SYMBOL INDEX (596 symbols across 80 files)

FILE: dff_rfcn/_init_paths.py
  function add_path (line 11) | def add_path(path):

FILE: dff_rfcn/config/config.py
  function update_config (line 157) | def update_config(config_file):

FILE: dff_rfcn/core/DataParallelExecutorGroup.py
  function _load_general (line 24) | def _load_general(data, targets, major_axis):
  function _load_data (line 37) | def _load_data(batch, targets, major_axis):
  function _load_label (line 42) | def _load_label(batch, targets, major_axis):
  function _merge_multi_context (line 47) | def _merge_multi_context(outputs, major_axis):
  class DataParallelExecutorGroup (line 64) | class DataParallelExecutorGroup(object):
    method __init__ (line 108) | def __init__(self, symbol, contexts, workload, data_shapes, label_shap...
    method decide_slices (line 193) | def decide_slices(self, data_shapes):
    method _collect_arrays (line 219) | def _collect_arrays(self):
    method bind_exec (line 253) | def bind_exec(self, data_shapes, label_shapes, shared_group=None, resh...
    method reshape (line 283) | def reshape(self, data_shapes, label_shapes):
    method set_params (line 302) | def set_params(self, arg_params, aux_params):
    method get_params (line 315) | def get_params(self, arg_params, aux_params):
    method forward (line 336) | def forward(self, data_batch, is_train=None):
    method get_outputs (line 363) | def get_outputs(self, merge_multi_context=True):
    method get_states (line 386) | def get_states(self, merge_multi_context=True):
    method set_states (line 407) | def set_states(self, states=None, value=None):
    method get_input_grads (line 428) | def get_input_grads(self, merge_multi_context=True):
    method backward (line 450) | def backward(self, out_grads=None):
    method update_metric (line 470) | def update_metric(self, eval_metric, labels):
    method _bind_ith_exec (line 483) | def _bind_ith_exec(self, i, data_shapes, label_shapes, shared_group):
    method _sliced_shape (line 575) | def _sliced_shape(self, shapes, i, major_axis):
    method install_monitor (line 593) | def install_monitor(self, mon):

FILE: dff_rfcn/core/callback.py
  class Speedometer (line 19) | class Speedometer(object):
    method __init__ (line 20) | def __init__(self, batch_size, frequent=50):
    method __call__ (line 27) | def __call__(self, param):
  function do_checkpoint (line 54) | def do_checkpoint(prefix, means, stds):

FILE: dff_rfcn/core/loader.py
  class TestLoader (line 23) | class TestLoader(mx.io.DataIter):
    method __init__ (line 24) | def __init__(self, roidb, config, batch_size=1, shuffle=False,
    method provide_data (line 62) | def provide_data(self):
    method provide_label (line 66) | def provide_label(self):
    method provide_data_single (line 70) | def provide_data_single(self):
    method provide_label_single (line 74) | def provide_label_single(self):
    method reset (line 77) | def reset(self):
    method iter_next (line 82) | def iter_next(self):
    method next (line 85) | def next(self):
    method getindex (line 102) | def getindex(self):
    method getpad (line 105) | def getpad(self):
    method get_batch (line 111) | def get_batch(self):
  class AnchorLoader (line 131) | class AnchorLoader(mx.io.DataIter):
    method __init__ (line 133) | def __init__(self, feat_sym, roidb, cfg, batch_size=1, shuffle=False, ...
    method provide_data (line 194) | def provide_data(self):
    method provide_label (line 198) | def provide_label(self):
    method provide_data_single (line 202) | def provide_data_single(self):
    method provide_label_single (line 206) | def provide_label_single(self):
    method reset (line 209) | def reset(self):
    method iter_next (line 228) | def iter_next(self):
    method next (line 231) | def next(self):
    method getindex (line 241) | def getindex(self):
    method getpad (line 244) | def getpad(self):
    method infer_shape (line 250) | def infer_shape(self, max_data_shape=None, max_label_shape=None):
    method get_batch (line 267) | def get_batch(self):
    method get_batch_individual (line 326) | def get_batch_individual(self):
    method parfetch (line 347) | def parfetch(self, iroidb):

FILE: dff_rfcn/core/metric.py
  function get_rpn_names (line 18) | def get_rpn_names():
  function get_rcnn_names (line 24) | def get_rcnn_names(cfg):
  class RPNAccMetric (line 36) | class RPNAccMetric(mx.metric.EvalMetric):
    method __init__ (line 37) | def __init__(self):
    method update (line 41) | def update(self, labels, preds):
  class RCNNAccMetric (line 60) | class RCNNAccMetric(mx.metric.EvalMetric):
    method __init__ (line 61) | def __init__(self, cfg):
    method update (line 67) | def update(self, labels, preds):
  class RPNLogLossMetric (line 87) | class RPNLogLossMetric(mx.metric.EvalMetric):
    method __init__ (line 88) | def __init__(self):
    method update (line 92) | def update(self, labels, preds):
  class RCNNLogLossMetric (line 114) | class RCNNLogLossMetric(mx.metric.EvalMetric):
    method __init__ (line 115) | def __init__(self, cfg):
    method update (line 121) | def update(self, labels, preds):
  class RPNL1LossMetric (line 144) | class RPNL1LossMetric(mx.metric.EvalMetric):
    method __init__ (line 145) | def __init__(self):
    method update (line 149) | def update(self, labels, preds):
  class RCNNL1LossMetric (line 160) | class RCNNL1LossMetric(mx.metric.EvalMetric):
    method __init__ (line 161) | def __init__(self, cfg):
    method update (line 167) | def update(self, labels, preds):

