From 1ed31a3c42535e5b9aaab5f58bf1ae39aec87276 Mon Sep 17 00:00:00 2001 From: Anatoly Orlov Date: Sat, 10 Mar 2018 22:03:49 +0300 Subject: [PATCH] readme --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index cd4f731..344f970 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,8 @@ This fork contains **pure python version** of [Realtime Multi-Person Pose Estima I this fork I've reimplemented images argumentation in pure python, it is significanly shorter(**285** lines vs **1202** lines in Michal Faber's C++ **rmpe_server**, and way less than in original work) -Despite of Python language this code is **significantly faster** than original implementation(140 images/s vs 30 images/s C++ code on my machine). This is not really useful since most of people doesn't have 5 GPUs, but has large hack value. The magic is in combining all affine transformations to one matrix, and calling single **warpAffine**, and vectorized numpy computation of PAFs and Heatmaps. +Despite of Python language this code is **significantly faster** than original implementation(140 images/s vs 30 images/s C++ code on my machine). This is not really useful since most of people don't have 5 GPUs, but just to prove the point python programs could be fast. The magic is in combining all affine transformations to one matrix, and calling single **warpAffine**, and vectorized numpy computation of PAFs and Heatmaps. + Could be run as iterator inside **train_pose.py** (default), or as separate **./rmpe_server.py**