From 9f7bce72dbff19fd54ed6cef07ef8efcd4ebc82f Mon Sep 17 00:00:00 2001 From: Daniel Morin Date: Tue, 14 May 2024 21:41:23 -0400 Subject: [PATCH] doc: remove section tensor-agnostic processing --- .../design/machine-learning-analytics.md | 15 --------------- 1 file changed, 15 deletions(-) diff --git a/subprojects/gst-docs/markdown/additional/design/machine-learning-analytics.md b/subprojects/gst-docs/markdown/additional/design/machine-learning-analytics.md index fbbdb3d88a..c9cd044fd8 100644 --- a/subprojects/gst-docs/markdown/additional/design/machine-learning-analytics.md +++ b/subprojects/gst-docs/markdown/additional/design/machine-learning-analytics.md @@ -251,21 +251,6 @@ specific to machine-learning techniques and can also be used to store analysis results from computer-vision, heuristics or other techniques. It can be used as a bridge between different techniques. -### Semantically-Agnostic Tensor Processing -Not all tensor processing is model dependent. Sometime the processing can be -done uniformly on all tensor's values. For example normalization, range -adjustment, offset adjustment, quantization are examples of operations that do -not require knowledge of how the information is encoded in the tensor. To the -contrary of tensor-decoder, elements implementing these types of processing -don't need to know how information is encoded in the tensor but need to know -general information about the tensor like: cardinality, dimension and data type. -Note GStreamer already does a lot of semantically-agnostic tensor processing, -remember image/frame are also a form of tensor, processing like scaling, -cropping, color-space conversion, ... - -#### Semantically-Agnostic Tensor Processing With Graph-Computing Framework -Graph computing frameworks, like ONNX, can also be used this type of operation. - #### Tensor-Decoder Bin And Auto-Plugging Since tensor-decoders are model specific, we expect that many will be created and one way to simplify analytics pipeline creation an promote re-usability is to provide