FILE: dff_rfcn/core/module.py
  class Module (line 35) | class Module(BaseModule):
    method __init__ (line 59) | def __init__(self, symbol, data_names=('data',), label_names=('softmax...
    method load (line 110) | def load(prefix, epoch, load_optimizer_states=False, **kwargs):
    method save_checkpoint (line 148) | def save_checkpoint(self, prefix, epoch, save_optimizer_states=False):
    method _reset_bind (line 170) | def _reset_bind(self):
    method data_names (line 178) | def data_names(self):
    method label_names (line 183) | def label_names(self):
    method output_names (line 188) | def output_names(self):
    method data_shapes (line 193) | def data_shapes(self):
    method label_shapes (line 203) | def label_shapes(self):
    method output_shapes (line 215) | def output_shapes(self):
    method get_params (line 224) | def get_params(self):
    method init_params (line 237) | def init_params(self, initializer=Uniform(0.01), arg_params=None, aux_...
    method set_params (line 295) | def set_params(self, arg_params, aux_params, allow_missing=False, forc...
    method bind (line 333) | def bind(self, data_shapes, label_shapes=None, for_training=True,
    method reshape (line 430) | def reshape(self, data_shapes, label_shapes=None):
    method init_optimizer (line 449) | def init_optimizer(self, kvstore='local', optimizer='sgd',
    method borrow_optimizer (line 527) | def borrow_optimizer(self, shared_module):
    method forward (line 542) | def forward(self, data_batch, is_train=None):
    method backward (line 555) | def backward(self, out_grads=None):
    method update (line 568) | def update(self):
    method get_outputs (line 586) | def get_outputs(self, merge_multi_context=True):
    method get_input_grads (line 606) | def get_input_grads(self, merge_multi_context=True):
    method get_states (line 626) | def get_states(self, merge_multi_context=True):
    method set_states (line 646) | def set_states(self, states=None, value=None):
    method update_metric (line 660) | def update_metric(self, eval_metric, labels):
    method _sync_params_from_devices (line 671) | def _sync_params_from_devices(self):
    method save_optimizer_states (line 679) | def save_optimizer_states(self, fname):
    method load_optimizer_states (line 695) | def load_optimizer_states(self, fname):
    method install_monitor (line 710) | def install_monitor(self, mon):
  class MutableModule (line 716) | class MutableModule(BaseModule):
    method __init__ (line 731) | def __init__(self, symbol, data_names, label_names,
    method _reset_bind (line 755) | def _reset_bind(self):
    method data_names (line 760) | def data_names(self):
    method output_names (line 764) | def output_names(self):
    method data_shapes (line 768) | def data_shapes(self):
    method label_shapes (line 773) | def label_shapes(self):
    method output_shapes (line 778) | def output_shapes(self):
    method get_params (line 782) | def get_params(self):
    method init_params (line 786) | def init_params(self, initializer=Uniform(0.01), arg_params=None, aux_...
    method bind (line 796) | def bind(self, data_shapes, label_shapes=None, for_training=True,
    method save_checkpoint (line 852) | def save_checkpoint(self, prefix, epoch, save_optimizer_states=False):
    method init_optimizer (line 867) | def init_optimizer(self, kvstore='local', optimizer='sgd',
    method fit (line 879) | def fit(self, train_data, eval_data=None, eval_metric='acc',
    method forward (line 1016) | def forward(self, data_batch, is_train=None):
    method backward (line 1051) | def backward(self, out_grads=None):
    method update (line 1055) | def update(self):
    method get_outputs (line 1059) | def get_outputs(self, merge_multi_context=True):
    method get_input_grads (line 1062) | def get_input_grads(self, merge_multi_context=True):
    method update_metric (line 1066) | def update_metric(self, eval_metric, labels):
    method install_monitor (line 1070) | def install_monitor(self, mon):

FILE: dff_rfcn/core/rcnn.py
  function get_rcnn_testbatch (line 36) | def get_rcnn_testbatch(roidb, cfg):
  function get_rcnn_batch (line 58) | def get_rcnn_batch(roidb, cfg):
  function sample_rois (line 126) | def sample_rois(rois, fg_rois_per_image, rois_per_image, num_classes, cfg,

FILE: dff_rfcn/core/tester.py
  class Predictor (line 28) | class Predictor(object):
    method __init__ (line 29) | def __init__(self, symbol, data_names, label_names,
    method predict (line 38) | def predict(self, data_batch):
  function im_proposal (line 44) | def im_proposal(predictor, data_batch, data_names, scales):
  function generate_proposals (line 64) | def generate_proposals(predictor, test_data, imdb, cfg, vis=False, thres...
  function im_detect (line 130) | def im_detect(predictor, data_batch, data_names, scales, cfg):
  function im_batch_detect (line 164) | def im_batch_detect(predictor, data_batch, data_names, scales, cfg):
  function pred_eval (line 193) | def pred_eval(gpu_id, key_predictor, cur_predictor, test_data, imdb, cfg...
  function pred_eval_multiprocess (line 295) | def pred_eval_multiprocess(gpu_num, key_predictors, cur_predictors, test...
  function vis_all_detection (line 308) | def vis_all_detection(im_array, detections, class_names, scale, cfg, thr...
  function draw_all_detection (line 342) | def draw_all_detection(im_array, detections, class_names, scale, cfg, th...

FILE: dff_rfcn/demo.py
  function parse_args (line 36) | def parse_args():
  function main (line 43) | def main():

FILE: dff_rfcn/demo_batch.py
  function parse_args (line 36) | def parse_args():
  function main (line 43) | def main():

FILE: dff_rfcn/function/test_rcnn.py
  function get_predictor (line 28) | def get_predictor(sym, sym_instance, cfg, arg_params, aux_params, test_d...
  function test_rcnn (line 47) | def test_rcnn(cfg, dataset, image_set, root_path, dataset_path,

FILE: dff_rfcn/function/test_rpn.py
  function test_rpn (line 26) | def test_rpn(cfg, dataset, image_set, root_path, dataset_path,

FILE: dff_rfcn/function/train_rcnn.py
  function train_rcnn (line 31) | def train_rcnn(cfg, dataset, image_set, root_path, dataset_path,

FILE: dff_rfcn/function/train_rpn.py
  function train_rpn (line 29) | def train_rpn(cfg, dataset, image_set, root_path, dataset_path,

FILE: dff_rfcn/operator_cxx/multi_proposal-inl.h
  function namespace (line 26) | namespace mxnet {
  function namespace (line 115) | namespace mxnet {
  function namespace (line 252) | namespace mxnet {

