looks that no tensorflow dependency is introduced, a new model format is
created together with some CPU implementation for inference. With this idea,
Android Neural Network would be a very good reference, see
https://developer.android.google.cn/ndk/guides/neuralnetworks/. It defines how
the model is organized, and also provided a CPU optimized inference
implementation (within the NNAPI runtime, it is open source). It is still under
development but mature enough to run some popular dnn models with proper
performance. We can absorb some basic design. Anyway, just a reference fyi.
(btw, I'm not sure about any IP issue)
For this patch, I have two comments.
1. change from "DNNModel* (*load_default_model)(DNNDefaultModel model_type);"
to " DNNModel* (*load_builtin_model)(DNNBuiltinModel model_type);"
The DNNModule can be invoked by many filters, default model is a good name at
the filter level, while built-in model is better within the DNN scope.
typedef struct DNNModule{
// Loads model and parameters from given file. Returns NULL if it is not
possible.
DNNModel* (*load_model)(const char* model_filename);
// Loads one of the default models
DNNModel* (*load_default_model)(DNNDefaultModel model_type);
// Executes model with specified input and output. Returns DNN_ERROR
otherwise.
DNNReturnType (*execute_model)(const DNNModel* model);
// Frees memory allocated for model.
void (*free_model)(DNNModel** model);
} DNNModule;
2. add a new variable 'number' for DNNData/InputParams
As a typical DNN concept, the data shape usually is: <number, height, width,
channel> or <number, channel, height, width>, the last component denotes its
index changes the fastest in the memory. We can add this concept into the API,
and decide to support <NHWC> or <NCHW> or both.
Thanks
Yejun (郭叶军)
-----Original Message-----
From: ffmpeg-devel [mailto:ffmpeg-devel-boun...@ffmpeg.org] On Behalf Of Sergey
Lavrushkin
Sent: Saturday, May 26, 2018 2:02 AM
To: FFmpeg development discussions and patches <ffmpeg-devel@ffmpeg.org>
Subject: Re: [FFmpeg-devel] [GSOC] [PATCH] DNN module introduction and SRCNN
filter update
>
> You should use the ff_ prefix for internal, non-static functions only.
> You don't need to use any prefix for internal structs.
> The AV* prefix is only for public structs, and the av_ prefix is for
> public functions.
>
> >
> >
> > And you need to indent and prettify the tables a bit.
> >
> >
> > Do you mean kernels and biases in dnn_srcnn.h?
> > Their formatting represents their 4D structure a little bit and it
> > is similar to one that I used for the first srcnn filter version
> > that was successfully pushed before.
>
> Yes, and i suppose they were pushed like that without the reviewer
> noticing they had no indentation or vertical alignment.
>
Here is the patch with DNN module moved to libavfilter and proper formatting of
tables in dnn_srcnn.h.
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