python类SUBCLS_NAME的实例源码

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_pascal3d_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'test':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def evaluate_detections(self, all_boxes, output_dir):
        # load the mapping for subcalss the azimuth (viewpoint)
        filename = os.path.join(self._pascal3d_path, cfg.SUBCLS_NAME, 'mapping.txt')
        assert os.path.exists(filename), \
                'Path does not exist: {}'.format(filename)

        mapping = np.zeros(self._num_subclasses, dtype=np.float)
        with open(filename) as f:
            for line in f:
                words = line.split()
                subcls = int(words[0])
                mapping[subcls] = float(words[2])

        for cls_ind, cls in enumerate(self.classes):
            if cls == '__background__':
                continue
            print 'Writing {} VOC results file'.format(cls)
            filename = os.path.join(output_dir, 'det_' + self._image_set + '_' + cls + '.txt')
            print filename

            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
                    # the VOCdevkit expects 1-based indices
                    for k in xrange(dets.shape[0]):
                        subcls = int(dets[k, 5])
                        cls_name = self.classes[self.subclass_mapping[subcls]]
                        assert (cls_name == cls), 'subclass not in class'
                        azimuth = mapping[subcls]
                        f.write('{:s} {:.3f} {:.3f} {:.1f} {:.1f} {:.1f} {:.1f}\n'.
                                format(index, dets[k, 4], azimuth,
                                       dets[k, 0] + 1, dets[k, 1] + 1,
                                       dets[k, 2] + 1, dets[k, 3] + 1))

    # evaluate detection results

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_imagenet3d_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_kitti_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'testing':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            if self._image_set == 'trainval':
                model = cfg.REGION_PROPOSAL + '_trainval/'
            else:
                model = cfg.REGION_PROPOSAL + '_train/'
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL + '_trainval/'
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_pascal3d_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'test':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def evaluate_detections(self, all_boxes, output_dir):
        # load the mapping for subcalss the azimuth (viewpoint)
        filename = os.path.join(self._pascal3d_path, cfg.SUBCLS_NAME, 'mapping.txt')
        assert os.path.exists(filename), \
                'Path does not exist: {}'.format(filename)

        mapping = np.zeros(self._num_subclasses, dtype=np.float)
        with open(filename) as f:
            for line in f:
                words = line.split()
                subcls = int(words[0])
                mapping[subcls] = float(words[2])

        for cls_ind, cls in enumerate(self.classes):
            if cls == '__background__':
                continue
            print 'Writing {} VOC results file'.format(cls)
            filename = os.path.join(output_dir, 'det_' + self._image_set + '_' + cls + '.txt')
            print filename

            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
                    # the VOCdevkit expects 1-based indices
                    for k in xrange(dets.shape[0]):
                        subcls = int(dets[k, 5])
                        cls_name = self.classes[self.subclass_mapping[subcls]]
                        assert (cls_name == cls), 'subclass not in class'
                        azimuth = mapping[subcls]
                        f.write('{:s} {:.3f} {:.3f} {:.1f} {:.1f} {:.1f} {:.1f}\n'.
                                format(index, dets[k, 4], azimuth,
                                       dets[k, 0] + 1, dets[k, 1] + 1,
                                       dets[k, 2] + 1, dets[k, 3] + 1))

    # evaluate detection results

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_imagenet3d_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_kitti_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'testing':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            if self._image_set == 'trainval':
                model = cfg.REGION_PROPOSAL + '_trainval/'
            else:
                model = cfg.REGION_PROPOSAL + '_train/'
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL + '_trainval/'
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_pascal3d_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'test':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def evaluate_detections(self, all_boxes, output_dir):
        # load the mapping for subcalss the azimuth (viewpoint)
        filename = os.path.join(self._pascal3d_path, cfg.SUBCLS_NAME, 'mapping.txt')
        assert os.path.exists(filename), \
                'Path does not exist: {}'.format(filename)

        mapping = np.zeros(self._num_subclasses, dtype=np.float)
        with open(filename) as f:
            for line in f:
                words = line.split()
                subcls = int(words[0])
                mapping[subcls] = float(words[2])

        for cls_ind, cls in enumerate(self.classes):
            if cls == '__background__':
                continue
            print 'Writing {} VOC results file'.format(cls)
            filename = os.path.join(output_dir, 'det_' + self._image_set + '_' + cls + '.txt')
            print filename

            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
                    # the VOCdevkit expects 1-based indices
                    for k in xrange(dets.shape[0]):
                        subcls = int(dets[k, 5])
                        cls_name = self.classes[self.subclass_mapping[subcls]]
                        assert (cls_name == cls), 'subclass not in class'
                        azimuth = mapping[subcls]
                        f.write('{:s} {:.3f} {:.3f} {:.1f} {:.1f} {:.1f} {:.1f}\n'.
                                format(index, dets[k, 4], azimuth,
                                       dets[k, 0] + 1, dets[k, 1] + 1,
                                       dets[k, 2] + 1, dets[k, 3] + 1))

    # evaluate detection results

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_imagenet3d_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_kitti_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'testing':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            if self._image_set == 'trainval':
                model = cfg.REGION_PROPOSAL + '_trainval/'
            else:
                model = cfg.REGION_PROPOSAL + '_train/'
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL + '_trainval/'
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        #cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_NAME + '_gt_roidb.pkl')
        cache_file = os.path.join(self.cache_path, self.name + '_' + '_gt_roidb.pkl')
        # the path is: .../Faster-RCNN_TF/data/cache/building_train_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

        gt_roidb = [self._load_building_annotation(index)
                    for index in self.image_index]

        """if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))"""

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

    # ---------------------------------------------------------------------------------------------------------------- #

    ############## ??

