mirror/darknet
1
0
Fork 0
mirror of https://github.com/pjreddie/darknet.git synced 2023-08-10 21:13:14 +03:00
Code Issues Projects Releases Wiki Activity
Files
ae1768e5831caa95214b93b08ee711aede36df07
darknet/src
History
AlexeyAB 5e448c00f3 Added Focal loss. Use focal_loss=1 in the [region] layer in your cfg-file. 
alpha = 0.5, gamma = 2
2018-03-05 19:59:29 +03:00
..
activation_kernels.cu
Added CUDA-streams to Darknet-Yolo forward inference
2017-12-31 20:10:32 +03:00
activation_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
activation_layer.h
idk
2016-01-18 15:40:14 -08:00
activations.c
checkpoint
2016-06-20 13:18:59 -07:00
activations.h
adding new tiny-yolo
2016-09-07 22:27:56 -07:00
art.c
Supported OpenCV 3.0 and 2.4.13. Supported Windows and Linux.
2017-08-03 00:48:29 +03:00
avgpool_layer_kernels.cu
Fix for cuda 7.5
2015-11-15 19:51:26 -08:00
avgpool_layer.c
🔥 🔥 :dragonite:
2016-11-16 00:15:46 -08:00
avgpool_layer.h
shortcut layers, msr networks
2015-12-14 11:57:10 -08:00
batchnorm_layer.c
:vegan: :charizard:
2016-11-24 22:56:23 -08:00
batchnorm_layer.h
stable
2016-05-11 10:45:50 -07:00
blas_kernels.cu
Added CUDA-streams to Darknet-Yolo forward inference
2017-12-31 20:10:32 +03:00
blas.c
Fixed reorg_layer. Old reorg can be used as [reorg_old] in the cfg-file.
2018-03-03 18:09:46 +03:00
blas.h
It takes into account the Difficult for calculating mAP for PascalVOC
2018-02-16 23:55:37 +03:00
box.c
Changed class to class_id
2018-03-01 15:14:58 +03:00
box.h
CVPR Experiments
2015-11-03 19:23:42 -08:00
captcha.c
better multigpu
2016-09-20 11:34:49 -07:00
cifar.c
Changed class to class_id
2018-03-01 15:14:58 +03:00
classifier.c
Changed class to class_id
2018-03-01 15:14:58 +03:00
classifier.h
so much need to commit
2016-05-06 16:25:16 -07:00
coco.c
Compile fix
2018-03-01 16:33:40 +03:00
col2im_kernels.cu
updates and things
2016-09-01 16:48:41 -07:00
col2im.c
updates and things
2016-09-01 16:48:41 -07:00
col2im.h
Detection is back, baby\!
2015-02-10 19:41:03 -08:00
compare.c
Changed class to class_id
2018-03-01 15:14:58 +03:00
connected_layer.c
🔥 🔥 :dragonite:
2016-11-16 00:15:46 -08:00
connected_layer.h
adding new tiny-yolo
2016-09-07 22:27:56 -07:00
convolutional_kernels.cu
Added support for Tensor Cores CC >= 7.0 (V100). For FP16/32 (mixed precision) define CUDNN_HALF should be used.
2018-02-25 16:29:44 +03:00
convolutional_layer.c
Added support for Tensor Cores CC >= 7.0 (V100). For FP16/32 (mixed precision) define CUDNN_HALF should be used.
2018-02-25 16:29:44 +03:00
convolutional_layer.h
Added support for Tensor Cores CC >= 7.0 (V100). For FP16/32 (mixed precision) define CUDNN_HALF should be used.
2018-02-25 16:29:44 +03:00
cost_layer.c
🔥 🔥 :dragonite:
2016-11-16 00:15:46 -08:00
cost_layer.h
shortcut layers, msr networks
2015-12-14 11:57:10 -08:00
cpu_gemm.c
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
crnn_layer.c
ADAM
2016-10-26 08:35:44 -07:00
crnn_layer.h
stuff
2016-02-29 13:54:12 -08:00
crop_layer_kernels.cu
lots of stuff
2016-01-28 12:30:38 -08:00
crop_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
crop_layer.h
lots of stuff
2016-01-28 12:30:38 -08:00
cuda.c
Tracking and Streaming fixed.
