Dnn models has different data preprocess requirements. Scale and mean
parameters are added to preprocess input data.
Signed-off-by: Wenbin Chen <wenbin.chen@intel.com>
Dnn models have different input layout (NCHW or NHWC), so a
"layout" option is added
Use openvino's API to do layout conversion for input data. Use swscale
to do layout conversion for output data as openvino doesn't have
similiar C API for output.
Signed-off-by: Wenbin Chen <wenbin.chen@intel.com>
When ov_model_const_input_by_name/ov_model_const_output_by_name
failed, input_port/output_port can be wild pointer.
Signed-off-by: Zhao Zhili <zhilizhao@tencent.com>
OpenVINO API 2.0 was released in March 2022, which introduced new
features.
This commit implements current OpenVINO features with new 2.0 APIs. And
will add other features in API 2.0.
Please add installation path, which include openvino.pc, to
PKG_CONFIG_PATH mannually for new OpenVINO libs config.
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Wenbin Chen <wenbin.chen@intel.com>
This also fixed a warning: implicit conversion from enumeration
type 'TF_DataType' (aka 'enum TF_DataType') to different
enumeration type 'DNNDataType'.
Signed-off-by: Zhao Zhili <zhilizhao@tencent.com>
Native backend will be removed in following commits, so change the
dnn interface and modify the error message in it first.
Signed-off-by: Ting Fu <ting.fu@intel.com>
Bugfix: The OpenVino DNN backend in the 'async' mode sets
'task->inference_done' to 'complete' prior to data copy from
OpenVino output buffer to task's output frame.
This order causes task destroy in ff_dnn_get_result_common()
prior to model output processing.
Signed-off-by: Rafik Saliev <rafik.f.saliev@intel.com>
Dump all input/output names to OVModel struct. In case other funcs use
them for reporting errors or locating issues.
Signed-off-by: Ting Fu <ting.fu@intel.com>
This patch removes all occurences of DNNReturnType from the DNN module.
This commit replaces DNN_SUCCESS by 0 (essentially the same), so the
functions with DNNReturnType now return 0 in case of success, the negative
values otherwise.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Switch to returning specific error codes or DNN_GENERIC_ERROR
when an error is encountered in the common DNN backend functions.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Switch to returning specific error codes or DNN_GENERIC_ERROR
when an error is encountered.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Switch to returning specific error codes or DNN_GENERIC_ERROR
when an error is encountered. For TensorFlow C API errors, currently
DNN_GENERIC_ERROR is returned.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Switch to returning specific error codes or DNN_GENERIC_ERROR
when an error is encountered. For OpenVINO API errors, currently
DNN_GENERIC_ERROR is returned.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit returns specific error codes from the functions in the
dnn_io_proc instead of DNN_ERROR.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit returns specific error codes from the execution
functions in the Native Backend layers instead of DNN_ERROR.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This patch renames the InferenceItem to LastLevelTaskItem in the
three backends to avoid confusion among the meanings of these structs.
The following are the renames done in this patch:
1. extract_inference_from_task -> extract_lltask_from_task
2. InferenceItem -> LastLevelTaskItem
3. inference_queue -> lltask_queue
4. inference -> lltask
5. inference_count -> lltask_count
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Remove async flag from filter's perspective after the unification
of async and sync modes in the DNN backend.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit unifies the async and sync mode from the DNN filters'
perspective. As of this commit, the Native backend only supports
synchronous execution mode.
Now the user can switch between async and sync mode by using the
'async' option in the backend_configs. The values can be 1 for
async and 0 for sync mode of execution.
This commit affects the following filters:
1. vf_dnn_classify
2. vf_dnn_detect
3. vf_dnn_processing
4. vf_sr
5. vf_derain
This commit also updates the filters vf_dnn_detect and vf_dnn_classify
to send only the input frame and send NULL as output frame instead of
input frame to the DNN backends.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit adds the case handling if the asynchronous execution
of a request fails by checking the exit status of the thread when
joining before starting another execution. On failure, it does the
cleanup as well.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
The frame allocation and filling the TaskItem with execution
parameters is common in the three backends. This commit shifts
this logic to dnn_backend_common.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Since requests are running in parallel, there is inconsistency in
the status of the execution. To resolve it, we avoid using mutex
as it would result in single TF_Session running at a time. So add
TF_Status to the TFRequestItem
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This patch adds error handling for cases where the execute_model_tf
fails, clears the used memory in the TFRequestItem and finally pushes
it back to the request queue.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit enables async execution in the TensorFlow backend
and adds function to flush extra frames.
The async execution mechanism executes the TFInferRequests on
a separate thread which is joined before the next execution of
same TFRequestItem/while freeing the model.
The following is the comparison of this mechanism with the existing
sync mechanism on TensorFlow C API 2.5 CPU variant.
Async Mode: 4m32.846s
Sync Mode: 5m17.582s
The above was performed on super resolution filter using SRCNN model.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit adds a function for execution of TFInferRequest and documentation
for functions related to TFInferRequest.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit adds an async execution mechanism for common use
in the TensorFlow and Native backends.
This commit also adds the documentation of typedefs and functions in
the async module for common use in DNN backends.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
The reasons for including them don't exist any longer: ff_tlog() has
been moved to libavutil/internal.h and FF_QSCALE_TYPE_* has been moved
to qp_table.h.
Reviewed-by: Nicolas George <george@nsup.org>
Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@outlook.com>
It is not used here at all; instead, add it where it is used without
including it or any of the arch-specific CPU headers.
Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@outlook.com>
Wenbin Chen
Zhao Zhili
Ting Fu
Saliev, Rafik F
Shubhanshu Saxena
Andreas Rheinhardt