Commit Graph

88 Commits

Author SHA1 Message Date
Alexander Alekhin
019b7c5a66 Merge pull request #10402 from dkurt:dnn_tf_quantized 2017-12-22 15:58:56 +00:00
Dmitry Kurtaev
bcc669f3f7 TensorFlow weights dequantization 2017-12-22 17:25:10 +03:00
Dmitry Kurtaev
7e48fa58eb Manage TensorFlow's NHWC data layout is smoother 2017-12-20 14:13:40 +03:00
Alexander Alekhin
dcdd6af5a8 Merge pull request #10341 from pengli:dnn 2017-12-19 14:04:55 +00:00
Li Peng
3b84acfc48 add ocl accuracy test for tf mobilenet ssd
Signed-off-by: Li Peng <peng.li@intel.com>
2017-12-19 18:38:55 +08:00
Dmitry Kurtaev
6aabd6cc7a Remove cv::dnn::Importer 2017-12-18 18:08:28 +03:00
Dmitry Kurtaev
08112f3821 Faster-RCNN models support 2017-12-15 12:16:21 +03:00
Alexander Alekhin
f2070c9f5d Merge pull request #10255 from dkurt:dnn_roi_pooling 2017-12-08 11:20:07 +00:00
Dmitry Kurtaev
17dcf0e82d ROIPooling layer 2017-12-07 19:04:38 +03:00
Dmitry Kurtaev
bbbec300a6 nn.BatchNormalization and nn.Dropout layers from Torch 2017-12-04 12:57:21 +03:00
Li Peng
a47fbd2610 Add ocl accuracy test for a few dnn nets
They are alexnet, mobilenet-ssd, resnet50, squeezeNet_v1_1,
yolo and fast_neural_style.

Signed-off-by: Li Peng <peng.li@intel.com>
2017-11-27 23:33:21 +08:00
Alexander Alekhin
107582c767 Merge pull request #9996 from dkurt:dnn_multiple_inputs 2017-11-23 18:22:37 +00:00
Alexander Alekhin
f37f4cf3b4 Merge pull request #9994 from r2d3:dnn_memory_load 2017-11-22 18:15:00 +00:00
David Geldreich
f723cede2e add loading TensorFlow/Caffe net from memory buffer
add a corresponding test
2017-11-20 16:28:22 +01:00
Wu Zhiwen
394101d6ed dnn(ocl4dnn): Fix relu fusion bug
Incorrect type of negative_slope result in this bug.

Also and OCL test for darknet to validate this patch.

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
2017-11-17 16:21:56 +08:00
Dmitry Kurtaev
20a2dc6ac5 Fix multiple inputs models from Caffe.
Fixed Concat optimization.
2017-11-02 18:55:08 +03:00
Dmitry Kurtaev
03cefa7bfe Set zero confidences in case of no detections 2017-10-30 10:17:57 +03:00
Vadim Pisarevsky
ff037ebe5f Merge pull request #9845 from dkurt:fast_neural_style_models 2017-10-27 13:59:02 +00:00
Vadim Pisarevsky
5384d2f090 Merge pull request #9880 from dkurt:caffe_ceil_mode 2017-10-27 11:51:46 +00:00
Dmitry Kurtaev
4b52b8df34 Layers for fast-neural-style models: https://github.com/jcjohnson/fast-neural-style 2017-10-27 14:26:45 +03:00
Vadim Pisarevsky
bc93775385 Merge pull request #9862 from sovrasov:dnn_nms 2017-10-27 11:19:57 +00:00
Vadim Pisarevsky
69f2590359 Merge pull request #9921 from dkurt:fix_prelu_after_fully_connected 2017-10-27 11:10:59 +00:00
Vladislav Sovrasov
5bf39ceb5d dnn: handle 4-channel images in blobFromImage (#9944) 2017-10-27 14:06:53 +03:00
Vladislav Sovrasov
7e3e9144de dnn: add an accuracy test for NMS 2017-10-25 13:40:56 +03:00
Dmitry Kurtaev
a36ebaecdc PReLU layer for multidimensional input 2017-10-23 16:13:03 +03:00
Dmitry Kurtaev
410d44d67d Binary data for batch normalization test from Torch 2017-10-20 12:01:42 +03:00
Dmitry Kurtaev
b903ff8992 Ceil mode from experimental version of Caffe, https://github.com/BVLC/caffe/pull/3057 2017-10-18 14:04:53 +03:00
Vadim Pisarevsky
b7ff9ddcdd Merge pull request #9705 from AlexeyAB:dnn_darknet_yolo_v2 2017-10-10 12:02:03 +00:00
Vadim Pisarevsky
046045239c Merge pull request #9750 from dkurt:feature_dnn_tf_text_graph 2017-10-10 10:06:24 +00:00
AlexeyAB
ecc34dc521 Added DNN Darknet Yolo v2 for object detection 2017-10-09 21:08:44 +03:00
Dmitry Kurtaev
eabf728682 PReLU layer from Caffe 2017-10-09 20:30:37 +03:00
Dmitry Kurtaev
e4aa39f9e5 Text TensorFlow graphs parsing. MobileNet-SSD for 90 classes. 2017-10-08 22:25:29 +03:00
Vadim Pisarevsky
21bd834a59 Merge pull request #9772 from dkurt:fix_caffe_eltwise_and_fc_layers 2017-10-06 13:47:54 +00:00
Vadim Pisarevsky
b969d86415 Merge pull request #9787 from dkurt:feature_dnn_resize_nearest_neighbor 2017-10-06 13:46:50 +00:00
Vadim Pisarevsky
fe58b58937 Merge pull request #9778 from dkurt:dnn_colorization 2017-10-06 11:48:05 +00:00
Dmitry Kurtaev
b9f94c9315 Nearest neighbor resize layer 2017-10-06 14:33:26 +03:00
Dmitry Kurtaev
e268606e26 Grayscale colorization model (https://github.com/richzhang/colorization) test. 2017-10-06 09:33:41 +03:00
Dmitry Kurtaev
ad8bbaf008 Multidimensional eltwise layer.
Fixed fully-connected layer axis.
2017-10-04 14:01:44 +03:00
Dmitry Kurtaev
2a21c10837 Fix TensorFlow split layer 2017-10-02 22:44:42 +03:00
pengli
e340ff9c3a Merge pull request #9114 from pengli:dnn_rebase
add libdnn acceleration to dnn module  (#9114)

