[DOCS] Updating Interactive Tutorials for 2025 version -porting (#28821)

port: #28820 Co-authored-by: sgolebiewski-intel <[email protected]>
openvinotoolkit · Feb 4, 2025 · 842a81d · 842a81d
1 parent 63acac4
commit 842a81d
Show file tree

Hide file tree

Showing 348 changed files with 16,532 additions and 15,819 deletions.
diff --git a/docs/nbdoc/consts.py b/docs/nbdoc/consts.py
@@ -6,7 +6,7 @@
 repo_owner = "openvinotoolkit"
 repo_name = "openvino_notebooks"
 repo_branch = "tree/main"
-artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20241209220902/dist/rst_files/"
+artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20250203220806/dist/rst_files/"
 blacklisted_extensions = ['.xml', '.bin']
 notebooks_repo = "https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/"
 notebooks_binder = "https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath="

diff --git a/docs/notebooks/3D-pose-estimation-with-output.rst b/docs/notebooks/3D-pose-estimation-with-output.rst
diff --git a/docs/notebooks/3D-segmentation-point-clouds-with-output.rst b/docs/notebooks/3D-segmentation-point-clouds-with-output.rst
@@ -66,16 +66,22 @@ Imports
     import numpy as np
     import matplotlib.pyplot as plt
     import openvino as ov
-
+    
     # Fetch `notebook_utils` module
     import requests
-
-    r = requests.get(
-        url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py",
-    )
-    open("notebook_utils.py", "w").write(r.text)
-
+    
+    if not Path("notebook_utils.py").exists():
+        r = requests.get(
+            url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py",
+        )
+        open("notebook_utils.py", "w").write(r.text)
+    
     from notebook_utils import download_file, device_widget
+    
+    # Read more about telemetry collection at https://github.com/openvinotoolkit/openvino_notebooks?tab=readme-ov-file#-telemetry
+    from notebook_utils import collect_telemetry
+    
+    collect_telemetry("3D-segmentation-point-clouds.ipynb")
 
 Prepare the Model
 -----------------
@@ -92,12 +98,14 @@ find more point clouds examples
     # Set the data and model directories, model source URL and model filename
     MODEL_DIR = Path("model")
     MODEL_DIR.mkdir(exist_ok=True)
-    download_file(
-        "https://storage.googleapis.com/ailia-models/pointnet_pytorch/chair_100.onnx",
-        directory=Path(MODEL_DIR),
-        show_progress=False,
-    )
     onnx_model_path = MODEL_DIR / "chair_100.onnx"
+    
+    if not onnx_model_path.exists():
+        download_file(
+            "https://storage.googleapis.com/ailia-models/pointnet_pytorch/chair_100.onnx",
+            directory=Path(MODEL_DIR),
+            show_progress=False,
+        )
 
 Convert the ONNX model to OpenVINO IR. An OpenVINO IR (Intermediate
 Representation) model consists of an ``.xml`` file, containing
@@ -108,14 +116,14 @@ function returns an OpenVINO model ready to load on a device and start
 making predictions. We can save it on a disk for next usage with
 ``ov.save_model``. For more information about model conversion Python
 API, see this
-`page <https://docs.openvino.ai/2025/openvino-workflow/model-preparation.html>`__.
+`page <https://docs.openvino.ai/2024/openvino-workflow/model-preparation.html>`__.
 
 .. code:: ipython3
 
     ir_model_xml = onnx_model_path.with_suffix(".xml")
-
+    
     core = ov.Core()
-
+    
     if not ir_model_xml.exists():
         # Convert model to OpenVINO Model
         model = ov.convert_model(onnx_model_path)
@@ -135,37 +143,37 @@ Data Processing Module
     def load_data(point_file: Union[str, Path]):
         """
         Load the point cloud data and convert it to ndarray
-
+    
         Parameters:
             point_file: string, path of .pts data
         Returns:
            point_set: point clound represented in np.array format
         """
-
+    
         point_set = np.loadtxt(point_file).astype(np.float32)
-
+    
         # normailization
         point_set = point_set - np.expand_dims(np.mean(point_set, axis=0), 0)  # center
         dist = np.max(np.sqrt(np.sum(point_set**2, axis=1)), 0)
         point_set = point_set / dist  # scale
-
+    
         return point_set
-
-
+    
+    
     def visualize(point_set: np.ndarray):
         """
         Create a 3D view for data visualization
-
+    
         Parameters:
             point_set: np.ndarray, the coordinate data in X Y Z format
         """
-
+    
         fig = plt.figure(dpi=192, figsize=(4, 4))
         ax = fig.add_subplot(111, projection="3d")
         X = point_set[:, 0]
         Y = point_set[:, 2]
         Z = point_set[:, 1]
-
+    
         # Scale the view of each axis to adapt to the coordinate data distribution
         max_range = np.array([X.max() - X.min(), Y.max() - Y.min(), Z.max() - Z.min()]).max() * 0.5
         mid_x = (X.max() + X.min()) * 0.5
@@ -174,12 +182,12 @@ Data Processing Module
         ax.set_xlim(mid_x - max_range, mid_x + max_range)
         ax.set_ylim(mid_y - max_range, mid_y + max_range)
         ax.set_zlim(mid_z - max_range, mid_z + max_range)
-
+    
         plt.tick_params(labelsize=5)
         ax.set_xlabel("X", fontsize=10)
         ax.set_ylabel("Y", fontsize=10)
         ax.set_zlabel("Z", fontsize=10)
-
+    
         return ax
 