FILE: dff_rfcn/operator_cxx/multi_proposal.cc
  type mxnet (line 12) | namespace mxnet {
    type op (line 13) | namespace op {
      class MultiProposalOp (line 16) | class MultiProposalOp : public Operator{
        method MultiProposalOp (line 18) | explicit MultiProposalOp(MultiProposalParam param) {
        method Forward (line 22) | virtual void Forward(const OpContext &ctx,
        method Backward (line 30) | virtual void Backward(const OpContext &ctx,
      function Operator (line 45) | Operator *CreateOp<cpu>(MultiProposalParam param) {
      function Operator (line 49) | Operator* MultiProposalProp::CreateOperator(Context ctx) const {

FILE: dff_rfcn/operator_cxx/psroi_pooling-inl.h
  function namespace (line 23) | namespace mxnet {

FILE: dff_rfcn/operator_cxx/psroi_pooling.cc
  type mshadow (line 21) | namespace mshadow {
    function PSROIPoolForward (line 23) | inline void PSROIPoolForward(const Tensor<cpu, 4, DType> &out,
    function PSROIPoolBackwardAcc (line 35) | inline void PSROIPoolBackwardAcc(const Tensor<cpu, 4, DType> &in_grad,
  type mxnet (line 46) | namespace mxnet {
    type op (line 47) | namespace op {
      function Operator (line 50) | Operator *CreateOp<cpu>(PSROIPoolingParam param, int dtype) {
      function Operator (line 58) | Operator *PSROIPoolingProp::CreateOperatorEx(Context ctx, std::vecto...

FILE: dff_rfcn/operator_py/box_annotator_ohem.py
  class BoxAnnotatorOHEMOperator (line 19) | class BoxAnnotatorOHEMOperator(mx.operator.CustomOp):
    method __init__ (line 20) | def __init__(self, num_classes, num_reg_classes, roi_per_img):
    method forward (line 26) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 56) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class BoxAnnotatorOHEMProp (line 62) | class BoxAnnotatorOHEMProp(mx.operator.CustomOpProp):
    method __init__ (line 63) | def __init__(self, num_classes, num_reg_classes, roi_per_img):
    method list_arguments (line 69) | def list_arguments(self):
    method list_outputs (line 72) | def list_outputs(self):
    method infer_shape (line 75) | def infer_shape(self, in_shape):
    method create_operator (line 82) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 85) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: dff_rfcn/operator_py/proposal.py
  class ProposalOperator (line 31) | class ProposalOperator(mx.operator.CustomOp):
    method __init__ (line 32) | def __init__(self, feat_stride, scales, ratios, output_score,
    method forward (line 51) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 170) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
    method _filter_boxes (line 176) | def _filter_boxes(boxes, min_size):
    method _clip_pad (line 184) | def _clip_pad(tensor, pad_shape):
  class ProposalProp (line 201) | class ProposalProp(mx.operator.CustomOpProp):
    method __init__ (line 202) | def __init__(self, feat_stride='16', scales='(8, 16, 32)', ratios='(0....
    method list_arguments (line 214) | def list_arguments(self):
    method list_outputs (line 217) | def list_outputs(self):
    method infer_shape (line 223) | def infer_shape(self, in_shape):
    method create_operator (line 238) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 242) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: dff_rfcn/operator_py/proposal_target.py
  class ProposalTargetOperator (line 30) | class ProposalTargetOperator(mx.operator.CustomOp):
    method __init__ (line 31) | def __init__(self, num_classes, batch_images, batch_rois, cfg, fg_frac...
    method forward (line 44) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 82) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class ProposalTargetProp (line 88) | class ProposalTargetProp(mx.operator.CustomOpProp):
    method __init__ (line 89) | def __init__(self, num_classes, batch_images, batch_rois, cfg, fg_frac...
    method list_arguments (line 97) | def list_arguments(self):
    method list_outputs (line 100) | def list_outputs(self):
    method infer_shape (line 103) | def infer_shape(self, in_shape):
    method create_operator (line 117) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 120) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: dff_rfcn/operator_py/rpn_inv_normalize.py
  class RPNInvNormalizeOperator (line 12) | class RPNInvNormalizeOperator(mx.operator.CustomOp):
    method __init__ (line 13) | def __init__(self, num_anchors, bbox_mean, bbox_std):
    method forward (line 19) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 28) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class RPNInvNormalizeProp (line 32) | class RPNInvNormalizeProp(mx.operator.CustomOpProp):
    method __init__ (line 33) | def __init__(self, num_anchors, bbox_mean='(0.0, 0.0, 0.0, 0.0)', bbox...
    method list_arguments (line 39) | def list_arguments(self):
    method list_outputs (line 42) | def list_outputs(self):
    method infer_shape (line 45) | def infer_shape(self, in_shape):
    method create_operator (line 50) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 53) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: dff_rfcn/operator_py/tile_as.py
  class TileAsOperator (line 12) | class TileAsOperator(mx.operator.CustomOp):
    method __init__ (line 13) | def __init__(self):
    method forward (line 16) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 21) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class TileAsProp (line 27) | class TileAsProp(mx.operator.CustomOpProp):
    method __init__ (line 28) | def __init__(self):
    method list_arguments (line 31) | def list_arguments(self):
    method list_outputs (line 34) | def list_outputs(self):
    method infer_shape (line 37) | def infer_shape(self, in_shape):
    method create_operator (line 46) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 49) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: dff_rfcn/symbols/resnet_v1_101_flownet_rfcn.py
  class resnet_v1_101_flownet_rfcn (line 17) | class resnet_v1_101_flownet_rfcn(Symbol):
    method __init__ (line 19) | def __init__(self):
    method get_resnet_v1 (line 29) | def get_resnet_v1(self, data):
    method get_flownet (line 482) | def get_flownet(self, img_cur, img_ref):
    method get_train_symbol (line 541) | def get_train_symbol(self, cfg):
    method get_key_test_symbol (line 661) | def get_key_test_symbol(self, cfg):
    method get_cur_test_symbol (line 737) | def get_cur_test_symbol(self, cfg):
    method get_batch_test_symbol (line 816) | def get_batch_test_symbol(self, cfg):
    method init_weight (line 896) | def init_weight(self, cfg, arg_params, aux_params):

