diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 000000000..ba734d257
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1 @@
+recursive-include faster_rcnn *
\ No newline at end of file
diff --git a/demo.py b/demo.py
deleted file mode 100644
index af78b0986..000000000
--- a/demo.py
+++ /dev/null
@@ -1,380 +0,0 @@
-# --------------------------------------------------------
-# Tensorflow Faster R-CNN
-# Licensed under The MIT License [see LICENSE for details]
-# Written by Jiasen Lu, Jianwei Yang, based on code from Ross Girshick
-# --------------------------------------------------------
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import _init_paths
-import os
-import sys
-import numpy as np
-import argparse
-import pprint
-import pdb
-import time
-import cv2
-import torch
-from torch.autograd import Variable
-import torch.nn as nn
-import torch.optim as optim
-
-import torchvision.transforms as transforms
-import torchvision.datasets as dset
-from scipy.misc import imread
-from roi_data_layer.roidb import combined_roidb
-from roi_data_layer.roibatchLoader import roibatchLoader
-from model.utils.config import cfg, cfg_from_file, cfg_from_list, get_output_dir
-from model.rpn.bbox_transform import clip_boxes
-# from model.nms.nms_wrapper import nms
-from model.roi_layers import nms
-from model.rpn.bbox_transform import bbox_transform_inv
-from model.utils.net_utils import save_net, load_net, vis_detections
-from model.utils.blob import im_list_to_blob
-from model.faster_rcnn.vgg16 import vgg16
-from model.faster_rcnn.resnet import resnet
-import pdb
-
-try:
-    xrange          # Python 2
-except NameError:
-    xrange = range  # Python 3
-
-
-def parse_args():
-  """
-  Parse input arguments
-  """
-  parser = argparse.ArgumentParser(description='Train a Fast R-CNN network')
-  parser.add_argument('--dataset', dest='dataset',
-                      help='training dataset',
-                      default='pascal_voc', type=str)
-  parser.add_argument('--cfg', dest='cfg_file',
-                      help='optional config file',
-                      default='cfgs/vgg16.yml', type=str)
-  parser.add_argument('--net', dest='net',
-                      help='vgg16, res50, res101, res152',
-                      default='res101', type=str)
-  parser.add_argument('--set', dest='set_cfgs',
-                      help='set config keys', default=None,
-                      nargs=argparse.REMAINDER)
-  parser.add_argument('--load_dir', dest='load_dir',
-                      help='directory to load models',
-                      default="/srv/share/jyang375/models")
-  parser.add_argument('--image_dir', dest='image_dir',
-                      help='directory to load images for demo',
-                      default="images")
-  parser.add_argument('--cuda', dest='cuda',
-                      help='whether use CUDA',
-                      action='store_true')
-  parser.add_argument('--mGPUs', dest='mGPUs',
-                      help='whether use multiple GPUs',
-                      action='store_true')
-  parser.add_argument('--cag', dest='class_agnostic',
-                      help='whether perform class_agnostic bbox regression',
-                      action='store_true')
-  parser.add_argument('--parallel_type', dest='parallel_type',
-                      help='which part of model to parallel, 0: all, 1: model before roi pooling',
-                      default=0, type=int)
-  parser.add_argument('--checksession', dest='checksession',
-                      help='checksession to load model',
-                      default=1, type=int)
-  parser.add_argument('--checkepoch', dest='checkepoch',
-                      help='checkepoch to load network',
-                      default=1, type=int)
-  parser.add_argument('--checkpoint', dest='checkpoint',
-                      help='checkpoint to load network',
-                      default=10021, type=int)
-  parser.add_argument('--bs', dest='batch_size',
-                      help='batch_size',
-                      default=1, type=int)
-  parser.add_argument('--vis', dest='vis',
-                      help='visualization mode',
-                      action='store_true')
-  parser.add_argument('--webcam_num', dest='webcam_num',
-                      help='webcam ID number',
-                      default=-1, type=int)
-
-  args = parser.parse_args()
-  return args
-
-lr = cfg.TRAIN.LEARNING_RATE
-momentum = cfg.TRAIN.MOMENTUM
-weight_decay = cfg.TRAIN.WEIGHT_DECAY
-
-def _get_image_blob(im):
-  """Converts an image into a network input.
-  Arguments:
-    im (ndarray): a color image in BGR order
-  Returns:
-    blob (ndarray): a data blob holding an image pyramid
-    im_scale_factors (list): list of image scales (relative to im) used
-      in the image pyramid
-  """
-  im_orig = im.astype(np.float32, copy=True)
-  im_orig -= cfg.PIXEL_MEANS
-
-  im_shape = im_orig.shape
-  im_size_min = np.min(im_shape[0:2])
-  im_size_max = np.max(im_shape[0:2])
-
-  processed_ims = []
-  im_scale_factors = []
-
-  for target_size in cfg.TEST.SCALES:
-    im_scale = float(target_size) / float(im_size_min)
-    # Prevent the biggest axis from being more than MAX_SIZE
-    if np.round(im_scale * im_size_max) > cfg.TEST.MAX_SIZE:
-      im_scale = float(cfg.TEST.MAX_SIZE) / float(im_size_max)
-    im = cv2.resize(im_orig, None, None, fx=im_scale, fy=im_scale,
-            interpolation=cv2.INTER_LINEAR)
-    im_scale_factors.append(im_scale)
-    processed_ims.append(im)
-
-  # Create a blob to hold the input images
-  blob = im_list_to_blob(processed_ims)
-
-  return blob, np.array(im_scale_factors)
-
-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.USE_GPU_NMS = args.cuda
-
-  print('Using config:')
-  pprint.pprint(cfg)
-  np.random.seed(cfg.RNG_SEED)
-
-  # train set
-  # -- Note: Use validation set and disable the flipped to enable faster loading.
-
-  input_dir = args.load_dir + "/" + args.net + "/" + args.dataset
-  if not os.path.exists(input_dir):
-    raise Exception('There is no input directory for loading network from ' + input_dir)
-  load_name = os.path.join(input_dir,
-    'faster_rcnn_{}_{}_{}.pth'.format(args.checksession, args.checkepoch, args.checkpoint))
-
-  pascal_classes = np.asarray(['__background__',
-                       'aeroplane', 'bicycle', 'bird', 'boat',
-                       'bottle', 'bus', 'car', 'cat', 'chair',
-                       'cow', 'diningtable', 'dog', 'horse',
-                       'motorbike', 'person', 'pottedplant',
-                       'sheep', 'sofa', 'train', 'tvmonitor'])
-
-  # initilize the network here.
-  if args.net == 'vgg16':
-    fasterRCNN = vgg16(pascal_classes, pretrained=False, class_agnostic=args.class_agnostic)
-  elif args.net == 'res101':
-    fasterRCNN = resnet(pascal_classes, 101, pretrained=False, class_agnostic=args.class_agnostic)
-  elif args.net == 'res50':
-    fasterRCNN = resnet(pascal_classes, 50, pretrained=False, class_agnostic=args.class_agnostic)
-  elif args.net == 'res152':
-    fasterRCNN = resnet(pascal_classes, 152, pretrained=False, class_agnostic=args.class_agnostic)
-  else:
-    print("network is not defined")
-    pdb.set_trace()
-
-  fasterRCNN.create_architecture()
-
-  print("load checkpoint %s" % (load_name))
-  if args.cuda > 0:
-    checkpoint = torch.load(load_name)
-  else:
-    checkpoint = torch.load(load_name, map_location=(lambda storage, loc: storage))
-  fasterRCNN.load_state_dict(checkpoint['model'])
-  if 'pooling_mode' in checkpoint.keys():
-    cfg.POOLING_MODE = checkpoint['pooling_mode']
-
-
-  print('load model successfully!')
-
-  # pdb.set_trace()
-
-  print("load checkpoint %s" % (load_name))
-
-  # initilize the tensor holder here.
-  im_data = torch.FloatTensor(1)
-  im_info = torch.FloatTensor(1)
-  num_boxes = torch.LongTensor(1)
-  gt_boxes = torch.FloatTensor(1)
-
-  # ship to cuda
-  if args.cuda > 0:
-    im_data = im_data.cuda()
-    im_info = im_info.cuda()
-    num_boxes = num_boxes.cuda()
-    gt_boxes = gt_boxes.cuda()
-
-  # make variable
-  im_data = Variable(im_data, volatile=True)
-  im_info = Variable(im_info, volatile=True)
-  num_boxes = Variable(num_boxes, volatile=True)
-  gt_boxes = Variable(gt_boxes, volatile=True)
-
-  if args.cuda > 0:
-    cfg.CUDA = True
-
-  if args.cuda > 0:
-    fasterRCNN.cuda()
-
-  fasterRCNN.eval()
-
-  start = time.time()
-  max_per_image = 100
-  thresh = 0.05
-  vis = True
-
-  webcam_num = args.webcam_num
-  # Set up webcam or get image directories
-  if webcam_num >= 0 :
-    cap = cv2.VideoCapture(webcam_num)
-    num_images = 0
-  else:
-    imglist = os.listdir(args.image_dir)
-    num_images = len(imglist)
-
-  print('Loaded Photo: {} images.'.format(num_images))
-
-
-  while (num_images >= 0):
-      total_tic = time.time()
-      if webcam_num == -1:
-        num_images -= 1
-
-      # Get image from the webcam
-      if webcam_num >= 0:
-        if not cap.isOpened():
-          raise RuntimeError("Webcam could not open. Please check connection.")
-        ret, frame = cap.read()
-        im_in = np.array(frame)
-      # Load the demo image
-      else:
-        im_file = os.path.join(args.image_dir, imglist[num_images])
-        # im = cv2.imread(im_file)
-        im_in = np.array(imread(im_file))
-      if len(im_in.shape) == 2:
-        im_in = im_in[:,:,np.newaxis]
-        im_in = np.concatenate((im_in,im_in,im_in), axis=2)
-      # rgb -> bgr
-      im = im_in[:,:,::-1]
-
-      blobs, im_scales = _get_image_blob(im)
-      assert len(im_scales) == 1, "Only single-image batch implemented"
-      im_blob = blobs
-      im_info_np = np.array([[im_blob.shape[1], im_blob.shape[2], im_scales[0]]], dtype=np.float32)
-
-      im_data_pt = torch.from_numpy(im_blob)
-      im_data_pt = im_data_pt.permute(0, 3, 1, 2)
-      im_info_pt = torch.from_numpy(im_info_np)
-
-      with torch.no_grad():
-              im_data.resize_(im_data_pt.size()).copy_(im_data_pt)
-              im_info.resize_(im_info_pt.size()).copy_(im_info_pt)
-              gt_boxes.resize_(1, 1, 5).zero_()
-              num_boxes.resize_(1).zero_()
-
-      # pdb.set_trace()
-      det_tic = time.time()
-
-      rois, cls_prob, bbox_pred, \
-      rpn_loss_cls, rpn_loss_box, \
-      RCNN_loss_cls, RCNN_loss_bbox, \
-      rois_label = fasterRCNN(im_data, im_info, gt_boxes, num_boxes)
-
-      scores = cls_prob.data
-      boxes = rois.data[:, :, 1:5]
-
-      if cfg.TEST.BBOX_REG:
-          # Apply bounding-box regression deltas
-          box_deltas = bbox_pred.data
-          if cfg.TRAIN.BBOX_NORMALIZE_TARGETS_PRECOMPUTED:
-          # Optionally normalize targets by a precomputed mean and stdev
-            if args.class_agnostic:
-                if args.cuda > 0:
-                    box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS).cuda() \
-                               + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS).cuda()
-                else:
-                    box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS) \
-                               + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS)
-
-                box_deltas = box_deltas.view(1, -1, 4)
-            else:
-                if args.cuda > 0:
-                    box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS).cuda() \
-                               + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS).cuda()
-                else:
-                    box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS) \
-                               + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS)
-                box_deltas = box_deltas.view(1, -1, 4 * len(pascal_classes))
-
-          pred_boxes = bbox_transform_inv(boxes, box_deltas, 1)
-          pred_boxes = clip_boxes(pred_boxes, im_info.data, 1)
-      else:
-          # Simply repeat the boxes, once for each class
-          pred_boxes = np.tile(boxes, (1, scores.shape[1]))
-
-      pred_boxes /= im_scales[0]
-
-      scores = scores.squeeze()
-      pred_boxes = pred_boxes.squeeze()
-      det_toc = time.time()
-      detect_time = det_toc - det_tic
-      misc_tic = time.time()
-      if vis:
-          im2show = np.copy(im)
-      for j in xrange(1, len(pascal_classes)):
-          inds = torch.nonzero(scores[:,j]>thresh).view(-1)
-          # if there is det
-          if inds.numel() > 0:
-            cls_scores = scores[:,j][inds]
-            _, order = torch.sort(cls_scores, 0, True)
-            if args.class_agnostic:
-              cls_boxes = pred_boxes[inds, :]
-            else:
-              cls_boxes = pred_boxes[inds][:, j * 4:(j + 1) * 4]
-            
-            cls_dets = torch.cat((cls_boxes, cls_scores.unsqueeze(1)), 1)
-            # cls_dets = torch.cat((cls_boxes, cls_scores), 1)
-            cls_dets = cls_dets[order]
-            # keep = nms(cls_dets, cfg.TEST.NMS, force_cpu=not cfg.USE_GPU_NMS)
-            keep = nms(cls_boxes[order, :], cls_scores[order], cfg.TEST.NMS)
-            cls_dets = cls_dets[keep.view(-1).long()]
-            if vis:
-              im2show = vis_detections(im2show, pascal_classes[j], cls_dets.cpu().numpy(), 0.5)
-
-      misc_toc = time.time()
-      nms_time = misc_toc - misc_tic
-
-      if webcam_num == -1:
-          sys.stdout.write('im_detect: {:d}/{:d} {:.3f}s {:.3f}s   \r' \
-                           .format(num_images + 1, len(imglist), detect_time, nms_time))
-          sys.stdout.flush()
-
-      if vis and webcam_num == -1:
-          # cv2.imshow('test', im2show)
-          # cv2.waitKey(0)
-          result_path = os.path.join(args.image_dir, imglist[num_images][:-4] + "_det.jpg")
-          cv2.imwrite(result_path, im2show)
-      else:
-          im2showRGB = cv2.cvtColor(im2show, cv2.COLOR_BGR2RGB)
-          cv2.imshow("frame", im2showRGB)
-          total_toc = time.time()
-          total_time = total_toc - total_tic
-          frame_rate = 1 / total_time
-          print('Frame rate:', frame_rate)
-          if cv2.waitKey(1) & 0xFF == ord('q'):
-              break
-  if webcam_num >= 0:
-      cap.release()
-      cv2.destroyAllWindows()
diff --git a/lib/model/__init__.py b/faster_rcnn/__init__.py
similarity index 100%
rename from lib/model/__init__.py
rename to faster_rcnn/__init__.py
diff --git a/_init_paths.py b/faster_rcnn/_init_paths.py
similarity index 85%
rename from _init_paths.py
rename to faster_rcnn/_init_paths.py
index bdc926d28..0136d64c8 100644
--- a/_init_paths.py
+++ b/faster_rcnn/_init_paths.py
@@ -1,3 +1,4 @@
+import os
 import os.path as osp
 import sys
 