 Visualize the original 3D data
@@ -195,11 +203,14 @@ chair for example.
 .. code:: ipython3
 
     # Download data from the openvino_notebooks storage
-    point_data = download_file(
-        "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/pts/chair.pts",
-        directory="data",
-    )
-
+    point_data_path = Path("data") / "chair.pts"
+    
+    if not point_data_path.exists():
+        point_data = download_file(
+            "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/pts/chair.pts",
+            directory="data",
+        )
+    
     points = load_data(str(point_data))
     X = points[:, 0]
     Y = points[:, 2]
@@ -219,7 +230,7 @@ chair for example.
 
 .. parsed-literal::
 
-    /tmp/ipykernel_2157242/2434168836.py:12: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
+    /tmp/ipykernel_3273469/2331834230.py:15: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
       ax.scatter3D(X, Y, Z, s=5, cmap="jet", marker="o", label="chair")
 
 
@@ -242,11 +253,11 @@ each input point.
 
     # Parts of a chair
     classes = ["back", "seat", "leg", "arm"]
-
+    
     # Preprocess the input data
     point = points.transpose(1, 0)
     point = np.expand_dims(point, axis=0)
-
+    
     # Print info about model input and output shape
     print(f"input shape: {model.input(0).partial_shape}")
     print(f"output shape: {model.output(0).partial_shape}")
@@ -268,7 +279,7 @@ select device from dropdown list for running inference using OpenVINO
 .. code:: ipython3
 
     device = device_widget()
-
+    
     device
 
 
@@ -286,7 +297,7 @@ select device from dropdown list for running inference using OpenVINO
     compiled_model = core.compile_model(model=model, device_name=device.value)
     output_layer = compiled_model.output(0)
     result = compiled_model([point])[output_layer]
-
+    
     # Find the label map for all points of chair with highest confidence
     pred = np.argmax(result[0], axis=1)
     ax = visualize(point)
@@ -302,18 +313,18 @@ select device from dropdown list for running inference using OpenVINO
         XCur = np.array(XCur)
         YCur = np.array(YCur)
         ZCur = np.array(ZCur)
-
+    
         # add current point of the part
         ax.scatter(XCur, YCur, ZCur, s=5, cmap="jet", marker="o", label=classes[i])
-
+    
     ax.set_title("3D Segmentation Visualization")
     plt.legend(loc="upper right", fontsize=8)
     plt.show()
 
 
 .. parsed-literal::
 
-    /tmp/ipykernel_2157242/2804603389.py:23: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
+    /tmp/ipykernel_3273469/2804603389.py:23: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
       ax.scatter(XCur, YCur, ZCur, s=5, cmap="jet", marker="o", label=classes[i])
 
 

diff --git a/...oint-clouds-with-output_files/3D-segmentation-point-clouds-with-output_11_1.png b/...oint-clouds-with-output_files/3D-segmentation-point-clouds-with-output_11_1.png
diff --git a/docs/notebooks/action-recognition-webcam-with-output.rst b/docs/notebooks/action-recognition-webcam-with-output.rst
@@ -99,11 +99,17 @@ Imports
     # Fetch `notebook_utils` module
     import requests
     
-    r = requests.get(
-        url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py",
-    )
-    open("notebook_utils.py", "w").write(r.text)
+    if not Path("notebook_utils.py").exists():
+        r = requests.get(
+            url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py",
+        )
+        open("notebook_utils.py", "w").write(r.text)
     import notebook_utils as utils
+    
+    # Read more about telemetry collection at https://github.com/openvinotoolkit/openvino_notebooks?tab=readme-ov-file#-telemetry
+    from notebook_utils import collect_telemetry
+    
+    collect_telemetry("action-recognition-webcam.ipynb")
 
 The models
 ----------
@@ -178,10 +184,12 @@ also provides the text file embedded into this notebook.
 .. code:: ipython3
 