FILE: dff_rfcn/test.py
  function parse_args (line 24) | def parse_args():
  function main (line 49) | def main():

FILE: dff_rfcn/train_end2end.py
  function parse_args (line 25) | def parse_args():
  function train_net (line 58) | def train_net(args, ctx, pretrained, pretrained_flow, epoch, prefix, beg...
  function main (line 172) | def main():

FILE: green2.py
  function modify (line 66) | def modify():
  function commit (line 78) | def commit():
  function set_sys_time (line 84) | def set_sys_time(day, month, year):
  function trick_commit (line 88) | def trick_commit(year, month, day):
  function daily_commit (line 94) | def daily_commit(start_date, end_date):

FILE: lib/bbox/bbox_regression.py
  function compute_bbox_regression_targets (line 23) | def compute_bbox_regression_targets(rois, overlaps, labels, cfg):
  function add_bbox_regression_targets (line 60) | def add_bbox_regression_targets(roidb, cfg):
  function expand_bbox_regression_targets (line 120) | def expand_bbox_regression_targets(bbox_targets_data, num_classes, cfg):

FILE: lib/bbox/bbox_transform.py
  function bbox_overlaps (line 18) | def bbox_overlaps(boxes, query_boxes):
  function bbox_overlaps_py (line 22) | def bbox_overlaps_py(boxes, query_boxes):
  function clip_boxes (line 45) | def clip_boxes(boxes, im_shape):
  function filter_boxes (line 62) | def filter_boxes(boxes, min_size):
  function nonlinear_transform (line 74) | def nonlinear_transform(ex_rois, gt_rois):
  function nonlinear_pred (line 103) | def nonlinear_pred(boxes, box_deltas):
  function iou_transform (line 143) | def iou_transform(ex_rois, gt_rois):
  function iou_pred (line 149) | def iou_pred(boxes, box_deltas):

FILE: lib/bbox/setup_linux.py
  function customize_compiler_for_nvcc (line 29) | def customize_compiler_for_nvcc(self):
  class custom_build_ext (line 67) | class custom_build_ext(build_ext):
    method build_extensions (line 68) | def build_extensions(self):

FILE: lib/dataset/ds_utils.py
  function unique_boxes (line 11) | def unique_boxes(boxes, scale=1.0):
  function filter_small_boxes (line 19) | def filter_small_boxes(boxes, min_size):

FILE: lib/dataset/imagenet_vid.py
  class ImageNetVID (line 26) | class ImageNetVID(IMDB):
    method __init__ (line 27) | def __init__(self, image_set, root_path, dataset_path, result_path=None):
    method load_image_set_index (line 62) | def load_image_set_index(self):
    method image_path_from_index (line 82) | def image_path_from_index(self, index):
    method gt_roidb (line 96) | def gt_roidb(self):
    method load_vid_annotation (line 115) | def load_vid_annotation(self, iindex):
    method evaluate_detections (line 184) | def evaluate_detections(self, detections):
    method evaluate_detections_multiprocess (line 199) | def evaluate_detections_multiprocess(self, detections):
    method get_result_file_template (line 214) | def get_result_file_template(self):
    method write_vid_results (line 223) | def write_vid_results(self, all_boxes):
    method write_vid_results_multiprocess (line 245) | def write_vid_results_multiprocess(self, detections):
    method do_python_eval (line 270) | def do_python_eval(self):
    method do_python_eval_gen (line 291) | def do_python_eval_gen(self):

FILE: lib/dataset/imagenet_vid_eval.py
  function parse_vid_rec (line 17) | def parse_vid_rec(filename, classhash, img_ids, defaultIOUthr=0.5, pixel...
  function vid_ap (line 45) | def vid_ap(rec, prec):
  function vid_eval (line 70) | def vid_eval(detpath, annopath, imageset_file, classname_map, annocache,...

FILE: lib/dataset/imdb.py
  function get_flipped_entry_outclass_wrapper (line 26) | def get_flipped_entry_outclass_wrapper(IMDB_instance, seg_rec):
  class IMDB (line 29) | class IMDB(object):
    method __init__ (line 30) | def __init__(self, name, image_set, root_path, dataset_path, result_pa...
    method image_path_from_index (line 51) | def image_path_from_index(self, index):
    method gt_roidb (line 54) | def gt_roidb(self):
    method evaluate_detections (line 57) | def evaluate_detections(self, detections):
    method evaluate_segmentations (line 60) | def evaluate_segmentations(self, segmentations):
    method cache_path (line 64) | def cache_path(self):
    method result_path (line 75) | def result_path(self):
    method image_path_at (line 81) | def image_path_at(self, index):
    method load_rpn_data (line 89) | def load_rpn_data(self, full=False):
    method load_rpn_roidb (line 100) | def load_rpn_roidb(self, gt_roidb):
    method rpn_roidb (line 109) | def rpn_roidb(self, gt_roidb, append_gt=False):
    method create_roidb_from_box_list (line 124) | def create_roidb_from_box_list(self, box_list, gt_roidb):
    method get_flipped_entry (line 173) | def get_flipped_entry(self, seg_rec):
    method append_flipped_images_for_segmentation (line 180) | def append_flipped_images_for_segmentation(self, segdb):
    method append_flipped_images (line 202) | def append_flipped_images(self, roidb):
    method flip_and_save (line 233) | def flip_and_save(self, image_path):
    method evaluate_recall (line 250) | def evaluate_recall(self, roidb, candidate_boxes=None, thresholds=None):
    method merge_roidbs (line 358) | def merge_roidbs(a, b):

FILE: lib/nms/nms.py
  function py_nms_wrapper (line 19) | def py_nms_wrapper(thresh):
  function cpu_nms_wrapper (line 25) | def cpu_nms_wrapper(thresh):
  function gpu_nms_wrapper (line 31) | def gpu_nms_wrapper(thresh, device_id):
  function nms (line 37) | def nms(dets, thresh):

