Improving README + docker fix

README.md

@@ -14,16 +14,42 @@ This is a brief explanation on how to enable the ZED camera support.
 
 - Windows 7 64bits or later, Ubuntu 16.04 or 18.04
 - [ZED SDK](https://www.stereolabs.com/developers/) and its dependencies ([CUDA](https://developer.nvidia.com/cuda-downloads))
-- **Darknet** : https://github.com/AlexeyAB/darknet
+- **Darknet** : https://github.com/AlexeyAB/darknet and its dependencies ([cuDNN](https://developer.nvidia.com/cudnn) and OpenCV)
 
-## Installing Darknet
+## Preparing Darknet installation
+
+### cuDNN
+
+In order to get the best performance, [cuDNN](https://developer.nvidia.com/cudnn) should be install before compiling darknet. Heads over to this [TensorFlow documentation article](https://www.tensorflow.org/install/gpu#install_cuda_with_apt) which explains how to setup both CUDA and cuDNN on Ubuntu and Windows.
+
+### OpenCV
+
+OpenCV binaries can be downloaded and install from [opencv.org](https://opencv.org/releases/).
+
+Alternatively, on Ubuntu :
+
+    sudo apt install pkg-config libopencv-dev
+
+### CMake
+
+On Windows, download and install CMAKE using the binary [available here](https://cmake.org/download/).
+
+On Ubuntu, cmake can be installed using the package manager, i.e : `sudo apt install cmake`
+
+However the default version of cmake might be too old, it can easily be updated using the script (located in this repository):
+
+```bash
+sudo bash cmake_apt_update.sh
+```
+
+## Compiling Darknet
 
 [Download](https://github.com/AlexeyAB/darknet) and compile darknet, following the instructions:
 
 - [How to compile on Linux](https://github.com/AlexeyAB/darknet#how-to-compile-on-linux)
 - [How to compile on Windows](https://github.com/AlexeyAB/darknet#how-to-compile-on-windows-using-vcpkg)
 
-### ZED Support Using CMake
+### ZED Support Using CMake (recommended)
 
 If the ZED SDK is installed, CMake will automatically detect it and compile with the ZED support. During the CMake configuration, a message will confirm that the ZED SDK was found.
 
@@ -33,17 +59,21 @@ If the ZED SDK is installed, CMake will automatically detect it and compile with
     -- Found OpenMP_C: -fopenmp (found version "4.5")
     ...
 
+
 ### ZED support Using Makefile
 
 To enable the ZED support in YOLO using the Makefile, simply enable [`GPU` and `ZED_CAMERA`](https://github.com/AlexeyAB/darknet/blob/cce34712f6928495f1fbc5d69332162fc23491b9/Makefile#L8), it's also recommended to enable `CUDNN` for improved performances.
 
 ## 2. Launching the sample
 
-    ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights zed_camera
+Download the yolo weights, either [yolov3](https://pjreddie.com/media/files/yolov3.weights) or [yolov3-tiny](https://pjreddie.com/media/files/yolov3-tiny.weights) for instance, and put them in the local folder.
+
+
+    ./uselib data/coco.names cfg/yolov3.cfg yolov3.weights zed_camera
 
 SVO files are also supported :
 
-    ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights /path/to/svo/file.svo
+    ./uselib data/coco.names cfg/yolov3.cfg yolov3.weights /path/to/svo/file.svo
 
