Proto commits in lzx1413/CAFFE_SSD

These commits are when the Protocol Buffers files have changed: (only the last 100 relevant commits are shown)

2017-09-25

add interp support

The documentation is generated from this commit.

2017-09-07

update kitti

2017-08-05

add bolt1

2016-12-05

add options to display per class AP

2016-11-24

Merge branch 'master' into ssd

Merge branch 'master' into ssd

2016-11-17

sigmoid cross-entropy loss: normalize loss by different schemes sig-ce loss handles all the same normalizations as the softmax loss; refer to #3296 for more detail. this preserves the default normalization for sig-ce loss: batch size.

2016-10-12

add option to set prior center offset

2016-09-13

add option to save display results to video file

2016-09-12

add option to expand the image

2016-09-09

add plateau learning rate

2016-09-08

Merge branch 'master' into ssd

Merge branch 'master' into ssd

2016-09-01

Add "plateau" LR policy for SGD solver

2016-07-13

add demo for processing video file

2016-07-09

add skip_frame and video file option in VideoDataLayer

2016-07-06

add anno_type in AnnotatedDataParameter

2016-07-05

merge master and fix conflict

2016-07-04

add color distortion options

2016-06-28

add default value for rms_decay

add fix scale for FIT_SMALL_SIZE resize option

2016-06-27

add resize parameter in detection output/evaluate layer

2016-06-25

add options to provide img_size and step in PriorBoxLayer

2016-06-24

change default value

2016-06-22

merge master and speed up nms

2016-06-15

refactor MineHardExample function and add use_prior_for_nms option

2016-06-14

add OHEM method

2016-06-06

add CORNER_SIZE code_type

2016-06-05

add ignore_cross_boundary_bbox option

2016-06-03

add multiple scales for PriorBoxLayer

2016-06-01

Add RecurrentLayer: an abstract superclass for other recurrent layer types

2016-05-05

add parameter layer for learning any bottom

2016-04-27

Fix an error in the example of ReshapeParameter. * this small mistake may confuse newer.

2016-04-09

rebase master

2016-04-05

Net: setting `propagate_down: true` forces backprop

2016-03-29

add webcam demo

2016-03-20

speed up nms and generate output for COCO

2016-03-06

add map_object_to_agnostic to enable learning object proposal

2016-03-05

Crop: fixes, tests and negative axis indexing.

Extend Crop to N-D, changed CropParameter.

add CropLayer: crop blob to another blob's dimensions with offsets configure offset(s) through proto definition.

2016-03-04

enable different choice of encoding the prior variance

make variance repeated in PriorBoxLayer

2016-02-29

merge master

2016-02-25

deprecate input fields and upgrade automagically

add InputLayer for Net input Create an input layer to replace oddball Net `input` fields.

add more normalization to MultiBoxLoss

2016-02-24

add logistic conf loss type

2016-02-21

add keep_top_k in DetectionOutputLayer

2016-02-20

tranpose parameter added to IP layer to support tied weights in an autoencoder. Arguments to matrix multiplication function are conditioned on this parameter, no actual transposing takes place. test ip gradient computation with transpose on

2016-02-19

add sampler and related functions

2016-02-16

add support when evaluating on partial test data

2016-02-15

add code_type

2016-02-14

add variance and make max_size optional

add neg_overlap for selecting hard negatives

2016-02-11

do negative mining based on scores instead of overlap

2016-02-09

change type of size from int to float

add do_neg_mining in MultiBoxLossLayer

2016-02-08

add name_size_file in DetectionEvaluationLayer

2016-02-07

add SmoothL1LossLayer from Ross Girshick's Fast R-CNN

2016-02-06

add MaxIntegral ap_version to match VOC2012/ILSVRC AP

add difficult property for bbox annotation

2016-02-05

set lr_mult to 0 instead of using fix_scale in NormalizeLayer to not learn scale parameter

add num_classes in DetectionEvaluateLayer

2016-02-04

add SaveOutputParameter in DetectionOutputLayer

2016-02-03

add NormalizeLayer from fcn branch

2016-02-02

add change in proto for normalize option

add TestDetection

2016-02-01

add DetectionEvaluateLayer with test

add DetectionOutputLayer with test

2016-01-31

add ApplyNMS and GetConfidenceScores to bbox_util

2016-01-27

fix merge upstream conflict

2016-01-25

fix several bugs in MultiBoxLossLayer

2016-01-24

add PermuteLayer

2016-01-23

fix merge upstream conflict

Separation and generalization of ChannelwiseAffineLayer into BiasLayer and ScaleLayer. The behavior of ChannelwiseAffineLayer can be reproduced by a ScaleLayer with `scale_param { bias_term: true }`. BiasLayer and ScaleLayer each take 1 or 2 bottoms, with the output having the same shape as the first. The second input -- either another bottom or a learned parameter -- will have its axes (virtually) broadcast and tiled to have the same shape as the first, after which elementwise addition (Bias) or multiplication (Scale) is performed.

2016-01-22

Add ChannelwiseAffine for batch norm

put label_map_file in AnnotatedDataParameter

Merge pull request #3388 from mohomran/exponential_linear_units Exponential Linear Units

add MultiBoxLossLayer and bbox_util

2016-01-19

add PriorBoxLayer which generates priors from a layer

2016-01-15

add LabelMap and tools for create DB to store AnnotatedDatum

2016-01-14

Add AnnotatedDataLayer

2015-12-28

add short description of dilation to caffe.proto

add support for 2D dilated convolution

2015-12-04

ELU layer with basic tests

2015-11-22

Better normalization options for SoftmaxWithLoss layer.

2015-10-23

Merge pull request #3229 from cdoersch/batchnorm2 Yet another batch normalization PR

2015-10-22

Cleanup batch norm layer, include global stats computation

2015-10-17

Change solver type to string and provide solver registry

2015-10-16

Merge pull request #3160 from shelhamer/cudnnV3 Basic cuDNN v3 support

Initial cuDNN v3 support

2015-09-25

Add argmax_param axis

2015-09-19

Im2col and Convolution layers support N spatial axes

caffe.proto: generalize ConvolutionParameter to N spatial axes

2015-08-26

Add TileLayer

2015-08-25

Merge pull request #2032 from jeffdonahue/embed-layer Embed layer for lookup table of one hot encodings

2015-08-14

Adam solver This commit implements the Adam solver by Kingma et. al for CPU and GPU. All solver parameters are defined in the caffe.proto. This also adds an example for the MNIST dataset.

2015-08-13

Merge pull request #2903 from ronghanghu/multi_gpu Multi-GPU Data Parallelism

2015-08-12

Data Layers Parallel for Multi-GPU Allow data layers (and also PythonLayer when used as data layer) to be shared among worker solver's training net, and also test net for future-proof if one wants to do Multi-GPU testing. Data layers are locked during forward to ensure sequential forward.