按照githup上playerkk的工程進行實踐，地址為：https://github.com/playerkk/face-py-faster-rcnn/blob/master/README.md
1.搭建faster rcnn
這個沒什么好說的，參考rbg大神的官網即可，附上地址：https://github.com/rbgirshick/py-faster-rcnn
需要注意的是對于顯卡是1080的，因為faster rcnn是基于老版本的cudnn，所以編譯的時候會出現許多關于cudnn的報錯問題。解決方案推薦的是用caffe中相關的文件替換掉faster rcnn中的相關文件。可參考地址：http://blog.csdn.NET/u010733679/article/details/52221404。
2.克隆工程及下載預訓練參數文件
git clone --recursive https://github.com/playerkk/face-py-faster-rcnn.git 在工程的根目錄下執行：
cd?face-py-faster-rcnn
./data/scripts/fetch_faster_rcnn_models.sh
會在data下出現 faster rcnn models.tgz。
3.下載wider face data數據
網站下載地址為：http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace/
下載三個數據文件到一個目錄中，我選擇的是ubuntu的home目錄下：
如圖所示進行分布。
圖中的最后一個文本文件從該網址下載：https://people.cs.umass.edu/~hzjiang//files/wider_face_train_annot.txt 。按照的是FDDB的格式。
在如圖所示的data目錄下建立symlinks：
會在工程的data目錄下出現鏈接，如上圖所示。
4.下載預訓練的Imagenet模型
在工程目錄下執行上圖所示命令。
接下來就是開始執行訓練的過程：
在工程的根目錄下執行命令：
++++++++++++++++++++++++2017.0224++++++++++++++++++++更新+++++++++++++++++++++++++++
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
更新工程后我的train_net.py文件內容為：
[python] view plaincopy
??????????????????????????import?_init_paths??from?fast_rcnn.train?import?get_training_roidb,?train_net??from?fast_rcnn.config?import?cfg,?cfg_from_file,?cfg_from_list,?get_output_dir??from?datasets.factory?import?get_imdb??import?datasets.imdb??import?caffe??import?argparse??import?pprint??import?numpy?as?np??import?sys????def?parse_args():??????????????parser?=?argparse.ArgumentParser(description='Train?a?Fast?R-CNN?network')??????parser.add_argument('--gpu',?dest='gpu_id',??????????????????????????help='GPU?device?id?to?use?[0]',??????????????????????????default=0,?type=int)??????parser.add_argument('--solver',?dest='solver',??????????????????????????help='solver?prototxt',??????????????????????????default=None,?type=str)??????parser.add_argument('--iters',?dest='max_iters',??????????????????????????help='number?of?iterations?to?train',??????????????????????????default=40000,?type=int)??????parser.add_argument('--weights',?dest='pretrained_model',??????????????????????????help='initialize?with?pretrained?model?weights',??????????????????????????default=None,?type=str)??????parser.add_argument('--cfg',?dest='cfg_file',??????????????????????????help='optional?config?file',??????????????????????????default=None,?type=str)??????parser.add_argument('--imdb',?dest='imdb_name',??????????????????????????help='dataset?to?train?on',??????????????????????????default='voc_2007_trainval',?type=str)??????parser.add_argument('--rand',?dest='randomize',??????????????????????????help='randomize?(do?not?use?a?fixed?seed)',??????????????????????????action='store_true')??????parser.add_argument('--set',?dest='set_cfgs',??????????????????????????help='set?config?keys',?default=None,??????????????????????????nargs=argparse.REMAINDER)????????if?len(sys.argv)?==?1:??????????parser.print_help()??????????sys.exit(1)????????args?=?parser.parse_args()??????return?args????def?combined_roidb(imdb_names):??????def?get_roidb(imdb_name):??????????imdb?=?get_imdb(imdb_name)??????????print?'Loaded?dataset?`{:s}`?for?training'.format(imdb.name)??????????imdb.set_proposal_method(cfg.TRAIN.PROPOSAL_METHOD)??????????print?'Set?proposal?method:?{:s}'.format(cfg.TRAIN.PROPOSAL_METHOD)??????????roidb?=?get_training_roidb(imdb)??????????return?roidb????????roidbs?=?[get_roidb(s)?for?s?in?imdb_names.split('+')]??????roidb?=?roidbs[0]??????if?len(roidbs)?>?1:??????????for?r?in?roidbs[1:]:??????????????roidb.extend(r)??????????imdb?