@@ -9,6 +10,7 @@ def add_path(path):
 
 # Add lib to PYTHONPATH
 lib_path = osp.join(this_dir, 'lib')
+assert os.path.isdir(lib_path), lib_path
 add_path(lib_path)
 
 coco_path = osp.join(this_dir, 'data', 'coco', 'PythonAPI')
diff --git a/cfgs/res101.yml b/faster_rcnn/cfgs/res101.yml
similarity index 100%
rename from cfgs/res101.yml
rename to faster_rcnn/cfgs/res101.yml
diff --git a/cfgs/res101_ls.yml b/faster_rcnn/cfgs/res101_ls.yml
similarity index 100%
rename from cfgs/res101_ls.yml
rename to faster_rcnn/cfgs/res101_ls.yml
diff --git a/cfgs/res50.yml b/faster_rcnn/cfgs/res50.yml
similarity index 100%
rename from cfgs/res50.yml
rename to faster_rcnn/cfgs/res50.yml
diff --git a/cfgs/vgg16.yml b/faster_rcnn/cfgs/vgg16.yml
similarity index 100%
rename from cfgs/vgg16.yml
rename to faster_rcnn/cfgs/vgg16.yml
diff --git a/images/img1.jpg b/faster_rcnn/images/img1.jpg
similarity index 100%
rename from images/img1.jpg
rename to faster_rcnn/images/img1.jpg
diff --git a/images/img1_det.jpg b/faster_rcnn/images/img1_det.jpg
similarity index 100%
rename from images/img1_det.jpg
rename to faster_rcnn/images/img1_det.jpg
diff --git a/images/img1_det_res101.jpg b/faster_rcnn/images/img1_det_res101.jpg
similarity index 100%
rename from images/img1_det_res101.jpg
rename to faster_rcnn/images/img1_det_res101.jpg
diff --git a/images/img2.jpg b/faster_rcnn/images/img2.jpg
similarity index 100%
rename from images/img2.jpg
rename to faster_rcnn/images/img2.jpg
diff --git a/images/img2_det.jpg b/faster_rcnn/images/img2_det.jpg
similarity index 100%
rename from images/img2_det.jpg
rename to faster_rcnn/images/img2_det.jpg
diff --git a/images/img2_det_res101.jpg b/faster_rcnn/images/img2_det_res101.jpg
similarity index 100%
rename from images/img2_det_res101.jpg
rename to faster_rcnn/images/img2_det_res101.jpg
diff --git a/images/img3.jpg b/faster_rcnn/images/img3.jpg
similarity index 100%
rename from images/img3.jpg
rename to faster_rcnn/images/img3.jpg
diff --git a/images/img3_det.jpg b/faster_rcnn/images/img3_det.jpg
similarity index 100%
rename from images/img3_det.jpg
rename to faster_rcnn/images/img3_det.jpg
diff --git a/images/img3_det_res101.jpg b/faster_rcnn/images/img3_det_res101.jpg
similarity index 100%
rename from images/img3_det_res101.jpg
rename to faster_rcnn/images/img3_det_res101.jpg
diff --git a/images/img4.jpg b/faster_rcnn/images/img4.jpg
similarity index 100%
rename from images/img4.jpg
rename to faster_rcnn/images/img4.jpg
diff --git a/images/img4_det.jpg b/faster_rcnn/images/img4_det.jpg
similarity index 100%
rename from images/img4_det.jpg
rename to faster_rcnn/images/img4_det.jpg
diff --git a/images/img4_det_res101.jpg b/faster_rcnn/images/img4_det_res101.jpg
similarity index 100%
rename from images/img4_det_res101.jpg
rename to faster_rcnn/images/img4_det_res101.jpg
diff --git a/lib/model/faster_rcnn/__init__.py b/faster_rcnn/lib/__init__.py
similarity index 100%
rename from lib/model/faster_rcnn/__init__.py
rename to faster_rcnn/lib/__init__.py
diff --git a/lib/datasets/VOCdevkit-matlab-wrapper/get_voc_opts.m b/faster_rcnn/lib/datasets/VOCdevkit-matlab-wrapper/get_voc_opts.m
similarity index 100%
rename from lib/datasets/VOCdevkit-matlab-wrapper/get_voc_opts.m
rename to faster_rcnn/lib/datasets/VOCdevkit-matlab-wrapper/get_voc_opts.m
diff --git a/lib/datasets/VOCdevkit-matlab-wrapper/voc_eval.m b/faster_rcnn/lib/datasets/VOCdevkit-matlab-wrapper/voc_eval.m
similarity index 100%
rename from lib/datasets/VOCdevkit-matlab-wrapper/voc_eval.m
rename to faster_rcnn/lib/datasets/VOCdevkit-matlab-wrapper/voc_eval.m
diff --git a/lib/datasets/VOCdevkit-matlab-wrapper/xVOCap.m b/faster_rcnn/lib/datasets/VOCdevkit-matlab-wrapper/xVOCap.m
similarity index 100%
rename from lib/datasets/VOCdevkit-matlab-wrapper/xVOCap.m
rename to faster_rcnn/lib/datasets/VOCdevkit-matlab-wrapper/xVOCap.m
diff --git a/lib/datasets/__init__.py b/faster_rcnn/lib/datasets/__init__.py
similarity index 100%
rename from lib/datasets/__init__.py
rename to faster_rcnn/lib/datasets/__init__.py
diff --git a/lib/datasets/coco.py b/faster_rcnn/lib/datasets/coco.py
similarity index 99%
rename from lib/datasets/coco.py
rename to faster_rcnn/lib/datasets/coco.py
index 97df5976d..0dd7cd0b6 100644
--- a/lib/datasets/coco.py
+++ b/faster_rcnn/lib/datasets/coco.py
@@ -9,7 +9,7 @@
 
 from datasets.imdb import imdb
 import datasets.ds_utils as ds_utils
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 import os.path as osp
 import sys
 import os
diff --git a/lib/datasets/ds_utils.py b/faster_rcnn/lib/datasets/ds_utils.py
similarity index 100%
rename from lib/datasets/ds_utils.py
rename to faster_rcnn/lib/datasets/ds_utils.py
diff --git a/lib/datasets/factory.py b/faster_rcnn/lib/datasets/factory.py
similarity index 100%
rename from lib/datasets/factory.py
rename to faster_rcnn/lib/datasets/factory.py
diff --git a/lib/datasets/imagenet.py b/faster_rcnn/lib/datasets/imagenet.py
similarity index 100%
rename from lib/datasets/imagenet.py
rename to faster_rcnn/lib/datasets/imagenet.py
diff --git a/lib/datasets/imdb.py b/faster_rcnn/lib/datasets/imdb.py
similarity index 98%
rename from lib/datasets/imdb.py
rename to faster_rcnn/lib/datasets/imdb.py
index 06dfbe556..cec59e195 100644
--- a/lib/datasets/imdb.py
+++ b/faster_rcnn/lib/datasets/imdb.py
@@ -11,10 +11,10 @@
 import os
 import os.path as osp
 import PIL
-# from model.utils.cython_bbox import bbox_overlaps
+# from faster_rcnn.lib.model.utils.cython_bbox import bbox_overlaps
 import numpy as np
 import scipy.sparse
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 import pdb
 
 ROOT_DIR = osp.join(osp.dirname(__file__), '..', '..')
diff --git a/lib/datasets/pascal_voc.py b/faster_rcnn/lib/datasets/pascal_voc.py
similarity index 99%
rename from lib/datasets/pascal_voc.py
rename to faster_rcnn/lib/datasets/pascal_voc.py
index 7a29bd9d2..3cb0bb505 100644
--- a/lib/datasets/pascal_voc.py
+++ b/faster_rcnn/lib/datasets/pascal_voc.py
@@ -27,7 +27,7 @@
 