* import libdnn code

Signed-off-by: Li Peng <peng.li@intel.com>

* add convolution layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add pooling layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add softmax layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add lrn layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add innerproduct layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add HAVE_OPENCL macro

Signed-off-by: Li Peng <peng.li@intel.com>

* fix for convolution ocl

Signed-off-by: Li Peng <peng.li@intel.com>

* enable getUMat() for multi-dimension Mat

Signed-off-by: Li Peng <peng.li@intel.com>

* use getUMat for ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* use CV_OCL_RUN macro

Signed-off-by: Li Peng <peng.li@intel.com>

* set OPENCL target when it is available

and disable fuseLayer for OCL target for the time being

Signed-off-by: Li Peng <peng.li@intel.com>

* fix innerproduct accuracy test

Signed-off-by: Li Peng <peng.li@intel.com>

* remove trailing space

Signed-off-by: Li Peng <peng.li@intel.com>

* Fixed tensorflow demo bug.

Root cause is that tensorflow has different algorithm with libdnn
to calculate convolution output dimension.

libdnn don't calculate output dimension anymore and just use one
passed in by config.

* split gemm ocl file

split it into gemm_buffer.cl and gemm_image.cl

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix compile failure

Signed-off-by: Li Peng <peng.li@intel.com>

* check env flag for auto tuning

Signed-off-by: Li Peng <peng.li@intel.com>

* switch to new ocl kernels for softmax layer

Signed-off-by: Li Peng <peng.li@intel.com>

* update softmax layer

on some platform subgroup extension may not work well,
fallback to non subgroup ocl acceleration.

Signed-off-by: Li Peng <peng.li@intel.com>

* fallback to cpu path for fc layer with multi output

Signed-off-by: Li Peng <peng.li@intel.com>

* update output message

Signed-off-by: Li Peng <peng.li@intel.com>

* update fully connected layer

fallback to gemm API if libdnn return false

Signed-off-by: Li Peng <peng.li@intel.com>

* Add ReLU OCL implementation

* disable layer fusion for now

Signed-off-by: Li Peng <peng.li@intel.com>

* Add OCL implementation for concat layer

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>

* libdnn: update license and copyrights

Also refine libdnn coding style

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
Signed-off-by: Li Peng <peng.li@intel.com>

* DNN: Don't link OpenCL library explicitly

* DNN: Make default preferableTarget to DNN_TARGET_CPU

User should set it to DNN_TARGET_OPENCL explicitly if want to
use OpenCL acceleration.

Also don't fusion when using DNN_TARGET_OPENCL

* DNN: refine coding style

* Add getOpenCLErrorString

* DNN: Use int32_t/uint32_t instread of alias

* Use namespace ocl4dnn to include libdnn things

* remove extra copyTo in softmax ocl path

Signed-off-by: Li Peng <peng.li@intel.com>

* update ReLU layer ocl path

Signed-off-by: Li Peng <peng.li@intel.com>

* Add prefer target property for layer class

It is used to indicate the target for layer forwarding,
either the default CPU target or OCL target.

