Moved notebooks to a separate dir, improved CI for notebooks (openvinotoolkit#118)

* Moved notebooks to a separate dir

* Update sanity-check.yml

* Update

* Update sanity-check.yml

* Update sanity-check.yml

* Update sanity-check.yml

* Update sanity-check.yml

* Update sanity-check.yml

* Update

Author: adrianboguszewski

.github/workflows/sanity-check.yml

@@ -28,9 +28,9 @@ jobs:
         run: |
           # Ensure the directories are passed correctly to the environment variable
           if [[ "${{ github.event_name }}" == "pull_request" ]]; then
-            subproject_dirs=$(git diff --name-only origin/master..HEAD | grep '^demos/' | xargs -I{} dirname "{}" | sort -u | tr '\n' ' ')
+            subproject_dirs=$(git diff --name-only origin/master..HEAD | grep -e '^demos' -e '^notebooks' | xargs -I{} dirname "{}" | sort -u | tr '\n' ' ')
           else
-            subproject_dirs=$(find demos -mindepth 1 -maxdepth 1 -type d ! -name utils | tr '\n' ' ')
+            subproject_dirs=$(find demos notebooks -mindepth 1 -maxdepth 1 -type d ! -name utils | tr '\n' ' ')
           fi
           echo "subproject_dirs=$subproject_dirs" >> $GITHUB_ENV
       - name: Categorize subprojects
@@ -44,11 +44,11 @@ jobs:
           for dir in $subproject_dirs; do
             if [ -f "$dir/package.json" ]; then
               js+=("$dir")
-            elif [ -f "$dir/main.ipynb" ]; then
+            elif find "$dir" -maxdepth 1 -name "*.ipynb" | grep -q "."; then
               notebook+=("$dir")
-            elif grep -q "gradio" "$dir/requirements.txt"; then
+            elif [ -f "$dir/requirements.txt" ] && grep -q "gradio" "$dir/requirements.txt"; then
               gradio+=("$dir")
-            elif grep -q -- "--stream" "$dir/main.py"; then
+            elif [ -f "$dir/main.py" ] && grep -q -- "--stream" "$dir/main.py"; then
               webcam+=("$dir")
             fi
           done
@@ -90,10 +90,16 @@ jobs:
         with:
           python: ${{ matrix.python }}
           project: ${{ matrix.subproject }}
+      - name: Use downloaded video as a stream
+        shell: bash
+        run: |
+          cd ${{ matrix.subproject }}
+          # replace video_path with sample_video.mp4
+          find . -name "*.ipynb" -exec sed -E -i "s/video_path\s*=\s*(['\"]?.*?['\"]?)/video_path=\\\\\"sample_video.mp4\\\\\"\\\n\",/g" {} +
       - uses: ./.github/reusable-steps/timeouted-action
         name: Run Notebook
         with:
-          command: jupyter nbconvert --to notebook --execute main.ipynb
+          command: jupyter nbconvert --to notebook --execute *.ipynb
           project: ${{ matrix.subproject }}
 
   gradio:

demos/CONTRIBUTING.md

@@ -6,7 +6,7 @@ The goal of any demo in this directory is to present OpenVINO as an optimization
 
 Rules:
 - The demo must be standalone - no dependencies to other demos (dependency to utils is ok)
-- The demo must be a Python script (preferable one) called `main.py` or a Jupyter notebook
+- The demo must be a Python script called `main.py`
 - All dependencies must be pinned to specific, stable, and tested versions and provided in the corresponding `requirements.txt` file (script) or the first code cell (notebook) 
 - If the demo is visual (produces any video/image output) it must add an OpenVINO watermark to the output video/image (see utils)
 - The demo must provide a README file with the instructions on installing the environment, setting up and running (+ changing the behavior if applicable)

demos/onnxruntime_lcm_demo/main.ipynb notebooks/onnxruntime_lcm/Latent Consistency Models with ONNX and OpenVINO Execution Provider.ipynb

@@ -1,24 +1,24 @@
-# Running YOLOv8 Object Detection with ONNX and OpenVINO
-
-In this demo, we'll perform object detection leveraging YOLOv8 with Ultralytics, and with ONNX using the OpenVINO Execution Provider for enhanced performance, to detect up to 80 different objects (e.g., birds, dogs, etc.)
-This sample was modified from one of the [available Onnx Runtime Inference examples here](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/python/OpenVINO_EP/yolov8_object_detection). 
-
-<p align="center">
-    <img src="https://github.com/user-attachments/assets/a3e35991-0c3b-47e0-a94a-c70d7b135261"/>
-</p>
-
-
-### Installation Instructions
-- Create a virtual environment using 
-  ```sh  
-  python -m venv <venv-name>
-  ```
-- To activate the virtual environment use
-  ```sh
-  \<venv-name>\Scripts\activate
-  ```
-- Install the required dependencies via pip
-  ```sh
-  pip install -r requirements.txt
-  ```
+# Running YOLOv8 Object Detection with ONNX and OpenVINO
+
+In this demo, we'll perform object detection leveraging YOLOv8 with Ultralytics, and with ONNX using the OpenVINO Execution Provider for enhanced performance, to detect up to 80 different objects (e.g., birds, dogs, etc.)
+This sample was modified from one of the [available Onnx Runtime Inference examples here](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/python/OpenVINO_EP/yolov8_object_detection). 
+
+<p align="center">
+    <img src="https://github.com/user-attachments/assets/a3e35991-0c3b-47e0-a94a-c70d7b135261"/>
+</p>
+
+
+### Installation Instructions
+- Create a virtual environment using 
+  ```sh  
+  python -m venv <venv-name>
+  ```
+- To activate the virtual environment use
+  ```sh
+  \<venv-name>\Scripts\activate
+  ```
+- Install the required dependencies via pip
+  ```sh
+  pip install -r requirements.txt
+  ```
 - Now you only need a Jupyter server to start.

demos/onnxruntime_lcm_demo/README.md notebooks/onnxruntime_lcm/README.md

@@ -419,8 +419,8 @@
     "#Inference on webcam or live streams\n",
     "import cv2\n",
     "\n",
-    "stream = 0 #can set to video path like /path/input.mp4\n",
-    "cap = cv2.VideoCapture(stream)\n",
+    "video_path = 0 #can set to video path like /path/input.mp4\n",
+    "cap = cv2.VideoCapture(video_path)\n",
     "assert cap.isOpened(), \"Error reading video file\"\n",
     "w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))\n",
     "frame_count = 0\n",
@@ -471,7 +471,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,

demos/onnxruntime_lcm_demo/requirements.txt notebooks/onnxruntime_lcm/requirements.txt

@@ -1,10 +1,10 @@
---extra-index-url https://download.pytorch.org/whl/cpu
-
-jupyterlab==4.2.5
-
-openvino==2024.3.0
-ultralytics==8.2.81
-onnxruntime-openvino==1.19.0
-onnx==1.17.0
-onnxruntime==1.19.2
-setuptools==73.0.1
+--extra-index-url https://download.pytorch.org/whl/cpu
+
+jupyterlab==4.2.5
+
+openvino==2024.3.0
+ultralytics==8.2.81
+onnxruntime-openvino==1.19.0
+onnx==1.17.0
+onnxruntime==1.19.2
+setuptools==73.0.1