 # TODO: make fast_rcnn irrelevant
 # >>>> obsolete, because it depends on sth outside of this project
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 
 try:
     xrange          # Python 2
diff --git a/lib/datasets/pascal_voc_rbg.py b/faster_rcnn/lib/datasets/pascal_voc_rbg.py
similarity index 99%
rename from lib/datasets/pascal_voc_rbg.py
rename to faster_rcnn/lib/datasets/pascal_voc_rbg.py
index 23b42240b..f98a17b27 100644
--- a/lib/datasets/pascal_voc_rbg.py
+++ b/faster_rcnn/lib/datasets/pascal_voc_rbg.py
@@ -20,7 +20,7 @@
 import subprocess
 import uuid
 from .voc_eval import voc_eval
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 import pdb
 
 
diff --git a/lib/datasets/tools/mcg_munge.py b/faster_rcnn/lib/datasets/tools/mcg_munge.py
similarity index 100%
rename from lib/datasets/tools/mcg_munge.py
rename to faster_rcnn/lib/datasets/tools/mcg_munge.py
diff --git a/lib/datasets/vg.py b/faster_rcnn/lib/datasets/vg.py
similarity index 99%
rename from lib/datasets/vg.py
rename to faster_rcnn/lib/datasets/vg.py
index 3c1a1a38b..57e7f6e76 100755
--- a/lib/datasets/vg.py
+++ b/faster_rcnn/lib/datasets/vg.py
@@ -17,7 +17,7 @@
 import PIL
 import json
 from .vg_eval import vg_eval
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 import pickle
 import pdb
 try:
diff --git a/lib/datasets/vg_eval.py b/faster_rcnn/lib/datasets/vg_eval.py
similarity index 100%
rename from lib/datasets/vg_eval.py
rename to faster_rcnn/lib/datasets/vg_eval.py
diff --git a/lib/datasets/voc_eval.py b/faster_rcnn/lib/datasets/voc_eval.py
similarity index 100%
rename from lib/datasets/voc_eval.py
rename to faster_rcnn/lib/datasets/voc_eval.py
diff --git a/lib/model/nms/__init__.py b/faster_rcnn/lib/model/__init__.py
similarity index 100%
rename from lib/model/nms/__init__.py
rename to faster_rcnn/lib/model/__init__.py
diff --git a/lib/model/csrc/ROIAlign.h b/faster_rcnn/lib/model/csrc/ROIAlign.h
similarity index 100%
rename from lib/model/csrc/ROIAlign.h
rename to faster_rcnn/lib/model/csrc/ROIAlign.h
diff --git a/lib/model/csrc/ROIPool.h b/faster_rcnn/lib/model/csrc/ROIPool.h
similarity index 100%
rename from lib/model/csrc/ROIPool.h
rename to faster_rcnn/lib/model/csrc/ROIPool.h
diff --git a/lib/model/csrc/cpu/ROIAlign_cpu.cpp b/faster_rcnn/lib/model/csrc/cpu/ROIAlign_cpu.cpp
similarity index 100%
rename from lib/model/csrc/cpu/ROIAlign_cpu.cpp
rename to faster_rcnn/lib/model/csrc/cpu/ROIAlign_cpu.cpp
diff --git a/lib/model/csrc/cpu/nms_cpu.cpp b/faster_rcnn/lib/model/csrc/cpu/nms_cpu.cpp
similarity index 100%
rename from lib/model/csrc/cpu/nms_cpu.cpp
rename to faster_rcnn/lib/model/csrc/cpu/nms_cpu.cpp
diff --git a/lib/model/csrc/cpu/vision.h b/faster_rcnn/lib/model/csrc/cpu/vision.h
similarity index 100%
rename from lib/model/csrc/cpu/vision.h
rename to faster_rcnn/lib/model/csrc/cpu/vision.h
diff --git a/lib/model/csrc/cuda/ROIAlign_cuda.cu b/faster_rcnn/lib/model/csrc/cuda/ROIAlign_cuda.cu
similarity index 100%
rename from lib/model/csrc/cuda/ROIAlign_cuda.cu
rename to faster_rcnn/lib/model/csrc/cuda/ROIAlign_cuda.cu
diff --git a/lib/model/csrc/cuda/ROIPool_cuda.cu b/faster_rcnn/lib/model/csrc/cuda/ROIPool_cuda.cu
similarity index 100%
rename from lib/model/csrc/cuda/ROIPool_cuda.cu
rename to faster_rcnn/lib/model/csrc/cuda/ROIPool_cuda.cu
diff --git a/lib/model/csrc/cuda/nms.cu b/faster_rcnn/lib/model/csrc/cuda/nms.cu
similarity index 100%
rename from lib/model/csrc/cuda/nms.cu
rename to faster_rcnn/lib/model/csrc/cuda/nms.cu
diff --git a/lib/model/csrc/cuda/vision.h b/faster_rcnn/lib/model/csrc/cuda/vision.h
similarity index 100%
rename from lib/model/csrc/cuda/vision.h
rename to faster_rcnn/lib/model/csrc/cuda/vision.h
diff --git a/lib/model/csrc/nms.h b/faster_rcnn/lib/model/csrc/nms.h
similarity index 100%
rename from lib/model/csrc/nms.h
rename to faster_rcnn/lib/model/csrc/nms.h
diff --git a/lib/model/csrc/vision.cpp b/faster_rcnn/lib/model/csrc/vision.cpp
similarity index 100%
rename from lib/model/csrc/vision.cpp
rename to faster_rcnn/lib/model/csrc/vision.cpp
diff --git a/lib/model/nms/_ext/__init__.py b/faster_rcnn/lib/model/faster_rcnn/__init__.py
similarity index 100%
rename from lib/model/nms/_ext/__init__.py
rename to faster_rcnn/lib/model/faster_rcnn/__init__.py
diff --git a/lib/model/faster_rcnn/faster_rcnn.py b/faster_rcnn/lib/model/faster_rcnn/faster_rcnn.py
similarity index 90%
rename from lib/model/faster_rcnn/faster_rcnn.py
rename to faster_rcnn/lib/model/faster_rcnn/faster_rcnn.py
index 649616260..a2b21b438 100644
--- a/lib/model/faster_rcnn/faster_rcnn.py
+++ b/faster_rcnn/lib/model/faster_rcnn/faster_rcnn.py
@@ -6,18 +6,18 @@
 import torchvision.models as models
 from torch.autograd import Variable
 import numpy as np
-from model.utils.config import cfg
-from model.rpn.rpn import _RPN
+from faster_rcnn.lib.model.utils.config import cfg
+from faster_rcnn.lib.model.rpn.rpn import _RPN
 
-from model.roi_layers import ROIAlign, ROIPool
+from faster_rcnn.lib.model.roi_layers import ROIAlign, ROIPool
 
-# from model.roi_pooling.modules.roi_pool import _RoIPooling
-# from model.roi_align.modules.roi_align import RoIAlignAvg
+# from faster_rcnn.lib.model.roi_pooling.modules.roi_pool import _RoIPooling
+# from faster_rcnn.lib.model.roi_align.modules.roi_align import RoIAlignAvg
 
-from model.rpn.proposal_target_layer_cascade import _ProposalTargetLayer
+from faster_rcnn.lib.model.rpn.proposal_target_layer_cascade import _ProposalTargetLayer
 import time
 import pdb
-from model.utils.net_utils import _smooth_l1_loss, _crop_pool_layer, _affine_grid_gen, _affine_theta
+from faster_rcnn.lib.model.utils.net_utils import _smooth_l1_loss, _crop_pool_layer, _affine_grid_gen, _affine_theta
 
 class _fasterRCNN(nn.Module):
     """ faster RCNN """
diff --git a/lib/model/faster_rcnn/resnet.py b/faster_rcnn/lib/model/faster_rcnn/resnet.py
similarity index 98%
rename from lib/model/faster_rcnn/resnet.py
rename to faster_rcnn/lib/model/faster_rcnn/resnet.py
index 5457724b3..f27bad836 100644
--- a/lib/model/faster_rcnn/resnet.py
+++ b/faster_rcnn/lib/model/faster_rcnn/resnet.py
@@ -2,8 +2,8 @@
 from __future__ import division
 from __future__ import print_function
 
-from model.utils.config import cfg
-from model.faster_rcnn.faster_rcnn import _fasterRCNN
+from faster_rcnn.lib.model.utils.config import cfg
+from faster_rcnn.lib.model.faster_rcnn.faster_rcnn import _fasterRCNN
 
 import torch
 import torch.nn as nn
diff --git a/lib/model/faster_rcnn/vgg16.py b/faster_rcnn/lib/model/faster_rcnn/vgg16.py
similarity index 93%
rename from lib/model/faster_rcnn/vgg16.py
rename to faster_rcnn/lib/model/faster_rcnn/vgg16.py
index 90fe0d7b9..bb6812665 100644
--- a/lib/model/faster_rcnn/vgg16.py
+++ b/faster_rcnn/lib/model/faster_rcnn/vgg16.py
@@ -13,7 +13,7 @@
 from torch.autograd import Variable
 import math
 import torchvision.models as models
-from model.faster_rcnn.faster_rcnn import _fasterRCNN
+from faster_rcnn.lib.model.faster_rcnn.faster_rcnn import _fasterRCNN
 import pdb
 
 class vgg16(_fasterRCNN):
@@ -51,10 +51,10 @@ def _init_modules(self):
     if self.class_agnostic:
       self.RCNN_bbox_pred = nn.Linear(4096, 4)
     else:
-      self.RCNN_bbox_pred = nn.Linear(4096, 4 * self.n_classes)      
+      self.RCNN_bbox_pred = nn.Linear(4096, 4 * self.n_classes)
 
   def _head_to_tail(self, pool5):
-    
+
     pool5_flat = pool5.view(pool5.size(0), -1)
     fc7 = self.RCNN_top(pool5_flat)
 
diff --git a/lib/model/nms/.gitignore b/faster_rcnn/lib/model/nms/.gitignore
similarity index 100%
rename from lib/model/nms/.gitignore
rename to faster_rcnn/lib/model/nms/.gitignore
diff --git a/lib/model/roi_align/__init__.py b/faster_rcnn/lib/model/nms/__init__.py
similarity index 100%
rename from lib/model/roi_align/__init__.py
rename to faster_rcnn/lib/model/nms/__init__.py
diff --git a/lib/model/roi_align/_ext/__init__.py b/faster_rcnn/lib/model/nms/_ext/__init__.py
similarity index 100%
rename from lib/model/roi_align/_ext/__init__.py
rename to faster_rcnn/lib/model/nms/_ext/__init__.py
diff --git a/lib/model/nms/_ext/nms/__init__.py b/faster_rcnn/lib/model/nms/_ext/nms/__init__.py
similarity index 100%
rename from lib/model/nms/_ext/nms/__init__.py
rename to faster_rcnn/lib/model/nms/_ext/nms/__init__.py
diff --git a/lib/model/nms/build.py b/faster_rcnn/lib/model/nms/build.py
similarity index 100%
rename from lib/model/nms/build.py
rename to faster_rcnn/lib/model/nms/build.py
diff --git a/lib/model/nms/make.sh b/faster_rcnn/lib/model/nms/make.sh
similarity index 100%
rename from lib/model/nms/make.sh
rename to faster_rcnn/lib/model/nms/make.sh
diff --git a/lib/model/nms/nms_cpu.py b/faster_rcnn/lib/model/nms/nms_cpu.py
similarity index 100%
rename from lib/model/nms/nms_cpu.py
rename to faster_rcnn/lib/model/nms/nms_cpu.py
diff --git a/lib/model/nms/nms_gpu.py b/faster_rcnn/lib/model/nms/nms_gpu.py
similarity index 100%
rename from lib/model/nms/nms_gpu.py
rename to faster_rcnn/lib/model/nms/nms_gpu.py
diff --git a/lib/model/nms/nms_kernel.cu b/faster_rcnn/lib/model/nms/nms_kernel.cu
similarity index 100%
rename from lib/model/nms/nms_kernel.cu
rename to faster_rcnn/lib/model/nms/nms_kernel.cu
diff --git a/lib/model/nms/nms_wrapper.py b/faster_rcnn/lib/model/nms/nms_wrapper.py
similarity index 79%
rename from lib/model/nms/nms_wrapper.py
rename to faster_rcnn/lib/model/nms/nms_wrapper.py
index 5ae36602b..94a400fd1 100644
--- a/lib/model/nms/nms_wrapper.py
+++ b/faster_rcnn/lib/model/nms/nms_wrapper.py
@@ -5,10 +5,10 @@
 # Written by Ross Girshick
 # --------------------------------------------------------
 import torch
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 if torch.cuda.is_available():
-    from model.nms.nms_gpu import nms_gpu
-from model.nms.nms_cpu import nms_cpu
+    from faster_rcnn.lib.model.nms.nms_gpu import nms_gpu
+from faster_rcnn.lib.model.nms.nms_cpu import nms_cpu
 
