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465 Commits

Author SHA1 Message Date
Davis King 05bbe4f4bb Fixed spelling error in comment 2016-09-30 23:09:03 -04:00
Davis King 4a408d5e07 Fixed example 2016-09-05 15:40:54 -04:00
Davis King d5dc371ff8 Added random_cropper and DNN MMOD example programs. 2016-09-05 15:39:31 -04:00
Davis King 9e42f86cd3 Adjusted face boxes so they are a little bit more accurately placed. 2016-09-05 15:38:44 -04:00
Davis King 87efe17225 Added a call to set_all_bn_running_stats_window_sizes() to set this value to 
what it was when this example was trained (since I just modified the default
value in dlib to something else).
 2016-09-05 15:00:52 -04:00
Davis King 91150823eb Simplified example to show only the C++11 version of the code. 2016-08-30 14:58:38 -04:00
Davis King 4ee1f6644d Made thread_pool and parallel_for propagate exceptions from task threads to 
calling code.
 2016-08-30 14:44:46 -04:00
Davis King 02d8ebc903 fixed typo in example 2016-08-24 06:56:35 -04:00
Davis King 4f0c2ba092 Fixed typo in network definition. 2016-08-22 14:53:26 -04:00
Davis King bdbc8e418b Renamed something to avoid name clash with standard library. 2016-07-22 16:22:57 -04:00
Evgeniy Fominov bbeac285d1 Shape predictor trainer optimizations (#126) 
* Shape predictor trainer optimizations

* Fixed performance leak in single thread mode & made VS2010 support
 2016-07-22 09:11:13 -04:00
Davis King 5e550a261e Added some more comments 2016-06-25 18:31:21 -04:00
Davis King 15f4081cdf fixed compiler warning 2016-06-25 13:03:12 -04:00
Davis King a9343acc51 Changed code so the validation listing file doesn't have to be in the imagenet 
root folder.
 2016-06-25 12:31:59 -04:00
Davis King efcdc871e4 fixed compiler warnings 2016-06-25 11:17:07 -04:00
Davis King f88f784a4e Minor formatting cleanup 2016-06-25 09:47:36 -04:00
Davis King 2469352e95 fixed typo 2016-06-25 09:42:22 -04:00
Davis King fcf7ab6daa Updated examples to refer to the correct file names. 2016-06-25 09:40:11 -04:00
Davis King a76b642a4e renamed examples 
--HG--
rename : examples/dnn_mnist_advanced_ex.cpp => examples/dnn_introduction2_ex.cpp
rename : examples/dnn_mnist_ex.cpp => examples/dnn_introduction_ex.cpp
 2016-06-25 09:34:53 -04:00
Davis King 541ce716b9 Added the program that made the resnet model. 2016-06-25 09:26:51 -04:00
Davis King 1123eaa134 Changed the message that cmake displays when opencv isn't found so users don't get confused. 2016-06-24 01:28:52 -04:00
Davis King 87493f4971 Added some comments 2016-06-22 22:30:45 -04:00
Davis King f453b03f39 Added an example showing how to classify imagenet images. 2016-06-22 22:26:48 -04:00
Fm cc38772715 #pragma warning moved to dnn.h 2016-06-22 18:09:26 +03:00
Fm 2e741703ef removed wrong empty line 2016-06-22 17:54:28 +03:00
Fm 9930d3279e removed comment form net printing 2016-06-22 17:53:37 +03:00
Fm f3b0159ef1 #pragma warning for C4503 and /bigobj 2016-06-22 17:51:06 +03:00
Fm 63c2465f32 Added compiler flags for VS compiling DNN samples without warnings 2016-06-22 17:22:43 +03:00
Davis King 1c01eaec1d updated example comments 2016-06-11 11:54:44 -04:00
Davis King 6e0f13ba06 minor cleanup 2016-05-30 13:14:04 -04:00
Davis King 53e9c15811 Clarified some parts of the example. 2016-05-30 08:50:28 -04:00
Fm d32bcdfa3d Changed concat syntax into concat1, concat2..., made dtest more readable:: 2016-05-27 09:56:00 +03:00
Fm 2f7d3578d2 Added layer access and printing examples to inception sample 2016-05-26 19:40:10 +03:00
Fm 1f0318e222 depth_group replaced with concat layer 2016-05-26 17:43:54 +03:00
Fm 93e786db6c Merge branch 'master' of https://github.com/davisking/dlib into dnn_group_layer 2016-05-26 17:15:56 +03:00
Davis King b9332698fe updated example 2016-05-23 22:01:47 -04:00
Davis King 5e70b7a2c6 Cleaned up code a little and made the example use a better version of the architecture. 2016-05-22 13:17:10 -04:00
Davis King 0cd76f899b Added an error message if a camera isn't available. 2016-05-18 22:22:56 -04:00
Fm 28c4a48281 Grouping layer added 2016-05-17 13:07:04 +03:00
Davis King ee2a0070db Added comment to show how to deserialize a network. 2016-05-15 14:52:33 -04:00
Davis King ba0f7c5c53 Added a function to dnn_trainer that lets you query the "steps without 
progress" estimate.  I also renamed the get/set functions for the shrink amount
to have a consistent name and use the word "factor" instead of "amount".
 2016-05-15 14:48:06 -04:00
Davis King 13cc545da3 clarified comments. 2016-05-15 14:31:06 -04:00
Davis King 66166c674d Changed the solver interface to take the learning rate and the layer details 
object as an input.  This allows the solvers to exhibit a more complex behavior
that depends on the specific layer.  It also removes the learning rate from the
solver's parameter set and pushes it entirely into the core training code.
This also removes the need for the separate "step size" which previously was
multiplied with the output of the solvers.

Most of the code is still the same, and in the core and trainer the step_size
variables have just been renamed to learning_rate.  The dnn_trainer's relevant
member functions have also been renamed.

The examples have been updated to reflect these API changes.  I also cleaned up
the resnet definition and added better downsampling.
 2016-05-14 20:30:45 -04:00
Davis King 1e70c721a4 Made example use the "everything" version of avg pooling. 2016-05-07 14:30:42 -04:00
Davis King 4a7633056c Fixed avg pooling filter sizes to avoid errors with the new rules about 
non-one based strides.
 2016-05-04 21:40:29 -04:00
Davis King 1f0705ae92 clarified example 2016-04-28 19:41:27 -04:00
Davis King d31723ff45 Fixed typo in example 2016-04-19 06:44:31 -04:00
Davis King b16cc99e8f Added comments about using multiple GPUs 2016-04-18 22:48:07 -04:00
Davis King 603d474352 - Renamed network_type::num_layers to network_type::num_computational_layers. 
- Made layer() recurse into repeat objects so that the index given to layer()
  does what you would expect.
- Added an operator<< for network objects that prints the network architecture.
 2016-04-16 10:50:15 -04:00
Davis King 61591b13e2 Seeded random number generator with the clock since that's generally a good 
thing to do for this kind of training.
 2016-04-11 23:11:18 -04:00