def main(): ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] print(args) if args.sample_stride != -1: config.TEST.sample_stride = args.sample_stride if args.key_frame_interval != -1: config.TEST.KEY_FRAME_INTERVAL = args.key_frame_interval if args.video_shuffle: config.TEST.video_shuffle = args.video_shuffle logger, final_output_path, tb_log_path = create_logger(config.output_path, config.log_path, args.cfg, config.dataset.test_image_set) trained_model = os.path.join(final_output_path, '..', '_'.join( [iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix) test_epoch = config.TEST.test_epoch if args.test_pretrained: trained_model = args.test_pretrained test_epoch = 0 test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, config.dataset.motion_iou_path, ctx, trained_model, test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path, enable_detailed_eval=config.dataset.enable_detailed_eval)
def main(): ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] print args logger, final_output_path, _ = create_logger(config.output_path, config.log_path, args.cfg, config.dataset.test_image_set) test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, config.dataset.motion_iou_path, ctx, os.path.join( final_output_path, '..', '_'.join( [iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path, enable_detailed_eval=config.dataset.enable_detailed_eval)
def main(): ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] print args logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) # test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, # ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch, # args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path) test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, ctx, os.path.join('./model', 'rfcn_vid'), 0, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path, use_philly=args.usePhilly)
def main(): #ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] ctx = [mx.gpu(0), mx.gpu(1), mx.gpu(2), mx.gpu(3)] print args #gpu_nums = [int(i) for i in config.gpus.split(',')] gpu_nums = [0, 1, 2, 3] nms_dets = gpu_nms_wrapper(config.TEST.NMS, gpu_nums[0]) logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) output_path = os.path.join( final_output_path, '..', '+'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix) test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, ctx, output_path, config.TEST.test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path, nms_dets=nms_dets, is_docker=args.is_docker)
def main(): # ctx为gpu(...),其中配置项在yaml配置文件中 ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] # print('ctx:', ctx) print args # config.output_path在yaml文件中定义,cfg为对应的yaml文件路径 logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) # config.dataset.dataset=ImageNetVID test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, config.dataset.motion_iou_path, ctx, os.path.join( final_output_path, '..', '_'.join( [iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path, enable_detailed_eval=config.dataset.enable_detailed_eval)
def main(): ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] print args logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) print "test with params in epoch " + str(config.TEST.test_epoch) test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, ctx, os.path.join( final_output_path, '..', '_'.join( [iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
def main(): ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] print args logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, ctx, os.path.join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), config.TEST.test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
def main(): import mxnet as mx import mxnet.ndarray as nd nd.zeros((1, 3, 600, 1000), mx.gpu(0), dtype=float) print('GPU ok') ctx = [mx.gpu(0)] print(args) logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) test_rcnn(config, config.dataset.dataset, config.dataset.test_image_set, config.dataset.root_path, config.dataset.dataset_path, ctx, os.path.join('model', config.TRAIN.model_prefix), config.TEST.test_epoch, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path)
def main(): ctx = [mx.gpu(int(i)) for i in config.gpus.split(',')] output_dir = "/tmp/res" if not os.path.exists(output_dir): os.mkdir(output_dir) print args logger, final_output_path = create_logger(config.output_path, args.cfg, config.dataset.test_image_set) sets = "/media/indoordesk/653ce34c-0c14-4427-8029-be7afe6d1989/test_sets/ImageSets" sets = "/data2/test_sets/ImageSets" #for epoc in range(1, 30): maps = [] #for epoc in range(1, 30): for file_name in os.listdir(sets): if "_eval" in file_name: continue logger.info("About to test with images:" + file_name) print ("About to test with images:" + file_name) try: res = test_rcnn(config, config.dataset.dataset, file_name.replace(".txt", ""), config.dataset.root_path, config.dataset.dataset_path, config.dataset.motion_iou_path, ctx, join(final_output_path, '..', '_'.join([iset for iset in config.dataset.image_set.split('+')]), config.TRAIN.model_prefix), epoc, args.vis, args.ignore_cache, args.shuffle, config.TEST.HAS_RPN, config.dataset.proposal, args.thresh, logger=logger, output_path=final_output_path, enable_detailed_eval=config.dataset.enable_detailed_eval) with open(join(output_dir, file_name), "a") as f: f.write('epoc: %s res: %s \n' % (epoc, res)) except Exception as e: logger.error(e) print e print maps