 def nms(dets, thresh, force_cpu=False):
     """Dispatch to either CPU or GPU NMS implementations."""
diff --git a/lib/model/nms/src/nms_cuda.h b/faster_rcnn/lib/model/nms/src/nms_cuda.h
similarity index 100%
rename from lib/model/nms/src/nms_cuda.h
rename to faster_rcnn/lib/model/nms/src/nms_cuda.h
diff --git a/lib/model/nms/src/nms_cuda_kernel.cu b/faster_rcnn/lib/model/nms/src/nms_cuda_kernel.cu
similarity index 100%
rename from lib/model/nms/src/nms_cuda_kernel.cu
rename to faster_rcnn/lib/model/nms/src/nms_cuda_kernel.cu
diff --git a/lib/model/nms/src/nms_cuda_kernel.h b/faster_rcnn/lib/model/nms/src/nms_cuda_kernel.h
similarity index 100%
rename from lib/model/nms/src/nms_cuda_kernel.h
rename to faster_rcnn/lib/model/nms/src/nms_cuda_kernel.h
diff --git a/lib/model/roi_align/functions/__init__.py b/faster_rcnn/lib/model/roi_align/__init__.py
similarity index 100%
rename from lib/model/roi_align/functions/__init__.py
rename to faster_rcnn/lib/model/roi_align/__init__.py
diff --git a/lib/model/roi_align/modules/__init__.py b/faster_rcnn/lib/model/roi_align/_ext/__init__.py
similarity index 100%
rename from lib/model/roi_align/modules/__init__.py
rename to faster_rcnn/lib/model/roi_align/_ext/__init__.py
diff --git a/lib/model/roi_align/_ext/roi_align/__init__.py b/faster_rcnn/lib/model/roi_align/_ext/roi_align/__init__.py
similarity index 100%
rename from lib/model/roi_align/_ext/roi_align/__init__.py
rename to faster_rcnn/lib/model/roi_align/_ext/roi_align/__init__.py
diff --git a/lib/model/roi_align/build.py b/faster_rcnn/lib/model/roi_align/build.py
similarity index 100%
rename from lib/model/roi_align/build.py
rename to faster_rcnn/lib/model/roi_align/build.py
diff --git a/lib/model/roi_crop/__init__.py b/faster_rcnn/lib/model/roi_align/functions/__init__.py
similarity index 100%
rename from lib/model/roi_crop/__init__.py
rename to faster_rcnn/lib/model/roi_align/functions/__init__.py
diff --git a/lib/model/roi_align/functions/roi_align.py b/faster_rcnn/lib/model/roi_align/functions/roi_align.py
similarity index 100%
rename from lib/model/roi_align/functions/roi_align.py
rename to faster_rcnn/lib/model/roi_align/functions/roi_align.py
diff --git a/lib/model/roi_align/make.sh b/faster_rcnn/lib/model/roi_align/make.sh
similarity index 100%
rename from lib/model/roi_align/make.sh
rename to faster_rcnn/lib/model/roi_align/make.sh
diff --git a/lib/model/roi_crop/_ext/__init__.py b/faster_rcnn/lib/model/roi_align/modules/__init__.py
similarity index 100%
rename from lib/model/roi_crop/_ext/__init__.py
rename to faster_rcnn/lib/model/roi_align/modules/__init__.py
diff --git a/lib/model/roi_align/modules/roi_align.py b/faster_rcnn/lib/model/roi_align/modules/roi_align.py
similarity index 100%
rename from lib/model/roi_align/modules/roi_align.py
rename to faster_rcnn/lib/model/roi_align/modules/roi_align.py
diff --git a/lib/model/roi_align/src/roi_align.c b/faster_rcnn/lib/model/roi_align/src/roi_align.c
similarity index 100%
rename from lib/model/roi_align/src/roi_align.c
rename to faster_rcnn/lib/model/roi_align/src/roi_align.c
diff --git a/lib/model/roi_align/src/roi_align.h b/faster_rcnn/lib/model/roi_align/src/roi_align.h
similarity index 100%
rename from lib/model/roi_align/src/roi_align.h
rename to faster_rcnn/lib/model/roi_align/src/roi_align.h
diff --git a/lib/model/roi_align/src/roi_align_cuda.c b/faster_rcnn/lib/model/roi_align/src/roi_align_cuda.c
similarity index 100%
rename from lib/model/roi_align/src/roi_align_cuda.c
rename to faster_rcnn/lib/model/roi_align/src/roi_align_cuda.c
diff --git a/lib/model/roi_align/src/roi_align_cuda.h b/faster_rcnn/lib/model/roi_align/src/roi_align_cuda.h
similarity index 100%
rename from lib/model/roi_align/src/roi_align_cuda.h
rename to faster_rcnn/lib/model/roi_align/src/roi_align_cuda.h
diff --git a/lib/model/roi_align/src/roi_align_kernel.cu b/faster_rcnn/lib/model/roi_align/src/roi_align_kernel.cu
similarity index 100%
rename from lib/model/roi_align/src/roi_align_kernel.cu
rename to faster_rcnn/lib/model/roi_align/src/roi_align_kernel.cu
diff --git a/lib/model/roi_align/src/roi_align_kernel.h b/faster_rcnn/lib/model/roi_align/src/roi_align_kernel.h
similarity index 100%
rename from lib/model/roi_align/src/roi_align_kernel.h
rename to faster_rcnn/lib/model/roi_align/src/roi_align_kernel.h
diff --git a/lib/model/roi_crop/functions/__init__.py b/faster_rcnn/lib/model/roi_crop/__init__.py
similarity index 100%
rename from lib/model/roi_crop/functions/__init__.py
rename to faster_rcnn/lib/model/roi_crop/__init__.py
diff --git a/lib/model/roi_crop/modules/__init__.py b/faster_rcnn/lib/model/roi_crop/_ext/__init__.py
similarity index 100%
rename from lib/model/roi_crop/modules/__init__.py
rename to faster_rcnn/lib/model/roi_crop/_ext/__init__.py
diff --git a/lib/model/roi_crop/_ext/crop_resize/__init__.py b/faster_rcnn/lib/model/roi_crop/_ext/crop_resize/__init__.py
similarity index 100%
rename from lib/model/roi_crop/_ext/crop_resize/__init__.py
rename to faster_rcnn/lib/model/roi_crop/_ext/crop_resize/__init__.py
diff --git a/lib/model/roi_crop/_ext/roi_crop/__init__.py b/faster_rcnn/lib/model/roi_crop/_ext/roi_crop/__init__.py
similarity index 100%
rename from lib/model/roi_crop/_ext/roi_crop/__init__.py
rename to faster_rcnn/lib/model/roi_crop/_ext/roi_crop/__init__.py
diff --git a/lib/model/roi_crop/build.py b/faster_rcnn/lib/model/roi_crop/build.py
similarity index 100%
rename from lib/model/roi_crop/build.py
rename to faster_rcnn/lib/model/roi_crop/build.py
diff --git a/lib/model/roi_pooling/__init__.py b/faster_rcnn/lib/model/roi_crop/functions/__init__.py
similarity index 100%
rename from lib/model/roi_pooling/__init__.py
rename to faster_rcnn/lib/model/roi_crop/functions/__init__.py
diff --git a/lib/model/roi_crop/functions/crop_resize.py b/faster_rcnn/lib/model/roi_crop/functions/crop_resize.py
similarity index 100%
rename from lib/model/roi_crop/functions/crop_resize.py
rename to faster_rcnn/lib/model/roi_crop/functions/crop_resize.py
diff --git a/lib/model/roi_crop/functions/gridgen.py b/faster_rcnn/lib/model/roi_crop/functions/gridgen.py
similarity index 100%
rename from lib/model/roi_crop/functions/gridgen.py
rename to faster_rcnn/lib/model/roi_crop/functions/gridgen.py
diff --git a/lib/model/roi_crop/functions/roi_crop.py b/faster_rcnn/lib/model/roi_crop/functions/roi_crop.py
similarity index 100%
rename from lib/model/roi_crop/functions/roi_crop.py
rename to faster_rcnn/lib/model/roi_crop/functions/roi_crop.py
diff --git a/lib/model/roi_crop/make.sh b/faster_rcnn/lib/model/roi_crop/make.sh
similarity index 100%
rename from lib/model/roi_crop/make.sh
rename to faster_rcnn/lib/model/roi_crop/make.sh
diff --git a/lib/model/roi_pooling/_ext/__init__.py b/faster_rcnn/lib/model/roi_crop/modules/__init__.py
similarity index 100%
rename from lib/model/roi_pooling/_ext/__init__.py
rename to faster_rcnn/lib/model/roi_crop/modules/__init__.py
diff --git a/lib/model/roi_crop/modules/gridgen.py b/faster_rcnn/lib/model/roi_crop/modules/gridgen.py
similarity index 100%
rename from lib/model/roi_crop/modules/gridgen.py
rename to faster_rcnn/lib/model/roi_crop/modules/gridgen.py
diff --git a/lib/model/roi_crop/modules/roi_crop.py b/faster_rcnn/lib/model/roi_crop/modules/roi_crop.py
similarity index 100%
rename from lib/model/roi_crop/modules/roi_crop.py
rename to faster_rcnn/lib/model/roi_crop/modules/roi_crop.py
diff --git a/lib/model/roi_crop/src/roi_crop.c b/faster_rcnn/lib/model/roi_crop/src/roi_crop.c
similarity index 100%
rename from lib/model/roi_crop/src/roi_crop.c
rename to faster_rcnn/lib/model/roi_crop/src/roi_crop.c
diff --git a/lib/model/roi_crop/src/roi_crop.h b/faster_rcnn/lib/model/roi_crop/src/roi_crop.h
similarity index 100%
rename from lib/model/roi_crop/src/roi_crop.h
rename to faster_rcnn/lib/model/roi_crop/src/roi_crop.h
diff --git a/lib/model/roi_crop/src/roi_crop_cuda.c b/faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda.c
similarity index 100%
rename from lib/model/roi_crop/src/roi_crop_cuda.c
rename to faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda.c
diff --git a/lib/model/roi_crop/src/roi_crop_cuda.h b/faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda.h
similarity index 100%
rename from lib/model/roi_crop/src/roi_crop_cuda.h
rename to faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda.h
diff --git a/lib/model/roi_crop/src/roi_crop_cuda_kernel.cu b/faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda_kernel.cu
similarity index 100%
rename from lib/model/roi_crop/src/roi_crop_cuda_kernel.cu
rename to faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda_kernel.cu
diff --git a/lib/model/roi_crop/src/roi_crop_cuda_kernel.h b/faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda_kernel.h
similarity index 100%
rename from lib/model/roi_crop/src/roi_crop_cuda_kernel.h
rename to faster_rcnn/lib/model/roi_crop/src/roi_crop_cuda_kernel.h
diff --git a/lib/model/roi_layers/__init__.py b/faster_rcnn/lib/model/roi_layers/__init__.py
similarity index 100%
rename from lib/model/roi_layers/__init__.py
rename to faster_rcnn/lib/model/roi_layers/__init__.py
diff --git a/lib/model/roi_layers/nms.py b/faster_rcnn/lib/model/roi_layers/nms.py
similarity index 83%
rename from lib/model/roi_layers/nms.py
rename to faster_rcnn/lib/model/roi_layers/nms.py
index c0de3f32d..0df1e787c 100644
--- a/lib/model/roi_layers/nms.py
+++ b/faster_rcnn/lib/model/roi_layers/nms.py
@@ -1,6 +1,6 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
 # from ._utils import _C
-from model import _C
+from faster_rcnn.lib.model import _C
 
 nms = _C.nms
 # nms.__doc__ = """
diff --git a/lib/model/roi_layers/roi_align.py b/faster_rcnn/lib/model/roi_layers/roi_align.py
similarity index 98%
rename from lib/model/roi_layers/roi_align.py
rename to faster_rcnn/lib/model/roi_layers/roi_align.py
index 10a448744..f6012f218 100644
--- a/lib/model/roi_layers/roi_align.py
+++ b/faster_rcnn/lib/model/roi_layers/roi_align.py
@@ -5,7 +5,7 @@
 from torch.autograd.function import once_differentiable
 from torch.nn.modules.utils import _pair
 