2018-01-07 03:30:51 +03:00
cuda.h
If there is excessive GPU-RAM consumption by CUDNN then then do not use Workspace
2018-02-21 19:14:01 +03:00
darknet.c
cheating a little here
2016-11-26 21:21:04 -08:00
data.c
Changed class to class_id
2018-03-01 15:14:58 +03:00
data.h
Fixed compile error
2018-02-08 01:24:38 +03:00
deconvolutional_kernels.cu
good chance I didn't break anything
2016-09-12 13:55:20 -07:00
deconvolutional_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
deconvolutional_layer.h
lots of stuff
2016-01-28 12:30:38 -08:00
demo.c
Fixed saving video file
2018-03-05 13:25:27 +03:00
demo.h
Compile fix
2018-03-01 16:33:40 +03:00
detection_layer.c
It takes into account the Difficult for calculating mAP for PascalVOC
2018-02-16 23:55:37 +03:00
detection_layer.h
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
detector.c
Show avg-loss chart during Training, if compiled with OpenCV. Use -dont_show to disable.
2018-03-04 23:41:23 +03:00
dice.c
better multigpu
2016-09-20 11:34:49 -07:00
dropout_layer_kernels.cu
lots of stuff
2016-01-28 12:30:38 -08:00
dropout_layer.c
🔥 🔥 :dragonite:
2016-11-16 00:15:46 -08:00
dropout_layer.h
lots of stuff
2016-01-28 12:30:38 -08:00
gemm.c
Added CUDA-streams to Darknet-Yolo forward inference
2017-12-31 20:10:32 +03:00
gemm.h
go updates
2016-03-16 04:30:48 -07:00
getopt.c
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
getopt.h
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
gettimeofday.c
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
gettimeofday.h
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
go.c
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
gru_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
gru_layer.h
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
http_stream.cpp
Fix
2018-02-22 23:16:36 +03:00
http_stream.h
Added param -http_port 8090 to show MJPEG-stream in the WebBrowser (Chrome/Firefox)
2018-02-18 02:31:56 +03:00
im2col_kernels.cu
Added CUDA-streams to Darknet-Yolo forward inference
2017-12-31 20:10:32 +03:00
im2col.c
updates and things
2016-09-01 16:48:41 -07:00
im2col.h
Detection is back, baby\!
2015-02-10 19:41:03 -08:00
image.c
Fixed saving video file
2018-03-05 13:25:27 +03:00
image.h
Fixed classifier for AlexNet and Resnet50
2017-09-15 20:31:48 +03:00
layer.c
Added support for Tensor Cores CC >= 7.0 (V100). For FP16/32 (mixed precision) define CUDNN_HALF should be used.
2018-02-25 16:29:44 +03:00
layer.h
Added Focal loss. Use focal_loss=1 in the [region] layer in your cfg-file.
2018-03-05 19:59:29 +03:00
list.c
Slowly refactoring and pushing to GPU
2014-05-02 15:20:34 -07:00
list.h
Parsing, image loading, lots of stuff
2013-11-13 10:50:38 -08:00
local_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
local_layer.h
shortcut layers, msr networks
2015-12-14 11:57:10 -08:00
matrix.c
Changed class to class_id
2018-03-01 15:14:58 +03:00
matrix.h
Go
2016-03-13 23:18:42 -07:00
maxpool_layer_kernels.cu
Added CUDA-streams to Darknet-Yolo forward inference
2017-12-31 20:10:32 +03:00
maxpool_layer.c
cpu batch norm works
2016-11-18 21:51:36 -08:00
maxpool_layer.h
updates and things
2016-09-01 16:48:41 -07:00
network_kernels.cu
Added support for Tensor Cores CC >= 7.0 (V100). For FP16/32 (mixed precision) define CUDNN_HALF should be used.