FILE: lib/nms/setup_linux.py
  function find_in_path (line 22) | def find_in_path(name, path):
  function locate_cuda (line 33) | def locate_cuda():
  function customize_compiler_for_nvcc (line 72) | def customize_compiler_for_nvcc(self):
  class custom_build_ext (line 110) | class custom_build_ext(build_ext):
    method build_extensions (line 111) | def build_extensions(self):

FILE: lib/nms/setup_windows.py
  function find_in_path (line 31) | def find_in_path(name, path):
  function locate_cuda (line 42) | def locate_cuda():
  function customize_compiler_for_nvcc (line 86) | def customize_compiler_for_nvcc(self):
  class custom_build_ext (line 130) | class custom_build_ext(build_ext):
    method build_extensions (line 131) | def build_extensions(self):

FILE: lib/nms/setup_windows_cuda.py
  class CUDA_build_ext (line 48) | class CUDA_build_ext(build_ext):
    method build_extensions (line 53) | def build_extensions(self):
    method spawn (line 62) | def spawn(self, cmd, search_path=1, verbose=0, dry_run=0):

FILE: lib/rpn/generate_anchor.py
  function generate_anchors (line 21) | def generate_anchors(base_size=16, ratios=[0.5, 1, 2],
  function _whctrs (line 35) | def _whctrs(anchor):
  function _mkanchors (line 47) | def _mkanchors(ws, hs, x_ctr, y_ctr):
  function _ratio_enum (line 62) | def _ratio_enum(anchor, ratios):
  function _scale_enum (line 76) | def _scale_enum(anchor, scales):

FILE: lib/rpn/rpn.py
  function get_rpn_testbatch (line 34) | def get_rpn_testbatch(roidb, cfg):
  function get_rpn_batch (line 52) | def get_rpn_batch(roidb, cfg):
  function get_rpn_pair_batch (line 78) | def get_rpn_pair_batch(roidb, cfg):
  function assign_anchor (line 108) | def assign_anchor(feat_shape, gt_boxes, im_info, cfg, feat_stride=16,

FILE: lib/utils/PrefetchingIter.py
  class PrefetchingIter (line 19) | class PrefetchingIter(mx.io.DataIter):
    method __init__ (line 40) | def __init__(self, iters, rename_data=None, rename_label=None):
    method __del__ (line 75) | def __del__(self):
    method provide_data (line 83) | def provide_data(self):
    method provide_label (line 95) | def provide_label(self):
    method reset (line 106) | def reset(self):
    method iter_next (line 116) | def iter_next(self):
    method next (line 129) | def next(self):
    method getdata (line 135) | def getdata(self):
    method getlabel (line 138) | def getlabel(self):
    method getindex (line 141) | def getindex(self):
    method getpad (line 144) | def getpad(self):

FILE: lib/utils/combine_model.py
  function combine_model (line 12) | def combine_model(prefix1, epoch1, prefix2, epoch2, prefix_out, epoch_out):

FILE: lib/utils/create_logger.py
  function create_logger (line 12) | def create_logger(root_output_path, cfg, image_set):

FILE: lib/utils/image.py
  function get_image (line 17) | def get_image(roidb, config):
  function get_pair_image (line 49) | def get_pair_image(roidb, config):
  function resize (line 104) | def resize(im, target_size, max_size, stride=0, interpolation = cv2.INTE...
  function transform (line 134) | def transform(im, pixel_means):
  function transform_seg_gt (line 147) | def transform_seg_gt(gt):
  function transform_inverse (line 158) | def transform_inverse(im_tensor, pixel_means):
  function tensor_vstack (line 177) | def tensor_vstack(tensor_list, pad=0):

FILE: lib/utils/image_processing.py
  function resize (line 12) | def resize(im, target_size, max_size):
  function transform (line 31) | def transform(im, pixel_means, need_mean=False):
  function transform_inverse (line 52) | def transform_inverse(im_tensor, pixel_means):
  function tensor_vstack (line 72) | def tensor_vstack(tensor_list, pad=0):

FILE: lib/utils/load_data.py
  function load_gt_roidb (line 12) | def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path,...
  function load_proposal_roidb (line 22) | def load_proposal_roidb(dataset_name, image_set_name, root_path, dataset...
  function merge_roidb (line 34) | def merge_roidb(roidbs):
  function filter_roidb (line 42) | def filter_roidb(roidb, config):
  function load_gt_segdb (line 61) | def load_gt_segdb(dataset_name, image_set_name, root_path, dataset_path,...
  function merge_segdb (line 71) | def merge_segdb(segdbs):

FILE: lib/utils/load_model.py
  function load_checkpoint (line 11) | def load_checkpoint(prefix, epoch):
  function convert_context (line 34) | def convert_context(params, ctx):
  function load_param (line 46) | def load_param(prefix, epoch, convert=False, ctx=None, process=False):

FILE: lib/utils/lr_scheduler.py
  class WarmupMultiFactorScheduler (line 12) | class WarmupMultiFactorScheduler(LRScheduler):
    method __init__ (line 27) | def __init__(self, step, factor=1, warmup=False, warmup_lr=0, warmup_s...
    method __call__ (line 45) | def __call__(self, num_update):

FILE: lib/utils/roidb.py
  function prepare_roidb (line 20) | def prepare_roidb(imdb, roidb, cfg):

FILE: lib/utils/save_model.py
  function save_checkpoint (line 11) | def save_checkpoint(prefix, epoch, arg_params, aux_params):

FILE: lib/utils/show_boxes.py
  function show_boxes (line 12) | def show_boxes(im, dets, classes, scale = 1.0):
  function draw_boxes (line 36) | def draw_boxes(im, dets, classes, scale = 1.0):

FILE: lib/utils/symbol.py
  class Symbol (line 9) | class Symbol:
    method __init__ (line 10) | def __init__(self):
    method symbol (line 17) | def symbol(self):
    method get_symbol (line 20) | def get_symbol(self, cfg, is_train=True):
    method init_weights (line 26) | def init_weights(self, cfg, arg_params, aux_params):
    method get_msra_std (line 29) | def get_msra_std(self, shape):
    method infer_shape (line 36) | def infer_shape(self, data_shape_dict):
    method check_parameter_shapes (line 43) | def check_parameter_shapes(self, arg_params, aux_params, data_shape_di...

