Merge branch 'dev-0.11'

.github/workflows/main.yml

@@ -10,65 +10,6 @@ on:
       - dev-*
 
 jobs:
-  build_autotools:
-    runs-on: ubuntu-18.04
-    strategy:
-      matrix:
-       container: ["ridgerun/r2inference-ubuntu-18.04:v0.1.5", "ridgerun/r2inference-ubuntu-16.04:v0.3.1"]
-    container:
-      image: ${{ matrix.container }}
-    env:
-      PREFIX: /usr/lib/x86_64-linux-gnu/
-      CFLAGS: -Werror
-      CXXFLAGS: -Werror
-    steps:
-    - uses: actions/checkout@v2
-    - name: Build backend
-      run: |
-        tar -C /usr/local -xzf /root/r2inference/backends/tensorflow/v1.15.0/libtensorflow-cpu-linux-x86_64-1.15.0.tar.gz
-        ldconfig
-    - name: Checkout r2i repo
-      uses: actions/checkout@master
-      with:
-        repository: RidgeRun/r2inference
-    - name: Build r2i
-      run: |
-        NOCONFIGURE=1 ./autogen.sh
-        ./configure --disable-docs --enable-tensorflow
-        make
-        make install
-    - name: Checkout gst-inference repo
-      uses: actions/checkout@v2
-      with:
-        submodules: true
-    - name: Build gst-inference
-      run: |
-        CFLAGS="${{ env.CFLAGS }}"
-        CXXFLAGS="${{ env.CXXFLAGS }}"
-        NOCONFIGURE=1 ./autogen.sh
-        ./configure  --disable-docs --prefix $PREFIX --libdir $PREFIX
-        make
-    - name: Check gst-inference
-      env:
-        LD_LIBRARY_PATH: /usr/local/lib/
-      run: make check VERBOSE=1
-    - name: Install gst-inference
-      run: |
-        make install
-    - name: Check gst-inference install
-      env:
-        LD_LIBRARY_PATH: /usr/local/lib/
-      run: gst-inspect-1.0 inference
-    - name: Run GStreamer pipeline
-      env:
-        ROOT: /root/r2inference/resources/InceptionV1_TensorFlow
-        LD_LIBRARY_PATH: /usr/local/lib/
-      run: |
-        GST_DEBUG=2,inferencebin:6 gst-launch-1.0 filesrc location=$ROOT/Egyptian_cat.jpg ! jpegparse ! jpegdec ! \
-        inferencebin arch='inceptionv1' model-location=$ROOT/graph_inceptionv1_tensorflow.pb \
-        backend='tensorflow' input-layer='input' output-layer='InceptionV1/Logits/Predictions/Reshape_1' \
-        labels=$ROOT/imagenet_labels.txt crop=false overlay=true filter=-1 ! \
-        fakesink silent=false sync=false async=false -v
   build_meson:
     runs-on: ubuntu-18.04
     strategy:
@@ -94,10 +35,9 @@ jobs:
       run: |
         CFLAGS="${{ env.CFLAGS }}"
         CXXFLAGS="${{ env.CXXFLAGS }}"
-        NOCONFIGURE=1 ./autogen.sh
-        ./configure --disable-docs --enable-tensorflow
-        make
-        make install
+        meson build --prefix $PREFIX -Denable-tensorflow=true -Denable-docs=disabled
+        ninja -C build
+        ninja -C build install
     - name: Checkout gst-inference repo
       uses: actions/checkout@v2
       with:

.gitignore

@@ -4,35 +4,7 @@
 \#*
 *.orig
 
-# Autotools cruft
-aclocal.m4
-autom4te.cache/
-compile
-config.guess
-config.h
-config.h.in
-config.status
-config.sub
-configure
-install-sh
-missing
-Makefile
-Makefile.in
-depcomp
-libtool
-ltmain.sh
-m4/
-.deps/
-.libs/
-stamp-h*
-autoregen.sh
-gst-inference-*.pc
-
 # Build outputs
-.deps/
-.libs/
-*.la
-*.lo
 *.o
 
 # Git conflict files
@@ -66,4 +38,3 @@ cscope.out
 # Examples
 tests/examples/classification/classification
 tests/examples/detection/detection
-tests/examples/embedding/embedding

README.md

@@ -1,4 +1,6 @@
-<a href="https://developer.ridgerun.com/wiki/index.php?title=GstInference"><img src="https://developer.ridgerun.com/wiki/images/thumb/9/92/GstInference_Logo_with_name.jpeg/600px-GstInference_Logo_with_name.jpeg" height="400" width="400"></a>
+GstInference               |  Coral from Google
+:-------------------------:|:-------------------------:
+[<img src="https://developer.ridgerun.com/wiki/images/thumb/9/92/GstInference_Logo_with_name.jpeg/600px-GstInference_Logo_with_name.jpeg" height="400" width="400">](https://developer.ridgerun.com/wiki/index.php?title=GstInference)  |  [<img src="https://developer.ridgerun.com/wiki/images/6/62/Works_with_coral_svg.svg" height="400" width="400">](https://coral.ai/products/#prototyping-products)
 
 # GstInference
 
@@ -8,7 +10,7 @@ GstInference is an open-source project from Ridgerun Engineering that provides a
 
 This repo uses **[R²Inference](https://github.com/RidgeRun/r2inference)**, an abstraction layer in C/C++ for a variety of machine learning frameworks. With R²Inference a single C/C++ application may work with models on different frameworks. This is useful to execute inference taking advantage of different hardware resources such as CPU, GPU, or  AI optimized acelerators.
 
-GstInference provides several example elements for common applications, such as [`Inception v4`](ext/r2inference/gstinceptionv4.c) for image classification, [`TinyYOLO v2`](ext/r2inference/gsttinyyolov2.c) for object detection, and [`FaceNet`](ext/r2inference/gstfacenetv1.c) for face recognition. Examples are provided for performing inference on any GStreamer video stream.
+GstInference provides several example elements for common applications, such as [`Inception v4`](ext/r2inference/gstinceptionv4.c) for image classification and  [`TinyYOLO v2`](ext/r2inference/gsttinyyolov2.c) for object detection. Examples are provided for performing inference on any GStreamer video stream.
 
 <img src="https://developer.ridgerun.com/wiki/images/thumb/4/4f/GstInference-examples.jpeg/800px-GstInference-examples.jpeg" width="800">
 
@@ -25,8 +27,6 @@ Follow the steps to get GstInference running on your platform:
 
 We provide GStreamer [example pipelines](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Example_pipelines) for all our suported platforms,architectures and backends. 
 
-We also provide [example applications](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Example_Applications) for classification, detection and face recognition.
-
-Our [smart lock](tests/examples/face_detection/README.md) example can get you started with a real security camera application.
+We also provide [example applications](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Example_Applications) for classification and detection.
 
 We also provide example trained models on our [model zoo](https://developer.ridgerun.com/wiki/index.php?title=GstInference/Model_Zoo)