-from model import _C
+from faster_rcnn.lib.model import _C
 
 import pdb
 
diff --git a/lib/model/roi_layers/roi_pool.py b/faster_rcnn/lib/model/roi_layers/roi_pool.py
similarity index 98%
rename from lib/model/roi_layers/roi_pool.py
rename to faster_rcnn/lib/model/roi_layers/roi_pool.py
index e9e6e1069..62d82b6bf 100644
--- a/lib/model/roi_layers/roi_pool.py
+++ b/faster_rcnn/lib/model/roi_layers/roi_pool.py
@@ -5,7 +5,7 @@
 from torch.autograd.function import once_differentiable
 from torch.nn.modules.utils import _pair
 
-from model import _C
+from faster_rcnn.lib.model import _C
 
 
 class _ROIPool(Function):
diff --git a/lib/model/roi_pooling/functions/__init__.py b/faster_rcnn/lib/model/roi_pooling/__init__.py
similarity index 100%
rename from lib/model/roi_pooling/functions/__init__.py
rename to faster_rcnn/lib/model/roi_pooling/__init__.py
diff --git a/lib/model/roi_pooling/modules/__init__.py b/faster_rcnn/lib/model/roi_pooling/_ext/__init__.py
similarity index 100%
rename from lib/model/roi_pooling/modules/__init__.py
rename to faster_rcnn/lib/model/roi_pooling/_ext/__init__.py
diff --git a/lib/model/roi_pooling/_ext/roi_pooling/__init__.py b/faster_rcnn/lib/model/roi_pooling/_ext/roi_pooling/__init__.py
similarity index 100%
rename from lib/model/roi_pooling/_ext/roi_pooling/__init__.py
rename to faster_rcnn/lib/model/roi_pooling/_ext/roi_pooling/__init__.py
diff --git a/lib/model/roi_pooling/build.py b/faster_rcnn/lib/model/roi_pooling/build.py
similarity index 100%
rename from lib/model/roi_pooling/build.py
rename to faster_rcnn/lib/model/roi_pooling/build.py
diff --git a/lib/model/rpn/__init__.py b/faster_rcnn/lib/model/roi_pooling/functions/__init__.py
similarity index 100%
rename from lib/model/rpn/__init__.py
rename to faster_rcnn/lib/model/roi_pooling/functions/__init__.py
diff --git a/lib/model/roi_pooling/functions/roi_pool.py b/faster_rcnn/lib/model/roi_pooling/functions/roi_pool.py
similarity index 100%
rename from lib/model/roi_pooling/functions/roi_pool.py
rename to faster_rcnn/lib/model/roi_pooling/functions/roi_pool.py
diff --git a/lib/model/utils/__init__.py b/faster_rcnn/lib/model/roi_pooling/modules/__init__.py
similarity index 100%
rename from lib/model/utils/__init__.py
rename to faster_rcnn/lib/model/roi_pooling/modules/__init__.py
diff --git a/lib/model/roi_pooling/modules/roi_pool.py b/faster_rcnn/lib/model/roi_pooling/modules/roi_pool.py
similarity index 100%
rename from lib/model/roi_pooling/modules/roi_pool.py
rename to faster_rcnn/lib/model/roi_pooling/modules/roi_pool.py
diff --git a/lib/model/roi_pooling/src/roi_pooling.c b/faster_rcnn/lib/model/roi_pooling/src/roi_pooling.c
similarity index 100%
rename from lib/model/roi_pooling/src/roi_pooling.c
rename to faster_rcnn/lib/model/roi_pooling/src/roi_pooling.c
diff --git a/lib/model/roi_pooling/src/roi_pooling.h b/faster_rcnn/lib/model/roi_pooling/src/roi_pooling.h
similarity index 100%
rename from lib/model/roi_pooling/src/roi_pooling.h
rename to faster_rcnn/lib/model/roi_pooling/src/roi_pooling.h
diff --git a/lib/model/roi_pooling/src/roi_pooling_cuda.c b/faster_rcnn/lib/model/roi_pooling/src/roi_pooling_cuda.c
similarity index 100%
rename from lib/model/roi_pooling/src/roi_pooling_cuda.c
rename to faster_rcnn/lib/model/roi_pooling/src/roi_pooling_cuda.c
diff --git a/lib/model/roi_pooling/src/roi_pooling_cuda.h b/faster_rcnn/lib/model/roi_pooling/src/roi_pooling_cuda.h
similarity index 100%
rename from lib/model/roi_pooling/src/roi_pooling_cuda.h
rename to faster_rcnn/lib/model/roi_pooling/src/roi_pooling_cuda.h
diff --git a/lib/model/roi_pooling/src/roi_pooling_kernel.cu b/faster_rcnn/lib/model/roi_pooling/src/roi_pooling_kernel.cu
similarity index 100%
rename from lib/model/roi_pooling/src/roi_pooling_kernel.cu
rename to faster_rcnn/lib/model/roi_pooling/src/roi_pooling_kernel.cu
diff --git a/lib/model/roi_pooling/src/roi_pooling_kernel.h b/faster_rcnn/lib/model/roi_pooling/src/roi_pooling_kernel.h
similarity index 100%
rename from lib/model/roi_pooling/src/roi_pooling_kernel.h
rename to faster_rcnn/lib/model/roi_pooling/src/roi_pooling_kernel.h
diff --git a/faster_rcnn/lib/model/rpn/__init__.py b/faster_rcnn/lib/model/rpn/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/lib/model/rpn/anchor_target_layer.py b/faster_rcnn/lib/model/rpn/anchor_target_layer.py
similarity index 99%
rename from lib/model/rpn/anchor_target_layer.py
rename to faster_rcnn/lib/model/rpn/anchor_target_layer.py
index ba00ad56b..9a82989ac 100644
--- a/lib/model/rpn/anchor_target_layer.py
+++ b/faster_rcnn/lib/model/rpn/anchor_target_layer.py
@@ -14,7 +14,7 @@
 import numpy as np
 import numpy.random as npr
 
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 from .generate_anchors import generate_anchors
 from .bbox_transform import clip_boxes, bbox_overlaps_batch, bbox_transform_batch
 
diff --git a/lib/model/rpn/bbox_transform.py b/faster_rcnn/lib/model/rpn/bbox_transform.py
similarity index 100%
rename from lib/model/rpn/bbox_transform.py
rename to faster_rcnn/lib/model/rpn/bbox_transform.py
diff --git a/lib/model/rpn/generate_anchors.py b/faster_rcnn/lib/model/rpn/generate_anchors.py
similarity index 100%
rename from lib/model/rpn/generate_anchors.py
rename to faster_rcnn/lib/model/rpn/generate_anchors.py
diff --git a/lib/model/rpn/proposal_layer.py b/faster_rcnn/lib/model/rpn/proposal_layer.py
similarity index 97%
rename from lib/model/rpn/proposal_layer.py
rename to faster_rcnn/lib/model/rpn/proposal_layer.py
index 9c787da91..81580de28 100644
--- a/lib/model/rpn/proposal_layer.py
+++ b/faster_rcnn/lib/model/rpn/proposal_layer.py
@@ -14,11 +14,11 @@
 import numpy as np
 import math
 import yaml
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 from .generate_anchors import generate_anchors
 from .bbox_transform import bbox_transform_inv, clip_boxes, clip_boxes_batch
-# from model.nms.nms_wrapper import nms
-from model.roi_layers import nms
+# from faster_rcnn.lib.model.nms.nms_wrapper import nms
+from faster_rcnn.lib.model.roi_layers import nms
 import pdb
 
 DEBUG = False
diff --git a/lib/model/rpn/proposal_target_layer_cascade.py b/faster_rcnn/lib/model/rpn/proposal_target_layer_cascade.py
similarity index 100%
rename from lib/model/rpn/proposal_target_layer_cascade.py
rename to faster_rcnn/lib/model/rpn/proposal_target_layer_cascade.py
diff --git a/lib/model/rpn/rpn.py b/faster_rcnn/lib/model/rpn/rpn.py
similarity index 97%
rename from lib/model/rpn/rpn.py
rename to faster_rcnn/lib/model/rpn/rpn.py
index 29bdaadb3..504fa799b 100644
--- a/lib/model/rpn/rpn.py
+++ b/faster_rcnn/lib/model/rpn/rpn.py
@@ -4,10 +4,10 @@
 import torch.nn.functional as F
 from torch.autograd import Variable
 
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 from .proposal_layer import _ProposalLayer
 from .anchor_target_layer import _AnchorTargetLayer
-from model.utils.net_utils import _smooth_l1_loss
+from faster_rcnn.lib.model.utils.net_utils import _smooth_l1_loss
 
 import numpy as np
 import math
@@ -18,7 +18,7 @@ class _RPN(nn.Module):
     """ region proposal network """
     def __init__(self, din):
         super(_RPN, self).__init__()
-        
+
         self.din = din  # get depth of input feature map, e.g., 512
         self.anchor_scales = cfg.ANCHOR_SCALES
         self.anchor_ratios = cfg.ANCHOR_RATIOS
diff --git a/lib/model/utils/.gitignore b/faster_rcnn/lib/model/utils/.gitignore
similarity index 100%
rename from lib/model/utils/.gitignore
rename to faster_rcnn/lib/model/utils/.gitignore
diff --git a/faster_rcnn/lib/model/utils/__init__.py b/faster_rcnn/lib/model/utils/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/lib/model/utils/bbox.pyx b/faster_rcnn/lib/model/utils/bbox.pyx
similarity index 100%
rename from lib/model/utils/bbox.pyx
rename to faster_rcnn/lib/model/utils/bbox.pyx
diff --git a/lib/model/utils/blob.py b/faster_rcnn/lib/model/utils/blob.py
similarity index 97%
rename from lib/model/utils/blob.py
rename to faster_rcnn/lib/model/utils/blob.py
index 48b233249..21f2f78bf 100644
--- a/lib/model/utils/blob.py
+++ b/faster_rcnn/lib/model/utils/blob.py
@@ -8,7 +8,7 @@
 """Blob helper functions."""
 