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        #cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_NAME + '_gt_roidb.pkl')
        cache_file = os.path.join(self.cache_path, self.name + '_' + '_gt_roidb.pkl')
        # the path is: .../Faster-RCNN_TF/data/cache/building_train_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

        gt_roidb = [self._load_building_annotation(index)
                    for index in self.image_index]

        """if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))"""

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

    # ---------------------------------------------------------------------------------------------------------------- #

    ############## ??

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_pascal3d_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'test':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_kitti_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        #cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_NAME + '_gt_roidb.pkl')
        cache_file = os.path.join(self.cache_path, self.name + '_' + '_gt_roidb.pkl')
        # the path is: .../Faster-RCNN_TF/data/cache/building_train_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

        gt_roidb = [self._load_building_annotation(index)
                    for index in self.image_index]

        """if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))"""

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

    # ---------------------------------------------------------------------------------------------------------------- #

    ############## ??

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_imagenet3d_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'testing':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            if self._image_set == 'trainval':
                model = cfg.REGION_PROPOSAL + '_trainval/'
            else:
                model = cfg.REGION_PROPOSAL + '_train/'
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL + '_trainval/'
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_pascal3d_voxel_exemplar_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb

def region_proposal_roidb(self):
        """
        Return the database of regions of interest.
        Ground-truth ROIs are also included.

        This function loads/saves from/to a cache file to speed up future calls.
        """
        cache_file = os.path.join(self.cache_path,
                                  self.name + '_' + cfg.SUBCLS_NAME + '_' + cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')

        if os.path.exists(cache_file):
            with open(cache_file, 'rb') as fid:
                roidb = cPickle.load(fid)
            print '{} roidb loaded from {}'.format(self.name, cache_file)
            return roidb

        if self._image_set != 'test':
            gt_roidb = self.gt_roidb()

            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
            print 'Region proposal network boxes loaded'
            roidb = datasets.imdb.merge_roidbs(rpn_roidb, gt_roidb)
        else:
            print 'Loading region proposal network boxes...'
            model = cfg.REGION_PROPOSAL
            roidb = self._load_rpn_roidb(None, model)
            print 'Region proposal network boxes loaded'

        print '{} region proposals per image'.format(self._num_boxes_proposal / len(self.image_index))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote roidb to {}'.format(cache_file)

        return roidb

def evaluate_detections(self, all_boxes, output_dir):
        # load the mapping for subcalss the azimuth (viewpoint)
        filename = os.path.join(self._pascal3d_path, cfg.SUBCLS_NAME, 'mapping.txt')
        assert os.path.exists(filename), \
                'Path does not exist: {}'.format(filename)

        mapping = np.zeros(self._num_subclasses, dtype=np.float)
        with open(filename) as f:
            for line in f:
                words = line.split()
                subcls = int(words[0])
                mapping[subcls] = float(words[2])

        for cls_ind, cls in enumerate(self.classes):
            if cls == '__background__':
                continue
            print 'Writing {} VOC results file'.format(cls)
            filename = os.path.join(output_dir, 'det_' + self._image_set + '_' + cls + '.txt')
            print filename

            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
                    # the VOCdevkit expects 1-based indices
                    for k in xrange(dets.shape[0]):
                        subcls = int(dets[k, 5])
                        cls_name = self.classes[self.subclass_mapping[subcls]]
                        assert (cls_name == cls), 'subclass not in class'
                        azimuth = mapping[subcls]
                        f.write('{:s} {:.3f} {:.3f} {:.1f} {:.1f} {:.1f} {:.1f}\n'.
                                format(index, dets[k, 4], azimuth,
                                       dets[k, 0] + 1, dets[k, 1] + 1,
                                       dets[k, 2] + 1, dets[k, 3] + 1))

    # evaluate detection results

def gt_roidb(self):
        """
        Return the database of ground-truth regions of interest.

        This function loads/saves from/to a cache file to speed up future calls.
        """

        cache_file = os.path.join(self.cache_path, self.name + '_' + cfg.SUBCLS_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

        gt_roidb = [self._load_imagenet3d_annotation(index)
                    for index in self.image_index]

        if cfg.IS_RPN:
            # print out recall
            for i in xrange(1, self.num_classes):
                print '{}: Total number of boxes {:d}'.format(self.classes[i], self._num_boxes_all[i])
                print '{}: Number of boxes covered {:d}'.format(self.classes[i], self._num_boxes_covered[i])
                print '{}: Recall {:f}'.format(self.classes[i], float(self._num_boxes_covered[i]) / float(self._num_boxes_all[i]))

        with open(cache_file, 'wb') as fid:
            cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)
        print 'wrote gt roidb to {}'.format(cache_file)

        return gt_roidb