstFrameNum*deltaTimestamp*1000) inc = 1000 #How many frame we fetch in the video at a time if lastFrameNum is not None: delta = lastFrameNum-firstFrameNum if delta < inc: inc = delta currentIdx = firstFrameNum frameList = cvutils.getImagesFromVideo(videoFile, firstFrameNum = currentIdx, nFrames = inc) while len(frameList) == inc and inc > 0: for f in frameList: cv2.imwrite(os.path.join(framePath,time.strftime("%Y%m%d-%H%M%S.%f")[:-3]+'.jpg'), f) time += datetime.timedelta(microseconds=deltaTimestamp*1000) currentIdx = currentIdx + inc if lastFrameNum is not None: delta = lastFrameNum-currentIdx if delta < inc: inc = delta if inc: frameList = cvutils.getImagesFromVideo(videoFile, firstFrameNum = currentIdx, nFrames = inc) print('Extracting frame ' + str(currentIdx)) return len(frameList) > 0 def convertDatabase(workDirname, sectionName, sceneFilename = None, databaseFilename = None, videoFilename = None, videoFolderExist = False, firstFrameNum = 0, lastFrameNum = None, cameraCalibrationFilename = None, outputFileName = 'roaduser.json'): ''' Method to convert database from polytrack to PDTV: workDirname is the current working directory sceneFilename is the path to the .cfg file sectionName is the name of the section we want to process in this file videoFolderExist specifiy if we want to reextract the video frame or if they already exist at workdir/videoframes/ firstFrameNum is the first frame we want to extract lastFrameNum is the last frame we want to extract (or None if we want to extract everything) ''' error = False if sceneFilename is not None: scene = utils.SceneParameters.loadConfigFile(os.path.join(workDirname, sceneFilename)) time = scene[sectionName].date inputDb = os.path.join(workDirname, scene[sectionName].databaseFilename) videoFile = os.path.join(workDirname, scene[sectionName].videoFilename) if databaseFilename is not None: inputDb = os.path.join(workDirname, databaseFilename) if videoFilename is not None: videoFile = os.path.join(workDirname, videoFilename) # elif videoFolderExist == False: # print('No video path specified') # error = True videoFolderPath = os.path.join(workDirname, "videoframes/") fileName = sectionName if videoFile is not None: fps = cvutils.getFPS(videoFile) print('Video should run at ' + str(fps) + ' fps') deltaTimestamp = 1000.0/float(fps); if videoFolderExist == False: if os.path.exists(videoFolderPath): shutil.rmtree(videoFolderPath) utils.mkdir(videoFolderPath) if extractFrames(videoFile, videoFolderPath, fps, time, firstFrameNum, lastFrameNum) == 0: print("Error. Frame were not extracted") error = True if not error: masterTimestamp = 0.0 masterTimestampList = list() video_timestringsList = list() frameNumberToMasterTimestamp = dict() for r,d,f in os.walk(videoFolderPath): i = firstFrameNum for files in f: name, ext = os.path.splitext(files) video_timestringsList.append(name) masterTimestampList.append(masterTimestamp) frameNumberToMasterTimestamp[i] = masterTimestamp i = i +1 masterTimestamp = masterTimestamp+deltaTimestamp inputZipVideoName = fileName+".zip" print('Zipping files...') if not os.path.exists(inputZipVideoName) or not videoFolderExist: zipFolder(videoFolderPath, inputZipVideoName) print('Zipping files...Done.') #We generate the structure for ZipVideo if cameraCalibrationFilename is not None: calibrationFile = cameraCalibrationFilename else: calibrationFile = 'calib.json' zipVideo = ZipVideo(video_zip_file=inputZipVideoName, time_offset=0.0, time_scale=1.0, master_timestamps=masterTimestampList, calibration_file=calibrationFile) zipVideo.save(os.path.join(workDirname, 'video.json')) print('ZipVideo saved') obj = SyncedVideos(master_timestamps = [masterTimestamp], video_timestrings = [video_timestringsList], video_files = ['video.json'], fps=fps) obj.save(os.path.join(workDirname, 'syncedvideo.json')) print('SyncedVideos saved') print('Opening db') connection = sqlite3.connect(inputDb) cursor = connection.cursor() #Tracket database trackset = TrackSet(synced_file = ['syncedvideo.json']) #1) We build the type index dictionnary typeDict = getTypeDict(cursor) idToTrackDict = dict() #2) We read the object database cursor.execute("SELECT object_id, road_user_type FROM objects") for row in cursor: objectId = row[0] objectType = row[1] t = Track(type=typeDict.get(objectType, "unknown")) idToTrackDict[objectId] = t; trackset.append(t) print('Reading boundingbox table') #3) We read the bounding box table cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='bounding_boxes'") data = cursor.fetchone() if data is None: print('No bounding box table. Maybe it was not generated ?') else: cursor.execute("SELECT object_id, frame_number, x_top_left, y_top_left, x_bottom_right, y_bottom_right FROM bounding_boxes") for row in cursor: objectId = row[0] frameNumber = row[1] x_top_left = row[2] y_top_left = row[3] x_bottom_right = row[4] y_bottom_right = row[5] idToTrackDict[objectId].append(State(frame=int(frameNumber), world_position = [0.,0.], master_timestamp=frameNumberToMasterTimestamp[int(frameNumber)], bounding_boxes=[[(x_top_left, x_bottom_right), (y_top_left, y_bottom_right)]])) print('Saving db in json') trackset.save(os.path.join(workDirname, outputFileName)) connection.close() print('Done.') if __name__ == "__main__": parser = argparse.ArgumentParser(description='The program convert polytrack.sqlite database to pdtv bounding boxes', epilog = 'Either the configuration filename or the other parameters (at least video and database filenames) need to be provided.') parser.add_argument('-w', dest = 'workDirname', help = 'use a different work directory', default = "./",type = str) parser.add_argument('--scene', dest = 'sceneFilename', help = 'name of the configuration file', type = str, default = None) parser.add_argument('--section', dest = 'sectionName', help = 'name of the section', type = str, default = None) parser.add_argument('-d', dest = 'databaseFilename', help = 'name of the Sqlite database file', type = str, default = None) parser.add_argument('-i', dest = 'videoFilename', help = 'name of the video file', type = str, default = None) parser.add_argument('-c', dest = 'cameraCalibrationFilename', help = 'name of the camera json file', type = str, default = None) parser.add_argument('-o', dest = 'outputFilename', help = 'name of the output json file', type = str, default = 'roaduser.json') parser.add_argument('-s', dest = 'firstFrameNum', help = 'forced start frame', type = int, default = 0) parser.add_argument('-e', dest = 'lastFrameNum', help = 'forced end frame', type = int, default = None) #parser.add_argument('-t', dest = 'useDatabaseTimestamp', help = 'use the timestamp of the database', default= False, type = bool) parser.add_argument('-u', dest = 'useCurrentVideoFile', help = 'use the previously generated video file', action = 'store_true') args = parser.parse_args() #convertDatabase(args) convertDatabase(args.workDirname, args.sectionName, args.sceneFilename, videoFilename = args.videoFilename, databaseFilename = args.databaseFilename, videoFolderExist = args.useCurrentVideoFile, firstFrameNum = args.firstFrameNum, lastFrameNum = args.lastFrameNum, cameraCalibrationFilename = args.cameraCalibrationFilename, outputFileName=args.outputFilename )