 import numpy as np
-# from scipy.misc import imread, imresize
+# from imageio  import imread, imresize
 import cv2
 
 try:
diff --git a/lib/model/utils/config.py b/faster_rcnn/lib/model/utils/config.py
similarity index 100%
rename from lib/model/utils/config.py
rename to faster_rcnn/lib/model/utils/config.py
diff --git a/lib/model/utils/logger.py b/faster_rcnn/lib/model/utils/logger.py
similarity index 100%
rename from lib/model/utils/logger.py
rename to faster_rcnn/lib/model/utils/logger.py
diff --git a/lib/model/utils/net_utils.py b/faster_rcnn/lib/model/utils/net_utils.py
similarity index 99%
rename from lib/model/utils/net_utils.py
rename to faster_rcnn/lib/model/utils/net_utils.py
index fb9dc1f19..f06ae5150 100644
--- a/lib/model/utils/net_utils.py
+++ b/faster_rcnn/lib/model/utils/net_utils.py
@@ -4,7 +4,7 @@
 from torch.autograd import Variable
 import numpy as np
 import torchvision.models as models
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 import cv2
 import pdb
 import random
diff --git a/lib/pycocotools/UPSTREAM_REV b/faster_rcnn/lib/pycocotools/UPSTREAM_REV
similarity index 100%
rename from lib/pycocotools/UPSTREAM_REV
rename to faster_rcnn/lib/pycocotools/UPSTREAM_REV
diff --git a/lib/pycocotools/__init__.py b/faster_rcnn/lib/pycocotools/__init__.py
similarity index 100%
rename from lib/pycocotools/__init__.py
rename to faster_rcnn/lib/pycocotools/__init__.py
diff --git a/lib/pycocotools/_mask.c b/faster_rcnn/lib/pycocotools/_mask.c
similarity index 100%
rename from lib/pycocotools/_mask.c
rename to faster_rcnn/lib/pycocotools/_mask.c
diff --git a/lib/pycocotools/_mask.pyx b/faster_rcnn/lib/pycocotools/_mask.pyx
similarity index 100%
rename from lib/pycocotools/_mask.pyx
rename to faster_rcnn/lib/pycocotools/_mask.pyx
diff --git a/lib/pycocotools/coco.py b/faster_rcnn/lib/pycocotools/coco.py
similarity index 100%
rename from lib/pycocotools/coco.py
rename to faster_rcnn/lib/pycocotools/coco.py
diff --git a/lib/pycocotools/cocoeval.py b/faster_rcnn/lib/pycocotools/cocoeval.py
similarity index 100%
rename from lib/pycocotools/cocoeval.py
rename to faster_rcnn/lib/pycocotools/cocoeval.py
diff --git a/lib/pycocotools/license.txt b/faster_rcnn/lib/pycocotools/license.txt
similarity index 100%
rename from lib/pycocotools/license.txt
rename to faster_rcnn/lib/pycocotools/license.txt
diff --git a/lib/pycocotools/mask.py b/faster_rcnn/lib/pycocotools/mask.py
similarity index 100%
rename from lib/pycocotools/mask.py
rename to faster_rcnn/lib/pycocotools/mask.py
diff --git a/lib/pycocotools/maskApi.c b/faster_rcnn/lib/pycocotools/maskApi.c
similarity index 100%
rename from lib/pycocotools/maskApi.c
rename to faster_rcnn/lib/pycocotools/maskApi.c
diff --git a/lib/pycocotools/maskApi.h b/faster_rcnn/lib/pycocotools/maskApi.h
similarity index 100%
rename from lib/pycocotools/maskApi.h
rename to faster_rcnn/lib/pycocotools/maskApi.h
diff --git a/lib/roi_data_layer/__init__.py b/faster_rcnn/lib/roi_data_layer/__init__.py
similarity index 100%
rename from lib/roi_data_layer/__init__.py
rename to faster_rcnn/lib/roi_data_layer/__init__.py
diff --git a/lib/roi_data_layer/minibatch.py b/faster_rcnn/lib/roi_data_layer/minibatch.py
similarity index 94%
rename from lib/roi_data_layer/minibatch.py
rename to faster_rcnn/lib/roi_data_layer/minibatch.py
index 4fb44328d..d80a9d3ed 100644
--- a/lib/roi_data_layer/minibatch.py
+++ b/faster_rcnn/lib/roi_data_layer/minibatch.py
@@ -12,9 +12,9 @@
 
 import numpy as np
 import numpy.random as npr
-from scipy.misc import imread
-from model.utils.config import cfg
-from model.utils.blob import prep_im_for_blob, im_list_to_blob
+from imageio  import imread
+from faster_rcnn.lib.model.utils.config import cfg
+from faster_rcnn.lib.model.utils.blob import prep_im_for_blob, im_list_to_blob
 import pdb
 def get_minibatch(roidb, num_classes):
   """Given a roidb, construct a minibatch sampled from it."""
@@ -33,13 +33,13 @@ def get_minibatch(roidb, num_classes):
 
   assert len(im_scales) == 1, "Single batch only"
   assert len(roidb) == 1, "Single batch only"
-  
+
   # gt boxes: (x1, y1, x2, y2, cls)
   if cfg.TRAIN.USE_ALL_GT:
     # Include all ground truth boxes
     gt_inds = np.where(roidb[0]['gt_classes'] != 0)[0]
   else:
-    # For the COCO ground truth boxes, exclude the ones that are ''iscrowd'' 
+    # For the COCO ground truth boxes, exclude the ones that are ''iscrowd''
     gt_inds = np.where((roidb[0]['gt_classes'] != 0) & np.all(roidb[0]['gt_overlaps'].toarray() > -1.0, axis=1))[0]
   gt_boxes = np.empty((len(gt_inds), 5), dtype=np.float32)
   gt_boxes[:, 0:4] = roidb[0]['boxes'][gt_inds, :] * im_scales[0]
diff --git a/lib/roi_data_layer/roibatchLoader.py b/faster_rcnn/lib/roi_data_layer/roibatchLoader.py
similarity index 97%
rename from lib/roi_data_layer/roibatchLoader.py
rename to faster_rcnn/lib/roi_data_layer/roibatchLoader.py
index 9b6e54ecf..016cc743f 100644
--- a/lib/roi_data_layer/roibatchLoader.py
+++ b/faster_rcnn/lib/roi_data_layer/roibatchLoader.py
@@ -10,9 +10,9 @@
 from PIL import Image
 import torch
 
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 from roi_data_layer.minibatch import get_minibatch, get_minibatch
-from model.rpn.bbox_transform import bbox_transform_inv, clip_boxes
+from faster_rcnn.lib.model.rpn.bbox_transform import bbox_transform_inv, clip_boxes
 
 import numpy as np
 import random
@@ -93,7 +93,7 @@ def __getitem__(self, index):
                 max_y = int(torch.max(gt_boxes[:,3]))
                 trim_size = int(np.floor(data_width / ratio))
                 if trim_size > data_height:
-                    trim_size = data_height                
+                    trim_size = data_height
                 box_region = max_y - min_y + 1
                 if min_y == 0:
                     y_s = 0
@@ -129,7 +129,7 @@ def __getitem__(self, index):
                 max_x = int(torch.max(gt_boxes[:,2]))
                 trim_size = int(np.ceil(data_height * ratio))
                 if trim_size > data_width:
-                    trim_size = data_width                
+                    trim_size = data_width
                 box_region = max_x - min_x + 1
                 if min_x == 0:
                     x_s = 0
diff --git a/lib/roi_data_layer/roidb.py b/faster_rcnn/lib/roi_data_layer/roidb.py
similarity index 96%
rename from lib/roi_data_layer/roidb.py
rename to faster_rcnn/lib/roi_data_layer/roidb.py
index df50e60c9..0570a193d 100644
--- a/lib/roi_data_layer/roidb.py
+++ b/faster_rcnn/lib/roi_data_layer/roidb.py
@@ -5,7 +5,7 @@
 
 import datasets
 import numpy as np
-from model.utils.config import cfg
+from faster_rcnn.lib.model.utils.config import cfg
 from datasets.factory import get_imdb
 import PIL
 import pdb
@@ -22,7 +22,7 @@ def prepare_roidb(imdb):
   if not (imdb.name.startswith('coco')):
     sizes = [PIL.Image.open(imdb.image_path_at(i)).size
          for i in range(imdb.num_images)]
-         
+
   for i in range(len(imdb.image_index)):
     roidb[i]['img_id'] = imdb.image_id_at(i)
     roidb[i]['image'] = imdb.image_path_at(i)
@@ -49,8 +49,8 @@ def prepare_roidb(imdb):
 def rank_roidb_ratio(roidb):
     # rank roidb based on the ratio between width and height.
     ratio_large = 2 # largest ratio to preserve.
-    ratio_small = 0.5 # smallest ratio to preserve.    
-    
+    ratio_small = 0.5 # smallest ratio to preserve.
+
     ratio_list = []
     for i in range(len(roidb)):
       width = roidb[i]['width']
@@ -62,7 +62,7 @@ def rank_roidb_ratio(roidb):
         ratio = ratio_large
       elif ratio < ratio_small:
         roidb[i]['need_crop'] = 1
-        ratio = ratio_small        
+        ratio = ratio_small
       else:
         roidb[i]['need_crop'] = 0
 
@@ -104,7 +104,7 @@ def get_training_roidb(imdb):
     print('done')
 