=?datasets.imdb.imdb(imdb_names)??????else:??????????imdb?=?get_imdb(imdb_names)??????return?imdb,?roidb????if?__name__?==?'__main__':??????args?=?parse_args()????????print('Called?with?args:')??????print(args)????????if?args.cfg_file?is?not?None:??????????cfg_from_file(args.cfg_file)??????if?args.set_cfgs?is?not?None:??????????cfg_from_list(args.set_cfgs)????????cfg.GPU_ID?=?args.gpu_id????????print('Using?config:')??????pprint.pprint(cfg)????????if?not?args.randomize:????????????????????np.random.seed(cfg.RNG_SEED)??????????caffe.set_random_seed(cfg.RNG_SEED)??????????????caffe.set_mode_gpu()??????caffe.set_device(args.gpu_id)????????imdb,?roidb?=?combined_roidb(args.imdb_name)??????print?'{:d}?roidb?entries'.format(len(roidb))????????output_dir?=?get_output_dir(imdb)??????print?'Output?will?be?saved?to?`{:s}`'.format(output_dir)????????train_net(args.solver,?roidb,?output_dir,????????????????pretrained_model=args.pretrained_model,????????????????max_iters=args.max_iters)?? face.py:
[python] view plaincopy
????????????????????????????????????import?os??from?datasets.imdb?import?imdb??import?datasets.ds_utils?as?ds_utils??import?xml.etree.ElementTree?as?ET??import?numpy?as?np??import?scipy.sparse??import?scipy.io?as?sio??import?utils.cython_bbox??import?cPickle??import?subprocess??import?uuid??from?voc_eval?import?voc_eval??from?fast_rcnn.config?import?cfg??import?cv2??import?PIL????class?face(imdb):??????def?__init__(self,?image_set,?split,?devkit_path):??????????imdb.__init__(self,?'wider')??????????self._image_set?=?image_set???????????????????self._split?=?split???????????????????????????self._devkit_path?=?devkit_path?????????????????????????self._data_path?=?self._devkit_path;??????????self._classes?=?('__background__',????????????????????????????'face')??????????self._class_to_ind?=?dict(zip(self.classes,?xrange(self.num_classes)))??????????self._image_ext?=?['.png']??????????self._image_index,?self._gt_roidb?=?self._load_image_set_index()????????????????????self._roidb_handler?=?self.selective_search_roidb??????????????????????self.config?=?{'cleanup'??:?True,?????????????????????????'use_salt'?:?True,?????????????????????????'top_k'????:?2000}????????????assert?os.path.exists(self._devkit_path),?\??????????????????'Devkit?path?does?not?exist:?{}'.format(self._devkit_path)??????????assert?os.path.exists(self._data_path),?\??????????????????'Path?does?not?exist:?{}'.format(self._data_path)????????def?image_path_at(self,?i):??????????????????????return?self.image_path_from_index(self._image_index[i])????????def?image_path_from_index(self,?index):??????????????????????for?ext?in?self._image_ext:??????????????image_path?=?os.path.join(self._data_path,?index)??????????????if?os.path.exists(image_path):??????????????????break??????????assert?os.path.exists(image_path),?\??????????????????'Path?does?not?exist:?{}'.format(image_path)????????????return?image_path????????def?_load_image_set_index(self):??????????????????????????????????????????????????????????????????????????????????image_set_file?=?self._name?+?'_face_'?+?self._image_set?+?'_annot.txt'??????????image_set_file?=?os.path.join(self._devkit_path,?image_set_file)????????????????????????????????????????????assert?os.path.exists(image_set_file),?\??????????????????'Path?does?not?exist:?{}'.format(image_set_file)????????????image_index?=?[]??????????gt_roidb?=?[]????????????????????with?open(image_set_file)?as?f:????????????????????????????lines?=?f.readlines()????????????????idx?=?0??????????????while?idx?<?len(lines):??????????????????image_name?