FILE: lib/utils/tictoc.py
  function tic (line 10) | def tic():
  function toc (line 16) | def toc():

FILE: rfcn/_init_paths.py
  function add_path (line 11) | def add_path(path):

FILE: rfcn/config/config.py
  function update_config (line 148) | def update_config(config_file):

FILE: rfcn/core/DataParallelExecutorGroup.py
  function _load_general (line 24) | def _load_general(data, targets, major_axis):
  function _load_data (line 37) | def _load_data(batch, targets, major_axis):
  function _load_label (line 42) | def _load_label(batch, targets, major_axis):
  function _merge_multi_context (line 47) | def _merge_multi_context(outputs, major_axis):
  class DataParallelExecutorGroup (line 64) | class DataParallelExecutorGroup(object):
    method __init__ (line 108) | def __init__(self, symbol, contexts, workload, data_shapes, label_shap...
    method decide_slices (line 193) | def decide_slices(self, data_shapes):
    method _collect_arrays (line 219) | def _collect_arrays(self):
    method bind_exec (line 253) | def bind_exec(self, data_shapes, label_shapes, shared_group=None, resh...
    method reshape (line 283) | def reshape(self, data_shapes, label_shapes):
    method set_params (line 302) | def set_params(self, arg_params, aux_params):
    method get_params (line 315) | def get_params(self, arg_params, aux_params):
    method forward (line 336) | def forward(self, data_batch, is_train=None):
    method get_outputs (line 363) | def get_outputs(self, merge_multi_context=True):
    method get_states (line 386) | def get_states(self, merge_multi_context=True):
    method set_states (line 407) | def set_states(self, states=None, value=None):
    method get_input_grads (line 428) | def get_input_grads(self, merge_multi_context=True):
    method backward (line 450) | def backward(self, out_grads=None):
    method update_metric (line 470) | def update_metric(self, eval_metric, labels):
    method _bind_ith_exec (line 483) | def _bind_ith_exec(self, i, data_shapes, label_shapes, shared_group):
    method _sliced_shape (line 575) | def _sliced_shape(self, shapes, i, major_axis):
    method install_monitor (line 593) | def install_monitor(self, mon):

FILE: rfcn/core/callback.py
  class Speedometer (line 19) | class Speedometer(object):
    method __init__ (line 20) | def __init__(self, batch_size, frequent=50):
    method __call__ (line 27) | def __call__(self, param):
  function do_checkpoint (line 54) | def do_checkpoint(prefix, means, stds):

FILE: rfcn/core/loader.py
  class TestLoader (line 23) | class TestLoader(mx.io.DataIter):
    method __init__ (line 24) | def __init__(self, roidb, config, batch_size=1, shuffle=False,
    method provide_data (line 57) | def provide_data(self):
    method provide_label (line 61) | def provide_label(self):
    method provide_data_single (line 65) | def provide_data_single(self):
    method provide_label_single (line 69) | def provide_label_single(self):
    method reset (line 72) | def reset(self):
    method iter_next (line 77) | def iter_next(self):
    method next (line 80) | def next(self):
    method getindex (line 90) | def getindex(self):
    method getpad (line 93) | def getpad(self):
    method get_batch (line 99) | def get_batch(self):
  class AnchorLoader (line 110) | class AnchorLoader(mx.io.DataIter):
    method __init__ (line 112) | def __init__(self, feat_sym, roidb, cfg, batch_size=1, shuffle=False, ...
    method provide_data (line 173) | def provide_data(self):
    method provide_label (line 177) | def provide_label(self):
    method provide_data_single (line 181) | def provide_data_single(self):
    method provide_label_single (line 185) | def provide_label_single(self):
    method reset (line 188) | def reset(self):
    method iter_next (line 207) | def iter_next(self):
    method next (line 210) | def next(self):
    method getindex (line 220) | def getindex(self):
    method getpad (line 223) | def getpad(self):
    method infer_shape (line 229) | def infer_shape(self, max_data_shape=None, max_label_shape=None):
    method get_batch (line 246) | def get_batch(self):
    method get_batch_individual (line 305) | def get_batch_individual(self):
    method parfetch (line 326) | def parfetch(self, iroidb):

FILE: rfcn/core/metric.py
  function get_rpn_names (line 18) | def get_rpn_names():
  function get_rcnn_names (line 24) | def get_rcnn_names(cfg):
  class RPNAccMetric (line 36) | class RPNAccMetric(mx.metric.EvalMetric):
    method __init__ (line 37) | def __init__(self):
    method update (line 41) | def update(self, labels, preds):
  class RCNNAccMetric (line 60) | class RCNNAccMetric(mx.metric.EvalMetric):
    method __init__ (line 61) | def __init__(self, cfg):
    method update (line 67) | def update(self, labels, preds):
  class RPNLogLossMetric (line 87) | class RPNLogLossMetric(mx.metric.EvalMetric):
    method __init__ (line 88) | def __init__(self):
    method update (line 92) | def update(self, labels, preds):
  class RCNNLogLossMetric (line 114) | class RCNNLogLossMetric(mx.metric.EvalMetric):
    method __init__ (line 115) | def __init__(self, cfg):
    method update (line 121) | def update(self, labels, preds):
  class RPNL1LossMetric (line 144) | class RPNL1LossMetric(mx.metric.EvalMetric):
    method __init__ (line 145) | def __init__(self):
    method update (line 149) | def update(self, labels, preds):
  class RCNNL1LossMetric (line 160) | class RCNNL1LossMetric(mx.metric.EvalMetric):
    method __init__ (line 161) | def __init__(self, cfg):
    method update (line 167) | def update(self, labels, preds):