 ## How to use YOLO 3D in Python
 

cmake_apt_update.sh

@@ -0,0 +1,19 @@
+#!/usr/bin/env bash
+
+if [ "$EUID" -ne 0 ]
+  then echo "Please run as root"
+  exit
+fi
+
+# https://apt.kitware.com/
+if [  -n "$(uname -a | grep Ubuntu)" ]; then
+  apt-get update ; apt-get install lsb-release apt-transport-https ca-certificates gnupg software-properties-common wget -y
+  wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | sudo apt-key add -
+  codename=`lsb_release --codename | cut -f2`
+  apt-add-repository 'deb https://apt.kitware.com/ubuntu/ '$codename' main'
+  apt-get install kitware-archive-keyring
+  apt-key --keyring /etc/apt/trusted.gpg del C1F34CDD40CD72DA
+  apt-get cmake
+else
+  echo "This script is only meant for Ubuntu"
+fi  

docker/Dockerfile

@@ -1,10 +1,10 @@
-FROM stereolabs/zed:ubuntu1604-cuda9.0-zed2.7-gl
+FROM stereolabs/zed:ubuntu1604-cuda9.0-zed2.8-gl
 
 ENV CUDNN_VERSION 7.4.1.5
 
-RUN apt-get update && apt-get upgrade -y
-RUN apt-get install python3-dev python3-pip unzip sudo libopencv-dev -y
-RUN apt-get install -y --no-install-recommends libcudnn7=$CUDNN_VERSION-1+cuda9.0 libcudnn7-dev=$CUDNN_VERSION-1+cuda9.0 && apt-mark hold libcudnn7
+RUN apt-get update && apt-get upgrade -y ; \
+     apt-get install python3-dev python3-pip unzip sudo libopencv-dev apt-transport-https ca-certificates gnupg software-properties-common wget -y ; \
+     apt-get install -y --no-install-recommends libcudnn7=$CUDNN_VERSION-1+cuda9.0 libcudnn7-dev=$CUDNN_VERSION-1+cuda9.0 && apt-mark hold libcudnn7
 
 RUN sudo chmod 777 -R /usr/local/zed ; \
     pip3 install --upgrade pip opencv-python ; \
@@ -15,12 +15,17 @@ USER docker
 WORKDIR /home/docker
 
 RUN git clone http://github.com/stereolabs/zed-python.git ; \
-    cd zed-python; sudo pip3 install -r requirements.txt; sudo python3 setup.py install
+    cd zed-python; sudo pip3 install -r requirements.txt; sudo python3 setup.py install ; cd .. ; sudo rm -rf zed-python
 
 RUN git clone https://github.com/stereolabs/zed-yolo.git ; \
-	cd zed-yolo/libdarknet ; make -j8
+    cd zed-yolo ; sudo bash cmake_apt_update.sh ; \
+	cd libdarknet ; make -j8
+
+RUN git clone https://github.com/alexeyAB/darknet.git ; \
+	cd darknet ; cmake . ; make -j8
 
 WORKDIR /home/docker/zed-yolo/
 RUN wget https://pjreddie.com/media/files/yolov3-tiny.weights ; \ 
-	ln -s /home/docker/zed-yolo/yolov3-tiny.weights /home/docker/zed-yolo/zed_python_sample/
+	ln -s /home/docker/zed-yolo/yolov3-tiny.weights /home/docker/zed-yolo/zed_python_sample/ ; \
+    ln -s /home/docker/zed-yolo/yolov3-tiny.weights /home/docker/darknet/
 CMD /bin/bash

docker/README.md

@@ -35,14 +35,9 @@ python3 darknet_zed.py -s /data/<path/to/SVO>
 
 ### Run the C++ sample
 
-From within the container compile the C++ sample :
+From within the container the C++ sample can be started :
 
 ```Bash
-cd /home/docker/zed-yolo/zed_cpp_sample/ ; mkdir build ; cd build; cmake .. ; make ; cd /home/docker/zed-yolo/
-```
-
-Then start it :
-
-```Bash
-zed_cpp_sample/build/darknet_zed libdarknet/data/coco.names libdarknet/cfg/yolov3-tiny.cfg yolov3-tiny.weights /data/<path/to/SVO>
+cd ~/darknet
+./uselib libdarknet/data/coco.names libdarknet/cfg/yolov3-tiny.cfg yolov3-tiny.weights /data/<path/to/SVO>
 ```