2018-02-25 16:29:44 +03:00
network.c
Added support for Tensor Cores CC >= 7.0 (V100). For FP16/32 (mixed precision) define CUDNN_HALF should be used.
2018-02-25 16:29:44 +03:00
network.h
Detection and Tracking work well
2018-01-08 01:47:50 +03:00
nightmare.c
stuff
2016-02-29 13:54:12 -08:00
normalization_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
normalization_layer.h
shortcut layers, msr networks
2015-12-14 11:57:10 -08:00
option_list.c
new font strategy
2016-11-05 14:09:21 -07:00
option_list.h
new font strategy
2016-11-05 14:09:21 -07:00
parser.c
Added Focal loss. Use focal_loss=1 in the [region] layer in your cfg-file.
2018-03-05 19:59:29 +03:00
parser.h
Fixed for Linux: detection for batch > 1 and 0x0d at command line
2017-10-29 18:34:55 +03:00
region_layer.c
Added Focal loss. Use focal_loss=1 in the [region] layer in your cfg-file.
2018-03-05 19:59:29 +03:00
region_layer.h
Parameter (max) in the cfg-file has an effect on the Yolo-training
2018-02-10 01:48:38 +03:00
reorg_layer.c
Added: calc_anchors
2018-03-04 03:09:40 +03:00
reorg_layer.h
stuff and things
2016-11-07 23:42:19 -08:00
reorg_old_layer.c
Fixed reorg_layer. Old reorg can be used as [reorg_old] in the cfg-file.
2018-03-03 18:09:46 +03:00
reorg_old_layer.h
Fixed reorg_layer. Old reorg can be used as [reorg_old] in the cfg-file.
2018-03-03 18:09:46 +03:00
rnn_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
rnn_layer.h
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
rnn_vid.c
Supported OpenCV 3.0 and 2.4.13. Supported Windows and Linux.
2017-08-03 00:48:29 +03:00
rnn.c
better multigpu
2016-09-20 11:34:49 -07:00
route_layer.c
🔥 🔥 yolo v2 🔥 🔥
2016-11-17 12:18:24 -08:00
route_layer.h
hey
2016-11-15 22:53:58 -08:00
shortcut_layer.c
So I have this new programming paradigm.......
2016-09-24 23:12:54 -07:00
shortcut_layer.h
shortcut layers, msr networks
2015-12-14 11:57:10 -08:00
softmax_layer.c
It takes into account the Difficult for calculating mAP for PascalVOC
2018-02-16 23:55:37 +03:00
softmax_layer.h
lots of stuff
2016-01-28 12:30:38 -08:00
stb_image_write.h
Fixed STB
2017-08-09 13:34:58 +03:00
stb_image.h
Fixed STB
2017-08-09 13:34:58 +03:00
super.c
better multigpu
2016-09-20 11:34:49 -07:00
swag.c
better multigpu
2016-09-20 11:34:49 -07:00
tag.c
better multigpu
2016-09-20 11:34:49 -07:00
tree.c
hey
2016-11-15 22:53:58 -08:00
tree.h
hey
2016-11-15 22:53:58 -08:00
unistd.h
Sources fixed - Yolo v2 can be used on Windows (MSVS 2015 + CUDA 8.0)
2016-12-02 17:13:40 +03:00
utils.c
Replaced '\r' and '\n' by 0x0d and 0x0a
2018-01-22 19:20:58 +03:00
utils.h
More usage rand_s()
2017-08-18 02:12:44 +03:00
voxel.c
Supported OpenCV 3.0 and 2.4.13. Supported Windows and Linux.
2017-08-03 00:48:29 +03:00
writing.c
better multigpu
2016-09-20 11:34:49 -07:00
yolo_console_dll.cpp
Minor fix
2018-02-21 00:14:46 +03:00
yolo_v2_class.cpp
Changed definition location to adhere to compatability promises
2018-02-19 14:26:53 -08:00
yolo_v2_class.hpp
Fixed Tracking using SparsePyrLKOpticalFlow on CPU
2018-02-20 02:43:04 +03:00
yolo.c
Compile fix
2018-03-01 16:33:40 +03:00