From 51238a98c777b7a49a07a62b508ad6feb0422ee5 Mon Sep 17 00:00:00 2001 From: Michal Faber Date: Fri, 2 Oct 2020 18:50:24 +0200 Subject: [PATCH] updated README --- README.md | 9 +++++---- requirements.txt | 2 +- setup.py | 2 +- 3 files changed, 7 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 968cf20..e70646a 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@ For example the lists : ``` Why is the first convolution repeated ? There is an argument ‘r2’ in the notation which means that this block should be repeated 2 times. -I came across this notation in an excellent git repo: [rwightman](https://github.com/rwightman/pytorch-image-models) where the author uses this notation to build stacks of layers in some of his models. This is definitely a very concise method. I find it easier to manage experiments by storing model definitions as text files instead of constantly tweaking Python scripts. +I came across this notation in this impressive git repo: [pytorch-image-models](https://github.com/rwightman/pytorch-image-models) where the author uses this notation to build stacks of layers in some of his models. This is definitely a very concise method. I find it easier to manage experiments by storing model definitions as text files instead of constantly tweaking Python scripts. My implementation goes a step further and introduces operations like concatenation, multiplications and any custom function which operates on tensors and can be used in the method **def call(self, x)** of custom class derived from **tf.keras.Model**. New block types or operations can be easily registered. @@ -100,7 +100,7 @@ Individual blocks can have custom name for example **c3#ir_r3...** This is usefu This is an example of a more complex model with concatenation, upsacling and multiple outputs. The architecture is described in detail here: [Single-Network Whole-Body Pose Estimation](https://arxiv.org/abs/1909.13423) -Although the original implementation uses more stages and VGG as a backbone, I have created a smaller version based on Mobilenet and only 3 paf stages and one heatmap stage. +Although the original implementation uses more stages and VGG as a backbone, I have created a smaller version based on MobilenetV3 and only 3 paf stages and one heatmap stage. Here is the [training code](https://github.com/michalfaber/tensorflow_Realtime_Multi-Person_Pose_Estimation) Definition of architecture @@ -195,7 +195,7 @@ This model has multiple stacks. How can we distinguish an operation from a layer ['cnct:c3#:upscaled_c4#'] ``` -This is a concatenation operation denoted by a code 'cnct:'. It has 2 arguments c3# and upscaled_c4# which are references to other blocks. +This is a concatenation operation denoted by a code **cnct:**. It has 2 arguments **c3#** and **upscaled_c4#** which are references to other blocks. Take a look at this special construct: @@ -208,7 +208,7 @@ Take a look at this special construct: ] } ``` -Here we select **stage_1#** and **backbone#** as input to the ‘'stage_2#’ stack. The operation in the next line **cnct:** will perform concatenation on the previously selected stacks +Here we select **stage_1#** and **backbone#** as input to the **stage_2#** stack. The operation in the next line **cnct:** will perform concatenation on the previously selected stacks. ## How to add more layers and operations @@ -270,6 +270,7 @@ There is still work going on in this library so I obviously don’t recommend in pip install -r requirements.txt cd examples python eval_mobilenet_v3.py + python eval_openpose_singlenet.py ``` ## Full doc diff --git a/requirements.txt b/requirements.txt index 751e9f2..81428ee 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,4 @@ -tensorflow==2.2.1 +tensorflow-gpu==2.2.1 tqdm==4.50.0 opencv-python-headless==4.4.0.44 matplotlib==3.3.2 \ No newline at end of file diff --git a/setup.py b/setup.py index 5795748..5bf916a 100644 --- a/setup.py +++ b/setup.py @@ -9,7 +9,7 @@ author_email='michal@worldestimators.com', url='https://github.com/michalfaber/tf_netbuilder', packages=find_packages(exclude=['examples', 'resources']), - install_requires=['tensorflow >= 2.2.1'], + install_requires=['tensorflow-gpu >= 2.2.1'], python_requires='>=3.6', classifiers=[ # How mature is this project? Common values are