Signed-off-by: Li Peng <peng.li@intel.com>

* Add cl_event based timer for cv::ocl

* Rename libdnn to ocl4dnn

Signed-off-by: Li Peng <peng.li@intel.com>
Signed-off-by: wzw <zhiwen.wu@intel.com>

* use UMat for ocl4dnn internal buffer

Remove allocateMemory which use clCreateBuffer directly

Signed-off-by: Li Peng <peng.li@intel.com>
Signed-off-by: wzw <zhiwen.wu@intel.com>

* enable buffer gemm in ocl4dnn innerproduct

Signed-off-by: Li Peng <peng.li@intel.com>

* replace int_tp globally for ocl4dnn kernels.

Signed-off-by: wzw <zhiwen.wu@intel.com>
Signed-off-by: Li Peng <peng.li@intel.com>

* create UMat for layer params

Signed-off-by: Li Peng <peng.li@intel.com>

* update sign ocl kernel

Signed-off-by: Li Peng <peng.li@intel.com>

* update image based gemm of inner product layer

Signed-off-by: Li Peng <peng.li@intel.com>

* remove buffer gemm of inner product layer

call cv::gemm API instead

Signed-off-by: Li Peng <peng.li@intel.com>

* change ocl4dnn forward parameter to UMat

Signed-off-by: Li Peng <peng.li@intel.com>

* Refine auto-tuning mechanism.

- Use OPENCV_OCL4DNN_KERNEL_CONFIG_PATH to set cache directory
  for fine-tuned kernel configuration.
  e.g. export OPENCV_OCL4DNN_KERNEL_CONFIG_PATH=/home/tmp,
  the cache directory will be /home/tmp/spatialkernels/ on Linux.

- Define environment OPENCV_OCL4DNN_ENABLE_AUTO_TUNING to enable
  auto-tuning.

- OPENCV_OPENCL_ENABLE_PROFILING is only used to enable profiling
  for OpenCL command queue. This fix basic kernel get wrong running
  time, i.e. 0ms.

- If creating cache directory failed, disable auto-tuning.

* Detect and create cache dir on windows

Signed-off-by: Li Peng <peng.li@intel.com>

* Refine gemm like convolution kernel.

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix redundant swizzleWeights calling when use cached kernel config.

* Fix "out of resource" bug when auto-tuning too many kernels.

* replace cl_mem with UMat in ocl4dnnConvSpatial class

* OCL4DNN: reduce the tuning kernel candidate.

This patch could reduce 75% of the tuning candidates with less
than 2% performance impact for the final result.

Signed-off-by: Zhigang Gong <zhigang.gong@intel.com>

* replace cl_mem with umat in ocl4dnn convolution

Signed-off-by: Li Peng <peng.li@intel.com>

* remove weight_image_ of ocl4dnn inner product

Actually it is unused in the computation

Signed-off-by: Li Peng <peng.li@intel.com>

* Various fixes for ocl4dnn

1. OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel())
2. Ptr<OCL4DNNInnerProduct<float> > innerProductOp
3. Code comments cleanup
4. ignore check on OCL cpu device

Signed-off-by: Li Peng <peng.li@intel.com>

* add build option for log softmax

Signed-off-by: Li Peng <peng.li@intel.com>

* remove unused ocl kernels in ocl4dnn

Signed-off-by: Li Peng <peng.li@intel.com>

* replace ocl4dnnSet with opencv setTo

Signed-off-by: Li Peng <peng.li@intel.com>

* replace ALIGN with cv::alignSize

Signed-off-by: Li Peng <peng.li@intel.com>

* check kernel build options

Signed-off-by: Li Peng <peng.li@intel.com>

* Handle program compilation fail properly.

* Use std::numeric_limits<float>::infinity() for large float number

* check ocl4dnn kernel compilation result

Signed-off-by: Li Peng <peng.li@intel.com>

* remove unused ctx_id

Signed-off-by: Li Peng <peng.li@intel.com>

* change clEnqueueNDRangeKernel to kernel.run()

Signed-off-by: Li Peng <peng.li@intel.com>

* change cl_mem to UMat in image based gemm

Signed-off-by: Li Peng <peng.li@intel.com>

* check intel subgroup support for lrn and pooling layer

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix convolution bug if group is greater than 1

Signed-off-by: Li Peng <peng.li@intel.com>

* Set default layer preferableTarget to be DNN_TARGET_CPU

Signed-off-by: Li Peng <peng.li@intel.com>

* Add ocl perf test for convolution

Signed-off-by: Li Peng <peng.li@intel.com>

* Add more ocl accuracy test

Signed-off-by: Li Peng <peng.li@intel.com>

* replace cl_image with ocl::Image2D

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix build failure in elementwise layer

Signed-off-by: Li Peng <peng.li@intel.com>

* use getUMat() to get blob data

Signed-off-by: Li Peng <peng.li@intel.com>

* replace cl_mem handle with ocl::KernelArg

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(build): don't use C++11, OPENCL_LIBRARIES fix

* dnn(ocl4dnn): remove unused OpenCL kernels

* dnn(ocl4dnn): extract OpenCL code into .cl files

* dnn(ocl4dnn): refine auto-tuning

Defaultly disable auto-tuning, set OPENCV_OCL4DNN_ENABLE_AUTO_TUNING
environment variable to enable it.