FILE: rfcn/core/module.py
  class Module (line 34) | class Module(BaseModule):
    method __init__ (line 58) | def __init__(self, symbol, data_names=('data',), label_names=('softmax...
    method load (line 109) | def load(prefix, epoch, load_optimizer_states=False, **kwargs):
    method save_checkpoint (line 147) | def save_checkpoint(self, prefix, epoch, save_optimizer_states=False):
    method _reset_bind (line 169) | def _reset_bind(self):
    method data_names (line 177) | def data_names(self):
    method label_names (line 182) | def label_names(self):
    method output_names (line 187) | def output_names(self):
    method data_shapes (line 192) | def data_shapes(self):
    method label_shapes (line 202) | def label_shapes(self):
    method output_shapes (line 214) | def output_shapes(self):
    method get_params (line 223) | def get_params(self):
    method init_params (line 236) | def init_params(self, initializer=Uniform(0.01), arg_params=None, aux_...
    method set_params (line 294) | def set_params(self, arg_params, aux_params, allow_missing=False, forc...
    method bind (line 332) | def bind(self, data_shapes, label_shapes=None, for_training=True,
    method reshape (line 429) | def reshape(self, data_shapes, label_shapes=None):
    method init_optimizer (line 448) | def init_optimizer(self, kvstore='local', optimizer='sgd',
    method borrow_optimizer (line 526) | def borrow_optimizer(self, shared_module):
    method forward (line 541) | def forward(self, data_batch, is_train=None):
    method backward (line 554) | def backward(self, out_grads=None):
    method update (line 567) | def update(self):
    method get_outputs (line 585) | def get_outputs(self, merge_multi_context=True):
    method get_input_grads (line 605) | def get_input_grads(self, merge_multi_context=True):
    method get_states (line 625) | def get_states(self, merge_multi_context=True):
    method set_states (line 645) | def set_states(self, states=None, value=None):
    method update_metric (line 659) | def update_metric(self, eval_metric, labels):
    method _sync_params_from_devices (line 670) | def _sync_params_from_devices(self):
    method save_optimizer_states (line 678) | def save_optimizer_states(self, fname):
    method load_optimizer_states (line 694) | def load_optimizer_states(self, fname):
    method install_monitor (line 709) | def install_monitor(self, mon):
  class MutableModule (line 715) | class MutableModule(BaseModule):
    method __init__ (line 730) | def __init__(self, symbol, data_names, label_names,
    method _reset_bind (line 754) | def _reset_bind(self):
    method data_names (line 759) | def data_names(self):
    method output_names (line 763) | def output_names(self):
    method data_shapes (line 767) | def data_shapes(self):
    method label_shapes (line 772) | def label_shapes(self):
    method output_shapes (line 777) | def output_shapes(self):
    method get_params (line 781) | def get_params(self):
    method init_params (line 785) | def init_params(self, initializer=Uniform(0.01), arg_params=None, aux_...
    method bind (line 795) | def bind(self, data_shapes, label_shapes=None, for_training=True,
    method save_checkpoint (line 851) | def save_checkpoint(self, prefix, epoch, save_optimizer_states=False):
    method init_optimizer (line 866) | def init_optimizer(self, kvstore='local', optimizer='sgd',
    method fit (line 878) | def fit(self, train_data, eval_data=None, eval_metric='acc',
    method forward (line 1015) | def forward(self, data_batch, is_train=None):
    method backward (line 1050) | def backward(self, out_grads=None):
    method update (line 1054) | def update(self):
    method get_outputs (line 1058) | def get_outputs(self, merge_multi_context=True):
    method get_input_grads (line 1061) | def get_input_grads(self, merge_multi_context=True):
    method update_metric (line 1065) | def update_metric(self, eval_metric, labels):
    method install_monitor (line 1069) | def install_monitor(self, mon):

FILE: rfcn/core/rcnn.py
  function get_rcnn_testbatch (line 36) | def get_rcnn_testbatch(roidb, cfg):
  function get_rcnn_batch (line 58) | def get_rcnn_batch(roidb, cfg):
  function sample_rois (line 126) | def sample_rois(rois, fg_rois_per_image, rois_per_image, num_classes, cfg,

FILE: rfcn/core/tester.py
  class Predictor (line 27) | class Predictor(object):
    method __init__ (line 28) | def __init__(self, symbol, data_names, label_names,
    method predict (line 37) | def predict(self, data_batch):
  function im_proposal (line 43) | def im_proposal(predictor, data_batch, data_names, scales):
  function generate_proposals (line 63) | def generate_proposals(predictor, test_data, imdb, cfg, vis=False, thres...
  function im_detect (line 129) | def im_detect(predictor, data_batch, data_names, scales, cfg):
  function im_batch_detect (line 157) | def im_batch_detect(predictor, data_batch, data_names, scales, cfg):
  function pred_eval (line 185) | def pred_eval(predictor, test_data, imdb, cfg, vis=False, thresh=1e-3, l...
  function vis_all_detection (line 276) | def vis_all_detection(im_array, detections, class_names, scale, cfg, thr...
  function draw_all_detection (line 310) | def draw_all_detection(im_array, detections, class_names, scale, cfg, th...

FILE: rfcn/demo.py
  function parse_args (line 36) | def parse_args():
  function main (line 43) | def main():

FILE: rfcn/demo_batch.py
  function parse_args (line 36) | def parse_args():
  function main (line 43) | def main():

FILE: rfcn/function/test_rcnn.py
  function test_rcnn (line 28) | def test_rcnn(cfg, dataset, image_set, root_path, dataset_path,

FILE: rfcn/function/test_rpn.py
  function test_rpn (line 26) | def test_rpn(cfg, dataset, image_set, root_path, dataset_path,

FILE: rfcn/function/train_rcnn.py
  function train_rcnn (line 31) | def train_rcnn(cfg, dataset, image_set, root_path, dataset_path,

FILE: rfcn/function/train_rpn.py
  function train_rpn (line 29) | def train_rpn(cfg, dataset, image_set, root_path, dataset_path,