=?lines[idx].split('\n')[0]??????????????????image_name?=?os.path.join('WIDER_%s/images'?%?self._image_set,?image_name)????????????????????????????????????image_ext?=?os.path.splitext(image_name)[1].lower()????????????????????????????????????assert(image_ext?==?'.png'?or?image_ext?==?'.jpg'?or?image_ext?==?'.jpeg')????????????????????image?=?PIL.Image.open(os.path.join(self._data_path,?image_name))??????????????????imw?=?image.size[0]??????????????????imh?=?image.size[1]????????????????????idx?+=?1??????????????????num_boxes?=?int(lines[idx])??????????????????????????????????????boxes?=?np.zeros((num_boxes,?4),?dtype=np.uint16)??????????????????gt_classes?=?np.zeros((num_boxes),?dtype=np.int32)??????????????????overlaps?=?np.zeros((num_boxes,?self.num_classes),?dtype=np.float32)????????????????????for?i?in?xrange(num_boxes):??????????????????????idx?+=?1??????????????????????coor?=?map(float,?lines[idx].split())????????????????????????x1?=?min(max(coor[0],?0),?imw?-?1)??????????????????????y1?=?min(max(coor[1],?0),?imh?-?1)??????????????????????x2?=?min(max(x1?+?coor[2]?-?1,?0),?imw?-?1)??????????????????????y2?=?min(max(y1?+?coor[3]?-?1,?0),?imh?-?1)????????????????????????if?np.isnan(x1):??????????????????????????x1?=?-1????????????????????????if?np.isnan(y1):??????????????????????????y1?=?-1????????????????????????if?np.isnan(x2):??????????????????????????x2?=?-1????????????????????????if?np.isnan(y2):??????????????????????????y2?=?-1????????????????????????????????????????????????cls?=?self._class_to_ind['face']??????????????????????boxes[i,?:]?=?[x1,?y1,?x2,?y2]??????????????????????gt_classes[i]?=?cls??????????????????????overlaps[i,?cls]?=?1.0????????????????????widths?=?boxes[:,?2]?-?boxes[:,?0]?+?1??????????????????heights?=?boxes[:,?3]?-?boxes[:,?1]?+?1??????????????????keep_idx?=?np.where(np.bitwise_and(widths?>?5,?heights?>?5))????????????????????if?len(keep_idx[0])?<=?0:??????????????????????idx?+=?1??????????????????????continue????????????????????boxes?=?boxes[keep_idx]??????????????????gt_classes?=?gt_classes[keep_idx[0]]??????????????????overlaps?=?overlaps[keep_idx[0],?:]????????????????????????if?not?(boxes[:,?2]?>=?boxes[:,?0]).all():??????????????????????print?boxes??????????????????????print?image_name??????????????????????????????????????assert?(boxes[:,?2]?>=?boxes[:,?0]).all()??????????????????assert?(boxes[:,?3]?>=?boxes[:,?1]).all()????????????????????overlaps?=?scipy.sparse.csr_matrix(overlaps)??????????????????gt_roidb.append({'boxes'?:?boxes,??????????????????????????????????'gt_classes':?gt_classes,??????????????????????????????????'gt_overlaps'?:?overlaps,??????????????????????????????????'flipped'?:?False,??????????????????????????????????'image_name':?image_name})??????????????????image_index.append(image_name)????????????????????idx?+=?1????????????????????????assert(idx?==?len(lines))????????????return?image_index,?gt_roidb????????def?gt_roidb(self):????????????????????????cache_file?=?os.path.join(self.cache_path,?self.name?+?'_gt_roidb.pkl')??????????if?os.path.exists(cache_file):??????????????with?open(cache_file,?'rb')?as?fid:??????????????????roidb?=?cPickle.load(fid)??????????????print?'{}?gt?roidb?loaded?from?{}'.format(self.name,?cache_file)??????????????return?roidb????????????with?open(cache_file,?'wb')?as?fid:??????????????cPickle.dump(self._gt_roidb,?fid,?cPickle.HIGHEST_PROTOCOL)??????????print?'wrote?gt?roidb?to?{}'.format(cache_file)????????????return?self._gt_roidb????????def?selective_search_roidb(self):?????????????????????????cache_file?