Use a set of pre-tuned configs as default config if auto-tuning is disabled.
These configs are tuned for Intel GPU with 48/72 EUs, and for googlenet,
AlexNet, ResNet-50

If default config is not suitable, use the first available kernel config
from the candidates. Candidate priority from high to low is gemm like kernel,
IDLF kernel, basick kernel.

* dnn(ocl4dnn): pooling doesn't use OpenCL subgroups

* dnn(ocl4dnn): fix perf test

OpenCV has default 3sec time limit for each performance test.
Warmup OpenCL backend outside of perf measurement loop.

* use ocl::KernelArg as much as possible

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): fix bias bug for gemm like kernel

* dnn(ocl4dnn): wrap cl_mem into UMat

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): Refine signature of kernel config

- Use more readable string as signture of kernel config
- Don't count device name and vendor in signature string
- Default kernel configurations are tuned for Intel GPU with
  24/48/72 EUs, and for googlenet, AlexNet, ResNet-50 net model.

* dnn(ocl4dnn): swap width/height in configuration

* dnn(ocl4dnn): enable configs for Intel OpenCL runtime only

* core: make configuration helper functions accessible from non-core modules

* dnn(ocl4dnn): update kernel auto-tuning behavior

Avoid unwanted creation of directories

* dnn(ocl4dnn): simplify kernel to workaround OpenCL compiler crash

* dnn(ocl4dnn): remove redundant code

* dnn(ocl4dnn): Add more clear message for simd size dismatch.

* dnn(ocl4dnn): add const to const argument

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): force compiler use a specific SIMD size for IDLF kernel

* dnn(ocl4dnn): drop unused tuneLocalSize()

* dnn(ocl4dnn): specify OpenCL queue for Timer and convolve() method

* dnn(ocl4dnn): sanitize file names used for cache

* dnn(perf): enable Network tests with OpenCL

* dnn(ocl4dnn/conv): drop computeGlobalSize()

* dnn(ocl4dnn/conv): drop unused fields

* dnn(ocl4dnn/conv): simplify ctor

* dnn(ocl4dnn/conv): refactor kernelConfig localSize=NULL

* dnn(ocl4dnn/conv): drop unsupported double / untested half types

* dnn(ocl4dnn/conv): drop unused variable

* dnn(ocl4dnn/conv): alignSize/divUp

* dnn(ocl4dnn/conv): use enum values

* dnn(ocl4dnn): drop unused innerproduct variable

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): add an generic function to check cl option support

* dnn(ocl4dnn): run softmax subgroup version kernel first

Signed-off-by: Li Peng <peng.li@intel.com>
2017-10-02 15:38:00 +03:00
Vadim Pisarevsky
5e93c82023 Merge pull request #9491 from dkurt:tf_lstm 2017-09-28 21:04:06 +00:00
Vadim Pisarevsky
68cc2e292d Merge pull request #9734 from dkurt:fix_deconv_layer_kernel_layout 2017-09-28 11:42:57 +00:00
Vadim Pisarevsky
45365e4df1 Merge pull request #9691 from dkurt:padding_layer_refactoring 2017-09-28 11:34:28 +00:00
Dmitry Kurtaev
6e593cd1f0 Swap dimensions of deconvolution kernel 2017-09-27 22:38:34 +03:00
Dmitry Kurtaev
84cec17913 LSTM layer for TensorFlow importer 2017-09-26 12:59:36 +03:00
Alexander Alekhin
aea25e7f90 Merge pull request #9676 from jrobble:fix_caffe_swaprb 2017-09-25 16:05:11 +00:00
jrobble
c67ad49378 Set swapRB to false in Caffe tests and examples. 2017-09-22 09:58:48 -04:00
Dmitry Kurtaev
222149b9c6 Refactored Padding layer 2017-09-22 12:39:00 +03:00
Dmitry Kurtaev
17a85b16fc Remove reorder_dims attribute of Reshape layer 2017-09-21 16:42:03 +03:00
Dmitry Kurtaev
bdd8cc697a Import wrapped Dropout subgraphs from TensorFlow 2017-09-20 13:30:25 +03:00