FILE: rfcn/operator_cxx/multi_proposal-inl.h
  function namespace (line 26) | namespace mxnet {
  function namespace (line 115) | namespace mxnet {
  function namespace (line 252) | namespace mxnet {

FILE: rfcn/operator_cxx/multi_proposal.cc
  type mxnet (line 12) | namespace mxnet {
    type op (line 13) | namespace op {
      class MultiProposalOp (line 16) | class MultiProposalOp : public Operator{
        method MultiProposalOp (line 18) | explicit MultiProposalOp(MultiProposalParam param) {
        method Forward (line 22) | virtual void Forward(const OpContext &ctx,
        method Backward (line 30) | virtual void Backward(const OpContext &ctx,
      function Operator (line 45) | Operator *CreateOp<cpu>(MultiProposalParam param) {
      function Operator (line 49) | Operator* MultiProposalProp::CreateOperator(Context ctx) const {

FILE: rfcn/operator_cxx/psroi_pooling-inl.h
  function namespace (line 23) | namespace mxnet {

FILE: rfcn/operator_cxx/psroi_pooling.cc
  type mshadow (line 21) | namespace mshadow {
    function PSROIPoolForward (line 23) | inline void PSROIPoolForward(const Tensor<cpu, 4, DType> &out,
    function PSROIPoolBackwardAcc (line 35) | inline void PSROIPoolBackwardAcc(const Tensor<cpu, 4, DType> &in_grad,
  type mxnet (line 46) | namespace mxnet {
    type op (line 47) | namespace op {
      function Operator (line 50) | Operator *CreateOp<cpu>(PSROIPoolingParam param, int dtype) {
      function Operator (line 58) | Operator *PSROIPoolingProp::CreateOperatorEx(Context ctx, std::vecto...

FILE: rfcn/operator_py/box_annotator_ohem.py
  class BoxAnnotatorOHEMOperator (line 19) | class BoxAnnotatorOHEMOperator(mx.operator.CustomOp):
    method __init__ (line 20) | def __init__(self, num_classes, num_reg_classes, roi_per_img):
    method forward (line 26) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 56) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class BoxAnnotatorOHEMProp (line 62) | class BoxAnnotatorOHEMProp(mx.operator.CustomOpProp):
    method __init__ (line 63) | def __init__(self, num_classes, num_reg_classes, roi_per_img):
    method list_arguments (line 69) | def list_arguments(self):
    method list_outputs (line 72) | def list_outputs(self):
    method infer_shape (line 75) | def infer_shape(self, in_shape):
    method create_operator (line 82) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 85) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: rfcn/operator_py/proposal.py
  class ProposalOperator (line 31) | class ProposalOperator(mx.operator.CustomOp):
    method __init__ (line 32) | def __init__(self, feat_stride, scales, ratios, output_score,
    method forward (line 51) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 170) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
    method _filter_boxes (line 176) | def _filter_boxes(boxes, min_size):
    method _clip_pad (line 184) | def _clip_pad(tensor, pad_shape):
  class ProposalProp (line 201) | class ProposalProp(mx.operator.CustomOpProp):
    method __init__ (line 202) | def __init__(self, feat_stride='16', scales='(8, 16, 32)', ratios='(0....
    method list_arguments (line 214) | def list_arguments(self):
    method list_outputs (line 217) | def list_outputs(self):
    method infer_shape (line 223) | def infer_shape(self, in_shape):
    method create_operator (line 238) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 242) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: rfcn/operator_py/proposal_target.py
  class ProposalTargetOperator (line 30) | class ProposalTargetOperator(mx.operator.CustomOp):
    method __init__ (line 31) | def __init__(self, num_classes, batch_images, batch_rois, cfg, fg_frac...
    method forward (line 44) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 82) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class ProposalTargetProp (line 88) | class ProposalTargetProp(mx.operator.CustomOpProp):
    method __init__ (line 89) | def __init__(self, num_classes, batch_images, batch_rois, cfg, fg_frac...
    method list_arguments (line 97) | def list_arguments(self):
    method list_outputs (line 100) | def list_outputs(self):
    method infer_shape (line 103) | def infer_shape(self, in_shape):
    method create_operator (line 117) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 120) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: rfcn/operator_py/rpn_inv_normalize.py
  class RPNInvNormalizeOperator (line 12) | class RPNInvNormalizeOperator(mx.operator.CustomOp):
    method __init__ (line 13) | def __init__(self, num_anchors, bbox_mean, bbox_std):
    method forward (line 19) | def forward(self, is_train, req, in_data, out_data, aux):
    method backward (line 28) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
  class RPNInvNormalizeProp (line 32) | class RPNInvNormalizeProp(mx.operator.CustomOpProp):
    method __init__ (line 33) | def __init__(self, num_anchors, bbox_mean='(0.0, 0.0, 0.0, 0.0)', bbox...
    method list_arguments (line 39) | def list_arguments(self):
    method list_outputs (line 42) | def list_outputs(self):
    method infer_shape (line 45) | def infer_shape(self, in_shape):
    method create_operator (line 50) | def create_operator(self, ctx, shapes, dtypes):
    method declare_backward_dependency (line 53) | def declare_backward_dependency(self, out_grad, in_data, out_data):

FILE: rfcn/symbols/resnet_v1_101_rfcn.py
  class resnet_v1_101_rfcn (line 16) | class resnet_v1_101_rfcn(Symbol):
    method __init__ (line 18) | def __init__(self):
    method get_resnet_v1 (line 28) | def get_resnet_v1(self, data):
    method get_train_symbol (line 481) | def get_train_symbol(self, cfg):
    method get_test_symbol (line 593) | def get_test_symbol(self, cfg):
    method init_weight (line 662) | def init_weight(self, cfg, arg_params, aux_params):

FILE: rfcn/test.py
  function parse_args (line 24) | def parse_args():
  function main (line 49) | def main():

FILE: rfcn/train_end2end.py
  function parse_args (line 25) | def parse_args():
  function train_net (line 58) | def train_net(args, ctx, pretrained, epoch, prefix, begin_epoch, end_epo...
  function main (line 167) | def main():