=?os.path.join(self.cache_path,????????????????????????????????????self.name?+?'_selective_search_roidb.pkl')????????????if?os.path.exists(cache_file):??????????????with?open(cache_file,?'rb')?as?fid:??????????????????roidb?=?cPickle.load(fid)??????????????print?'{}?ss?roidb?loaded?from?{}'.format(self.name,?cache_file)??????????????return?roidb????????????if?self._image_set?!=?'test':??????????????gt_roidb?=?self.gt_roidb()??????????????ss_roidb?=?self._load_selective_search_roidb(gt_roidb)??????????????roidb?=?datasets.imdb.merge_roidbs(gt_roidb,?ss_roidb)??????????else:??????????????roidb?=?self._load_selective_search_roidb(None)??????????????print?len(roidb)????????????with?open(cache_file,?'wb')?as?fid:??????????????cPickle.dump(roidb,?fid,?cPickle.HIGHEST_PROTOCOL)??????????print?'wrote?ss?roidb?to?{}'.format(cache_file)????????????return?roidb????????def?_load_selective_search_roidb(self,?gt_roidb):??????????filename?=?os.path.abspath(os.path.join(self._devkit_path,??????????????????????????????????????????????????self.name?+?'.mat'))??????????assert?os.path.exists(filename),?\?????????????????'Selective?search?data?not?found?at:?{}'.format(filename)????????????raw_data?=?sio.loadmat(filename)['all_boxes'].ravel()????????????box_list?=?[]??????????for?i?in?xrange(raw_data.shape[0]):??????????????boxes?=?raw_data[i][:,?(1,?0,?3,?2)]?-?1??????????????assert?(boxes[:,?2]?>=?boxes[:,?0]).all()??????????????box_list.append(boxes)????????????return?self.create_roidb_from_box_list(box_list,?gt_roidb)????????def?selective_search_IJCV_roidb(self):?????????????????????????cache_file?=?os.path.join(self.cache_path,??????????????????'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.??????????????????format(self.name,?self.config['top_k']))????????????if?os.path.exists(cache_file):??????????????with?open(cache_file,?'rb')?as?fid:??????????????????roidb?=?cPickle.load(fid)??????????????print?'{}?ss?roidb?loaded?from?{}'.format(self.name,?cache_file)??????????????return?roidb????????????gt_roidb?=?self.gt_roidb()??????????ss_roidb?=?self._load_selective_search_IJCV_roidb(gt_roidb)??????????roidb?=?datasets.imdb.merge_roidbs(gt_roidb,?ss_roidb)??????????with?open(cache_file,?'wb')?as?fid:??????????????cPickle.dump(roidb,?fid,?cPickle.HIGHEST_PROTOCOL)??????????print?'wrote?ss?roidb?to?{}'.format(cache_file)????????????return?roidb????????def?_load_selective_search_IJCV_roidb(self,?gt_roidb):??????????IJCV_path?=?os.path.abspath(os.path.join(self.cache_path,?'..',???????????????????????????????????????????????????'selective_search_IJCV_data',???????????????????????????????????????????????????self.name))??????????assert?os.path.exists(IJCV_path),?\?????????????????'Selective?search?IJCV?data?not?found?at:?{}'.format(IJCV_path)????????????top_k?=?self.config['top_k']??????????box_list?=?[]??????????for?i?in?xrange(self.num_images):??????????????filename?=?os.path.join(IJCV_path,?self.image_index[i]?+?'.mat')??????????????raw_data?=?sio.loadmat(filename)??????????????box_list.append((raw_data['boxes'][:top_k,?:]-1).astype(np.uint16))????????????return?self.create_roidb_from_box_list(box_list,?gt_roidb)????????def?_load_face_annotation(self,?index):??????????????????????filename?=?os.path.join(self._data_path,?'Annotations',?index?+?'.mat')????????????data?=?sio.loadmat(filename)????????????num_objs?=?data['gt'].shape[0]????????????boxes?=?np.zeros((num_objs,?4),?dtype=np.uint16)??????????gt_classes?=?np.zeros((num_objs),?dtype=np.int32)??????????overlaps?