Issue Summary

Documentation and error messages are misleading when using a release version of Caffe on Ubuntu.

Executed Command (if any)

cmake .. -DBUILD_CAFFE=OFF -DCaffe_INCLUDE_DIRS=/usr/include/caffe -DCaffe_LIBS=/usr/lib/x86_64-linux-gnu/libcaffe.so

OpenPose Output (if any)

-- The C compiler identification is GNU 7.5.0
-- The CXX compiler identificatio

Paper says:

Code is following
https://github.com/CMU-Perceptual-Computing-Lab/caffe_train/blob/master/src/caffe/cpm_data_transformer.cpp
<img width="1077" alt="screen shot 2017-11-14 at 01 33 49" src="https://user-images.

Is there code on just using the models for inference? I want to feed the model images (each image may have multiple humans), and I would expect the outputs to be the body part estimations (in JSON or whatever format).

As I am reading the issues, especially the one on making inference with a web camera, I "think" that using these models is not trivial. For example, it seems to be I have to dete

As the subject states: the instructions to fetch and make this repo are simply not geared towards Win10 users, and are both incorrect and very frustrating. There needs to be a section specifically for Windows 10 users, and should have 2 sets of instructions for those that use Git-Bash or Mingw32/64, and those that use PowerShell.

I personally use Git-Bash, and after 25 minutes here still have n

I'm a little bit confused when I run and analysis your repo
for i in range(17):
for s in subset:
index = s[np.array(util.limbSeq[i]) - 1]
if -1 in index:
continue
cur_canvas = canvas.copy()

how to explain and understand s[np.array(util.limbSeq[i]) - 1] ? can we use util.limbSeq[i]) - 1 to replace the s[np.array(util.limbSeq[i]) -

Hope this is helpful for others. I have tested it on Mojave. Great library!

# How to Install on MacOSX #
git clone https://github.com/rwightman/posenet-python.git  # Clone Git Repo
cd posenet-python/ # Change directory to project 
virtualenv venv     # Create a virtual environment
source venv/bin/activate # Activate Virtual Environment
sudo pip3 install tensorflow scipy pyyaml opencv-