     return imdb.roidb
-  
+
   def get_roidb(imdb_name):
     imdb = get_imdb(imdb_name)
     print('Loaded dataset `{:s}` for training'.format(imdb.name))
diff --git a/faster_rcnn/scripts/__init__.py b/faster_rcnn/scripts/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/faster_rcnn/scripts/demo.py b/faster_rcnn/scripts/demo.py
new file mode 100644
index 000000000..08009d7b8
--- /dev/null
+++ b/faster_rcnn/scripts/demo.py
@@ -0,0 +1,398 @@
+# --------------------------------------------------------
+# Tensorflow Faster R-CNN
+# Licensed under The MIT License [see LICENSE for details]
+# Written by Jiasen Lu, Jianwei Yang, based on code from Ross Girshick
+# --------------------------------------------------------
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import faster_rcnn._init_paths
+import os
+import sys
+import numpy as np
+import argparse
+import pprint
+import pdb
+import time
+import cv2
+import torch
+from torch.autograd import Variable
+import torch.nn as nn
+import torch.optim as optim
+
+import torchvision.transforms as transforms
+import torchvision.datasets as dset
+from imageio  import imread
+from roi_data_layer.roidb import combined_roidb
+from roi_data_layer.roibatchLoader import roibatchLoader
+from faster_rcnn.lib.model.utils.config import cfg, cfg_from_file, cfg_from_list, get_output_dir
+from faster_rcnn.lib.model.rpn.bbox_transform import clip_boxes
+# from faster_rcnn.lib.model.nms.nms_wrapper import nms
+from faster_rcnn.lib.model.roi_layers import nms
+from faster_rcnn.lib.model.rpn.bbox_transform import bbox_transform_inv
+from faster_rcnn.lib.model.utils.net_utils import save_net, load_net, vis_detections
+from faster_rcnn.lib.model.utils.blob import im_list_to_blob
+from faster_rcnn.lib.model.faster_rcnn.vgg16 import vgg16
+from faster_rcnn.lib.model.faster_rcnn.resnet import resnet
+import pdb
+
+try:
+    xrange          # Python 2
+except NameError:
+    xrange = range  # Python 3
+
+
+def parse_args():
+    """
+    Parse input arguments
+    """
+    parser = argparse.ArgumentParser(description='Train a Fast R-CNN network')
+    parser.add_argument('--dataset', dest='dataset',
+                        help='training dataset',
+                        default='pascal_voc', type=str)
+    parser.add_argument('--cfg', dest='cfg_file',
+                        help='optional config file',
+                        default=
+                        os.path.join(os.sep.join(faster_rcnn.__file__.split(os.sep)[:-1]),
+                            'cfgs', 'vgg16.yml'), type=str)
+    parser.add_argument('--net', dest='net',
+                        help='vgg16, res50, res101, res152',
+                        default='res101', type=str)
+    parser.add_argument('--set', dest='set_cfgs',
+                        help='set config keys', default=None,
+                        nargs=argparse.REMAINDER)
+    parser.add_argument('--load_dir', dest='load_dir',
+                        help='directory to load models',
+                        default="/srv/share/jyang375/models")
+    parser.add_argument('--image_dir', dest='image_dir',
+                        help='directory to load images for demo',
+                        default="images")
+    parser.add_argument('--cuda', dest='cuda',
+                        help='whether use CUDA',
+                        action='store_true')
+    parser.add_argument('--mGPUs', dest='mGPUs',
+                        help='whether use multiple GPUs',
+                        action='store_true')
+    parser.add_argument('--cag', dest='class_agnostic',
+                        help='whether perform class_agnostic bbox regression',
+                        action='store_true')
+    parser.add_argument('--parallel_type', dest='parallel_type',
+                        help='which part of model to parallel, 0: all, 1: model before roi pooling',
+                        default=0, type=int)
+    parser.add_argument('--checksession', dest='checksession',
+                        help='checksession to load model',
+                        default=1, type=int)
+    parser.add_argument('--checkepoch', dest='checkepoch',
+                        help='checkepoch to load network',
+                        default=1, type=int)
+    parser.add_argument('--checkpoint', dest='checkpoint',
+                        help='checkpoint to load network',
+                        default=10021, type=int)
+    parser.add_argument('--bs', dest='batch_size',
+                        help='batch_size',
+                        default=1, type=int)
+    parser.add_argument('--vis', dest='vis',
+                        help='visualization mode',
+                        action='store_true')
+    parser.add_argument('--webcam_num', dest='webcam_num',
+                        help='webcam ID number',
+                        default=-1, type=int)
+
+    args = parser.parse_args()
+    return args
+
+
+lr = cfg.TRAIN.LEARNING_RATE
+momentum = cfg.TRAIN.MOMENTUM
+weight_decay = cfg.TRAIN.WEIGHT_DECAY
+
+
+def _get_image_blob(im):
+    """Converts an image into a network input.
+    Arguments:
+      im (ndarray): a color image in BGR order
+    Returns:
+      blob (ndarray): a data blob holding an image pyramid
+      im_scale_factors (list): list of image scales (relative to im) used
+        in the image pyramid
+    """
+    im_orig = im.astype(np.float32, copy=True)
+    im_orig -= cfg.PIXEL_MEANS
+
+    im_shape = im_orig.shape
+    im_size_min = np.min(im_shape[0:2])
+    im_size_max = np.max(im_shape[0:2])
+
+    processed_ims = []
+    im_scale_factors = []
+
+    for target_size in cfg.TEST.SCALES:
+        im_scale = float(target_size) / float(im_size_min)
+        # Prevent the biggest axis from being more than MAX_SIZE
+        if np.round(im_scale * im_size_max) > cfg.TEST.MAX_SIZE:
+            im_scale = float(cfg.TEST.MAX_SIZE) / float(im_size_max)
+        im = cv2.resize(im_orig, None, None, fx=im_scale, fy=im_scale,
+                        interpolation=cv2.INTER_LINEAR)
+        im_scale_factors.append(im_scale)
+        processed_ims.append(im)
+
+    # Create a blob to hold the input images
+    blob = im_list_to_blob(processed_ims)
+
+    return blob, np.array(im_scale_factors)
+
+
+def 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.USE_GPU_NMS = args.cuda
+
+    print('Using config:')
+    pprint.pprint(cfg)
+    np.random.seed(cfg.RNG_SEED)
+
+    # train set
+    # -- Note: Use validation set and disable the flipped to enable faster loading.
+
+    input_dir = args.load_dir + "/" + args.net + "/" + args.dataset
+    if not os.path.exists(input_dir):
+        raise Exception(
+            'There is no input directory for loading network from ' + input_dir)
+    load_name = os.path.join(input_dir,
+                             'faster_rcnn_{}_{}_{}.pth'.format(args.checksession, args.checkepoch, args.checkpoint))
+
+    pascal_classes = np.asarray(['__background__',
+                                 'aeroplane', 'bicycle', 'bird', 'boat',
+                                 'bottle', 'bus', 'car', 'cat', 'chair',
+                                 'cow', 'diningtable', 'dog', 'horse',
+                                 'motorbike', 'person', 'pottedplant',
+                                 'sheep', 'sofa', 'train', 'tvmonitor'])
+
+    # initilize the network here.
+    if args.net == 'vgg16':
+        fasterRCNN = vgg16(pascal_classes, pretrained=False,
+                           class_agnostic=args.class_agnostic)
+    elif args.net == 'res101':
+        fasterRCNN = resnet(pascal_classes, 101, pretrained=False,
+                            class_agnostic=args.class_agnostic)
+    elif args.net == 'res50':
+        fasterRCNN = resnet(pascal_classes, 50, pretrained=False,
+                            class_agnostic=args.class_agnostic)
+    elif args.net == 'res152':
+        fasterRCNN = resnet(pascal_classes, 152, pretrained=False,
+                            class_agnostic=args.class_agnostic)
+    else:
+        print("network is not defined")
+        pdb.set_trace()
+
+    fasterRCNN.create_architecture()
+
+    print("load checkpoint %s" % (load_name))
+    if args.cuda > 0:
+        checkpoint = torch.load(load_name)
+    else:
+        checkpoint = torch.load(
+            load_name, map_location=(lambda storage, loc: storage))
+    fasterRCNN.load_state_dict(checkpoint['model'])
+    if 'pooling_mode' in checkpoint.keys():
+        cfg.POOLING_MODE = checkpoint['pooling_mode']
+
+    print('load model successfully!')
+
+    # pdb.set_trace()
+
+    print("load checkpoint %s" % (load_name))
+
+    # initilize the tensor holder here.
+    im_data = torch.FloatTensor(1)
+    im_info = torch.FloatTensor(1)
+    num_boxes = torch.LongTensor(1)
+    gt_boxes = torch.FloatTensor(1)
+
+    # ship to cuda
+    if args.cuda > 0:
+        im_data = im_data.cuda()
+        im_info = im_info.cuda()
+        num_boxes = num_boxes.cuda()
+        gt_boxes = gt_boxes.cuda()
+
+    # make variable
+    im_data = Variable(im_data, volatile=True)
+    im_info = Variable(im_info, volatile=True)
+    num_boxes = Variable(num_boxes, volatile=True)
+    gt_boxes = Variable(gt_boxes, volatile=True)
+
+    if args.cuda > 0:
+        cfg.CUDA = True
+
+    if args.cuda > 0:
+        fasterRCNN.cuda()
+
+    fasterRCNN.eval()
+
+    start = time.time()
+    max_per_image = 100
+    thresh = 0.05
+    vis = True
+
+    webcam_num = args.webcam_num
+    # Set up webcam or get image directories
+    if webcam_num >= 0:
+        cap = cv2.VideoCapture(webcam_num)
+        num_images = 0
+    else:
+        imglist = os.listdir(args.image_dir)
+        num_images = len(imglist)
+
+    print('Loaded Photo: {} images.'.format(num_images))
+
+    while (num_images >= 0):
+        total_tic = time.time()
+        if webcam_num == -1:
+            num_images -= 1
+
+        # Get image from the webcam
+        if webcam_num >= 0:
+            if not cap.isOpened():
+                raise RuntimeError(
+                    "Webcam could not open. Please check connection.")
+            ret, frame = cap.read()
+            im_in = np.array(frame)
+        # Load the demo image
+        else:
+            im_file = os.path.join(args.image_dir, imglist[num_images])
+            # im = cv2.imread(im_file)
+            im_in = np.array(imread(im_file))
+        if len(im_in.shape) == 2:
+            im_in = im_in[:, :, np.newaxis]
+            im_in = np.concatenate((im_in, im_in, im_in), axis=2)
+        # rgb -> bgr
+        im = im_in[:, :, ::-1]
+
+        blobs, im_scales = _get_image_blob(im)
+        assert len(im_scales) == 1, "Only single-image batch implemented"
+        im_blob = blobs
+        im_info_np = np.array(
+            [[im_blob.shape[1], im_blob.shape[2], im_scales[0]]], dtype=np.float32)
+
+        im_data_pt = torch.from_numpy(im_blob)
+        im_data_pt = im_data_pt.permute(0, 3, 1, 2)
+        im_info_pt = torch.from_numpy(im_info_np)
+
+        with torch.no_grad():
+            im_data.resize_(im_data_pt.size()).copy_(im_data_pt)
+            im_info.resize_(im_info_pt.size()).copy_(im_info_pt)
+            gt_boxes.resize_(1, 1, 5).zero_()
+            num_boxes.resize_(1).zero_()
+
+        # pdb.set_trace()
+        det_tic = time.time()
+
+        rois, cls_prob, bbox_pred, \
+            rpn_loss_cls, rpn_loss_box, \
+            RCNN_loss_cls, RCNN_loss_bbox, \
+            rois_label = fasterRCNN(im_data, im_info, gt_boxes, num_boxes)
+
+        scores = cls_prob.data
+        boxes = rois.data[:, :, 1:5]
+
+        if cfg.TEST.BBOX_REG:
+                # Apply bounding-box regression deltas
+            box_deltas = bbox_pred.data
+            if cfg.TRAIN.BBOX_NORMALIZE_TARGETS_PRECOMPUTED:
+                # Optionally normalize targets by a precomputed mean and stdev
+                if args.class_agnostic:
+                    if args.cuda > 0:
+                        box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS).cuda() \
+                            + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS).cuda()
+                    else:
+                        box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS) \
+                            + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS)
+
+                    box_deltas = box_deltas.view(1, -1, 4)
+                else:
+                    if args.cuda > 0:
+                        box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS).cuda() \
+                            + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS).cuda()
+                    else:
+                        box_deltas = box_deltas.view(-1, 4) * torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_STDS) \
+                            + torch.FloatTensor(cfg.TRAIN.BBOX_NORMALIZE_MEANS)
+                    box_deltas = box_deltas.view(
+                        1, -1, 4 * len(pascal_classes))
+
+            pred_boxes = bbox_transform_inv(boxes, box_deltas, 1)
+            pred_boxes = clip_boxes(pred_boxes, im_info.data, 1)
+        else:
+            # Simply repeat the boxes, once for each class
+            pred_boxes = np.tile(boxes, (1, scores.shape[1]))
+
+        pred_boxes /= im_scales[0]
+
+        scores = scores.squeeze()
+        pred_boxes = pred_boxes.squeeze()
+        det_toc = time.time()
+        detect_time = det_toc - det_tic
+        misc_tic = time.time()
+        if vis:
+            im2show = np.copy(im)
+        for j in xrange(1, len(pascal_classes)):
+            inds = torch.nonzero(scores[:, j] > thresh).view(-1)
+            # if there is det
+            if inds.numel() > 0:
+                cls_scores = scores[:, j][inds]
+                _, order = torch.sort(cls_scores, 0, True)
+                if args.class_agnostic:
+                    cls_boxes = pred_boxes[inds, :]
+                else:
+                    cls_boxes = pred_boxes[inds][:, j * 4:(j + 1) * 4]
+
+                cls_dets = torch.cat((cls_boxes, cls_scores.unsqueeze(1)), 1)
+                # cls_dets = torch.cat((cls_boxes, cls_scores), 1)
+                cls_dets = cls_dets[order]
+                # keep = nms(cls_dets, cfg.TEST.NMS, force_cpu=not cfg.USE_GPU_NMS)
+                keep = nms(cls_boxes[order, :],
+                           cls_scores[order], cfg.TEST.NMS)
+                cls_dets = cls_dets[keep.view(-1).long()]
+                if vis:
+                    im2show = vis_detections(
+                        im2show, pascal_classes[j], cls_dets.cpu().numpy(), 0.5)
+
+        misc_toc = time.time()
+        nms_time = misc_toc - misc_tic
+
+        if webcam_num == -1:
+            sys.stdout.write('im_detect: {:d}/{:d} {:.3f}s {:.3f}s   \r'
+                             .format(num_images + 1, len(imglist), detect_time, nms_time))
+            sys.stdout.flush()
+
+        if vis and webcam_num == -1:
+            # cv2.imshow('test', im2show)
+            # cv2.waitKey(0)
+            result_path = os.path.join(
+                args.image_dir, imglist[num_images][:-4] + "_det.jpg")
+            cv2.imwrite(result_path, im2show)
+        else:
+            im2showRGB = cv2.cvtColor(im2show, cv2.COLOR_BGR2RGB)
+            cv2.imshow("frame", im2showRGB)
+            total_toc = time.time()
+            total_time = total_toc - total_tic
+            frame_rate = 1 / total_time
+            print('Frame rate:', frame_rate)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+    if webcam_num >= 0:
+        cap.release()
+        cv2.destroyAllWindows()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/test_net.py b/faster_rcnn/scripts/test_net.py
similarity index 92%
rename from test_net.py
rename to faster_rcnn/scripts/test_net.py
index 7e8522a2a..abc5f3b6c 100644
--- a/test_net.py
+++ b/faster_rcnn/scripts/test_net.py
@@ -7,7 +7,7 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
+import faster_rcnn._init_paths
 import os
 import sys
 import numpy as np
@@ -25,14 +25,14 @@
 import pickle
 from roi_data_layer.roidb import combined_roidb
 from roi_data_layer.roibatchLoader import roibatchLoader
-from model.utils.config import cfg, cfg_from_file, cfg_from_list, get_output_dir
-from model.rpn.bbox_transform import clip_boxes
-# from model.nms.nms_wrapper import nms
-from model.roi_layers import nms
-from model.rpn.bbox_transform import bbox_transform_inv
-from model.utils.net_utils import save_net, load_net, vis_detections
-from model.faster_rcnn.vgg16 import vgg16
-from model.faster_rcnn.resnet import resnet
+from faster_rcnn.lib.model.utils.config import cfg, cfg_from_file, cfg_from_list, get_output_dir
+from faster_rcnn.lib.model.rpn.bbox_transform import clip_boxes
+# from faster_rcnn.lib.model.nms.nms_wrapper import nms
+from faster_rcnn.lib.model.roi_layers import nms
+from faster_rcnn.lib.model.rpn.bbox_transform import bbox_transform_inv
+from faster_rcnn.lib.model.utils.net_utils import save_net, load_net, vis_detections
+from faster_rcnn.lib.model.faster_rcnn.vgg16 import vgg16
+from faster_rcnn.lib.model.faster_rcnn.resnet import resnet
 