=?np.zeros((num_objs,?self.num_classes),?dtype=np.float32)??????????????????????for?ix?in?xrange(num_objs):????????????????????????????coor?=?data['gt'][ix,?:]??????????????x1?=?float(coor[0])?-?1??????????????y1?=?float(coor[1])?-?1??????????????x2?=?float(coor[2])?-?1??????????????y2?=?float(coor[3])?-?1??????????????cls?=?self._class_to_ind['face']??????????????boxes[ix,?:]?=?[x1,?y1,?x2,?y2]??????????????gt_classes[ix]?=?cls??????????????overlaps[ix,?cls]?=?1.0????????????overlaps?=?scipy.sparse.csr_matrix(overlaps)????????????if?not?(boxes[:,?2]?>=?boxes[:,?0]).all():??????????????print?boxes??????????????print?filename????????????assert?(boxes[:,?2]?>=?boxes[:,?0]).all()????????????return?{'boxes'?:?boxes,??????????????????'gt_classes':?gt_classes,??????????????????'gt_overlaps'?:?overlaps,??????????????????'flipped'?:?False}????????def?_write_inria_results_file(self,?all_boxes):??????????use_salt?=?self.config['use_salt']??????????comp_id?=?'comp4'??????????if?use_salt:??????????????comp_id?+=?'-{}'.format(os.getpid())??????????????????????path?=?os.path.join(self._devkit_path,?'results',?self.name,?comp_id?+?'_')??????????for?cls_ind,?cls?in?enumerate(self.classes):??????????????if?cls?==?'__background__':??????????????????continue??????????????print?'Writing?{}?results?file'.format(cls)??????????????filename?=?path?+?'det_'?+?self._image_set?+?'_'?+?cls?+?'.txt'??????????????with?open(filename,?'wt')?as?f:??????????????????for?im_ind,?index?in?enumerate(self.image_index):??????????????????????dets?=?all_boxes[cls_ind][im_ind]??????????????????????if?dets?==?[]:??????????????????????????continue????????????????????????????????????????????for?k?in?xrange(dets.shape[0]):??????????????????????????f.write('{:s}?{:.3f}?{:.1f}?{:.1f}?{:.1f}?{:.1f}\n'.??????????????????????????????????format(index,?dets[k,?-1],?????????????????????????????????????????dets[k,?0]?+?1,?dets[k,?1]?+?1,?????????????????????????????????????????dets[k,?2]?+?1,?dets[k,?3]?+?1))??????????return?comp_id????????def?_do_matlab_eval(self,?comp_id,?output_dir='output'):??????????rm_results?=?self.config['cleanup']????????????path?=?os.path.join(os.path.dirname(__file__),??????????????????????????????'VOCdevkit-matlab-wrapper')??????????cmd?=?'cd?{}?&&?'.format(path)??????????cmd?+=?'{:s}?-nodisplay?-nodesktop?'.format(datasets.MATLAB)??????????cmd?+=?'-r?"dbstop?if?error;?'??????????cmd?+=?'setenv(\'LC_ALL\',\'C\');?voc_eval(\'{:s}\',\'{:s}\',\'{:s}\',\'{:s}\',{:d});?quit;"'?\?????????????????.format(self._devkit_path,?comp_id,?????????????????????????self._image_set,?output_dir,?int(rm_results))??????????print('Running:\n{}'.format(cmd))??????????status?=?subprocess.call(cmd,?shell=True)????????def?evaluate_detections(self,?all_boxes,?output_dir):??????????comp_id?=?self._write_inria_results_file(all_boxes)??????????self._do_matlab_eval(comp_id,?output_dir)????????def?competition_mode(self,?on):??????????if?on:??????????????self.config['use_salt']?=?False??????????????self.config['cleanup']?=?False??????????else:??????????????self.config['use_salt']?=?True??????????????self.config['cleanup']?=?True????if?__name__?==?'__main__':??????d?=?datasets.inria('train',?'')??????res?=?d.roidb??????from?IPython?import?embed;?embed()?? +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
之后在命令行中輸入： voole@zhx:~/face-py-faster-rcnn$ ./experiments/scripts/faster_rcnn_end2end.sh 0 VGG16 wider
輸出：
問題已經得到解決了：原因是因為我安裝的easydict的版本是1.4，即使我配置了faster_rcnn_end2end.yml，但是easydict并沒有將參數傳給train_net.py，所以才會出現上述問題，解決方案就是升級你的easydict。
總結
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