 try:
     xrange          # Python 2
@@ -50,7 +50,8 @@ def parse_args():
                       default='pascal_voc', type=str)
   parser.add_argument('--cfg', dest='cfg_file',
                       help='optional config file',
-                      default='cfgs/vgg16.yml', type=str)
+                      default=os.path.join(os.sep.join(faster_rcnn.__file__.split(os.sep)[:-1]),
+                            'cfgs', 'vgg16.yml'), type=str)
   parser.add_argument('--net', dest='net',
                       help='vgg16, res50, res101, res152',
                       default='res101', type=str)
@@ -94,8 +95,7 @@ def parse_args():
 momentum = cfg.TRAIN.MOMENTUM
 weight_decay = cfg.TRAIN.WEIGHT_DECAY
 
-if __name__ == '__main__':
-
+def main():
   args = parse_args()
 
   print('Called with args:')
@@ -126,7 +126,10 @@ def parse_args():
       args.imdbval_name = "vg_150-50-50_minival"
       args.set_cfgs = ['ANCHOR_SCALES', '[4, 8, 16, 32]', 'ANCHOR_RATIOS', '[0.5,1,2]']
 
-  args.cfg_file = "cfgs/{}_ls.yml".format(args.net) if args.large_scale else "cfgs/{}.yml".format(args.net)
+  args.cfg_file = os.path.join(os.sep.join(faster_rcnn.__file__.split(os.sep)[:-1]),
+                            'cfgs',
+                            ("{}_ls.yml".format(args.net) if
+                             args.large_scale else "{}.yml".format(args.net)))
 
   if args.cfg_file is not None:
     cfg_from_file(args.cfg_file)
@@ -283,7 +286,7 @@ def parse_args():
               cls_boxes = pred_boxes[inds, :]
             else:
               cls_boxes = pred_boxes[inds][:, j * 4:(j + 1) * 4]
-            
+
             cls_dets = torch.cat((cls_boxes, cls_scores.unsqueeze(1)), 1)
             # cls_dets = torch.cat((cls_boxes, cls_scores), 1)
             cls_dets = cls_dets[order]
@@ -326,3 +329,5 @@ def parse_args():
 
   end = time.time()
   print("test time: %0.4fs" % (end - start))
+if __name__ == '__main__':
+  main()
\ No newline at end of file
diff --git a/trainval_net.py b/faster_rcnn/scripts/trainval_net.py
similarity index 97%
rename from trainval_net.py
rename to faster_rcnn/scripts/trainval_net.py
index 4bc817307..e0dfe3f73 100644
--- a/trainval_net.py
+++ b/faster_rcnn/scripts/trainval_net.py
@@ -7,7 +7,7 @@
 from __future__ import division
 from __future__ import print_function
 
-import _init_paths
+import faster_rcnn._init_paths
 import os
 import sys
 import numpy as np
@@ -26,12 +26,12 @@
 
 from roi_data_layer.roidb import combined_roidb
 from roi_data_layer.roibatchLoader import roibatchLoader
-from model.utils.config import cfg, cfg_from_file, cfg_from_list, get_output_dir
-from model.utils.net_utils import weights_normal_init, save_net, load_net, \
+from faster_rcnn.lib.model.utils.config import cfg, cfg_from_file, cfg_from_list, get_output_dir
+from faster_rcnn.lib.model.utils.net_utils import weights_normal_init, save_net, load_net, \
       adjust_learning_rate, save_checkpoint, clip_gradient
 
-from model.faster_rcnn.vgg16 import vgg16
-from model.faster_rcnn.resnet import resnet
+from faster_rcnn.lib.model.faster_rcnn.vgg16 import vgg16
+from faster_rcnn.lib.model.faster_rcnn.resnet import resnet
 
 def parse_args():
   """
@@ -68,7 +68,7 @@ def parse_args():
                       action='store_true')
   parser.add_argument('--ls', dest='large_scale',
                       help='whether use large imag scale',
-                      action='store_true')                      
+                      action='store_true')
   parser.add_argument('--mGPUs', dest='mGPUs',
                       help='whether use multiple GPUs',
                       action='store_true')
@@ -145,8 +145,8 @@ def __iter__(self):
   def __len__(self):
     return self.num_data
 
-if __name__ == '__main__':
 
+def main():
   args = parse_args()
 
   print('Called with args:')
@@ -264,7 +264,7 @@ def __len__(self):
 
   if args.cuda:
     fasterRCNN.cuda()
-      
+
   if args.optimizer == "adam":
     lr = lr * 0.1
     optimizer = torch.optim.Adam(params)
@@ -369,7 +369,7 @@ def __len__(self):
         loss_temp = 0
         start = time.time()
 
-    
+
     save_name = os.path.join(output_dir, 'faster_rcnn_{}_{}_{}.pth'.format(args.session, epoch, step))
     save_checkpoint({
       'session': args.session,
@@ -383,3 +383,6 @@ def __len__(self):
 
   if args.use_tfboard:
     logger.close()
+
+if __name__ == '__main__':
+  main()
\ No newline at end of file
diff --git a/lib/model/nms/src/nms_cuda.c b/lib/model/nms/src/nms_cuda.c
deleted file mode 100644
index 3667c7d2f..000000000
--- a/lib/model/nms/src/nms_cuda.c
+++ /dev/null
@@ -1,19 +0,0 @@
-#include <THC/THC.h>
-#include <stdio.h>
-#include "nms_cuda_kernel.h"
-
-// this symbol will be resolved automatically from PyTorch libs
-extern THCState *state;
-
-int nms_cuda(THCudaIntTensor *keep_out, THCudaTensor *boxes_host,
-		     THCudaIntTensor *num_out, float nms_overlap_thresh) {
-
-	nms_cuda_compute(THCudaIntTensor_data(state, keep_out), 
-		         THCudaIntTensor_data(state, num_out), 
-      	                 THCudaTensor_data(state, boxes_host), 
-		         THCudaTensor_size(state, boxes_host, 0),
-		         THCudaTensor_size(state, boxes_host, 1),
-		         nms_overlap_thresh);
-
-	return 1;
-}
diff --git a/lib/model/roi_crop/_ext/crop_resize/_crop_resize.so b/lib/model/roi_crop/_ext/crop_resize/_crop_resize.so
deleted file mode 100755
index 9baf6615c..000000000
Binary files a/lib/model/roi_crop/_ext/crop_resize/_crop_resize.so and /dev/null differ
diff --git a/lib/setup.py b/setup.py
similarity index 62%
rename from lib/setup.py
rename to setup.py
index 7e7e20018..043b38406 100644
--- a/lib/setup.py
+++ b/setup.py
@@ -11,11 +11,11 @@
 from torch.utils.cpp_extension import CppExtension
 from torch.utils.cpp_extension import CUDAExtension
 
-requirements = ["torch", "torchvision"]
-
+with open('requirements.txt') as inp:
+    requirements = inp.read().splitlines()
 
 def get_extensions():
-    this_dir = os.path.dirname(os.path.abspath(__file__))
+    this_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'faster_rcnn', 'lib')
     extensions_dir = os.path.join(this_dir, "model", "csrc")
 
     main_file = glob.glob(os.path.join(extensions_dir, "*.cpp"))
@@ -45,7 +45,7 @@ def get_extensions():
 
     ext_modules = [
         extension(
-            "model._C",
+            "faster_rcnn.lib.model._C",
             sources,
             include_dirs=include_dirs,
             define_macros=define_macros,
@@ -56,12 +56,30 @@ def get_extensions():
     return ext_modules
 
 
+def get_scripts_dict():
+    """Construct the scripts dictionary, ie the dictionary of the executables
+    """
+    scripts_dict = {}
+    for root, _, files in os.walk(os.path.join('faster_rcnn', 'scripts')):
+        for fil in files:
+            if fil.endswith('.py') and fil != '__init__.py':
+                path = os.path.join(root, fil)
+                module = 'faster_rcnn' + '.'.join(path.split(
+                    'faster_rcnn')[-1][:-3].split(os.sep)) + ":main"
+                scripts_dict[fil[:-3]] = module
+    return scripts_dict
+
+
 setup(
     name="faster_rcnn",
-    version="0.1",
+    version="0.2",
     description="object detection in pytorch",
-    packages=find_packages(exclude=("configs", "tests",)),
-    # install_requires=requirements,
+    install_requires=requirements,
+    packages=find_packages(),
     ext_modules=get_extensions(),
     cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},
+    entry_points={
+        'console_scripts': [
+            "faster_rcnn_" + script +
+            '=' + d[script] for d in [get_scripts_dict()] for script in d]}
 )