     # Download the text from the openvino_notebooks storage
-    vocab_file_path = utils.download_file(
-        "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/text/kinetics.txt",
-        directory="data",
-    )
+    
+    if not (Path("data") / "kinetics.txt").exists():
+        vocab_file_path = utils.download_file(
+            "https://storage.openvinotoolkit.org/repositories/openvino_notebooks/data/data/text/kinetics.txt",
+            directory="data",
+        )
     
     with vocab_file_path.open(mode="r") as f:
         labels = [line.strip() for line in f]
@@ -676,18 +684,27 @@ multi-camera systems).
     USE_WEBCAM = False
     
     cam_id = 0
-    video_file = "https://archive.org/serve/ISSVideoResourceLifeOnStation720p/ISS%20Video%20Resource_LifeOnStation_720p.mp4"
+    video_url = "https://archive.org/serve/ISSVideoResourceLifeOnStation720p/ISS%20Video%20Resource_LifeOnStation_720p.mp4"
+    video_file = Path("ISS%20Video%20Resource_LifeOnStation_720p.mp4")
+    
+    if not USE_WEBCAM and video_file.exists():
+        utils.download_file(video_url, filename=video_file.name)
     
     source = cam_id if USE_WEBCAM else video_file
     additional_options = {"skip_first_frames": 600, "flip": False} if not USE_WEBCAM else {"flip": True}
     run_action_recognition(source=source, use_popup=False, **additional_options)
 
 
+.. parsed-literal::
 
-.. image:: action-recognition-webcam-with-output_files/action-recognition-webcam-with-output_22_0.png
+    Cannot open  ISS%20Video%20Resource_LifeOnStation_720p.mp4
 
 
 .. parsed-literal::
 
-    Source ended
+    [ WARN:[email protected]] global cap.cpp:175 open VIDEOIO(CV_IMAGES): raised OpenCV exception:
+    
+    OpenCV(4.11.0) /io/opencv/modules/videoio/src/cap_images.cpp:237: error: (-5:Bad argument) CAP_IMAGES: error, expected '0?[1-9][du]' pattern, got: ISS%20Video%20Resource_LifeOnStation_720p.mp4 in function 'icvExtractPattern'
+    
+    
 
diff --git a/...gnition-webcam-with-output_files/action-recognition-webcam-with-output_22_0.png b/...gnition-webcam-with-output_files/action-recognition-webcam-with-output_22_0.png
diff --git a/docs/notebooks/all_notebooks_paths.txt b/docs/notebooks/all_notebooks_paths.txt
@@ -12,9 +12,9 @@ notebooks/clip-language-saliency-map/clip-language-saliency-map.ipynb
 notebooks/clip-zero-shot-image-classification/clip-zero-shot-classification.ipynb
 notebooks/controlnet-stable-diffusion/controlnet-stable-diffusion.ipynb
 notebooks/convert-to-openvino/convert-to-openvino.ipynb
-notebooks/cross-lingual-books-alignment/cross-lingual-books-alignment.ipynb
 notebooks/ct-segmentation-quantize/ct-segmentation-quantize-nncf.ipynb
 notebooks/ddcolor-image-colorization/ddcolor-image-colorization.ipynb
+notebooks/deepseek-r1/deepseek-r1.ipynb
 notebooks/depth-anything/depth-anything.ipynb
 notebooks/depth-anything/depth-anything-v2.ipynb
 notebooks/detectron2-to-openvino/detectron2-to-openvino.ipynb
@@ -42,6 +42,8 @@ notebooks/hello-world/hello-world.ipynb
 notebooks/hugging-face-hub/hugging-face-hub.ipynb
 notebooks/hunyuan-dit-image-generation/hunyuan-dit-image-generation.ipynb
 notebooks/image-classification-quantization/image-classification-quantization.ipynb
+notebooks/image-to-image-genai/image-to-image-genai.ipynb
+notebooks/inpainting-genai/inpainting-genai.ipynb
 notebooks/instant-id/instant-id.ipynb
 notebooks/instruct-pix2pix-image-editing/instruct-pix2pix-image-editing.ipynb
 notebooks/internvl2/internvl2.ipynb
@@ -63,9 +65,11 @@ notebooks/llm-agent-react/llm-agent-react-langchain.ipynb
 notebooks/llm-chatbot/llm-chatbot-generate-api.ipynb
 notebooks/llm-chatbot/llm-chatbot.ipynb
 notebooks/llm-question-answering/llm-question-answering.ipynb
+notebooks/llm-rag-langchain/llm-rag-langchain-genai.ipynb
 notebooks/llm-rag-langchain/llm-rag-langchain.ipynb
 notebooks/llm-rag-llamaindex/llm-rag-llamaindex.ipynb
 notebooks/localai/localai.ipynb
+notebooks/ltx-video/ltx-video.ipynb
 notebooks/magika-content-type-recognition/magika-content-type-recognition.ipynb
 notebooks/meter-reader/meter-reader.ipynb
 notebooks/minicpm-v-multimodal-chatbot/minicpm-v-multimodal-chatbot.ipynb
@@ -75,11 +79,13 @@ notebooks/mobileclip-video-search/mobileclip-video-search.ipynb
 notebooks/modelscope-to-openvino/modelscope-to-openvino.ipynb
 notebooks/model-server/model-server.ipynb
 notebooks/multilora-image-generation/multilora-image-generation.ipynb
+notebooks/multimodal-rag/multimodal-rag-llamaindex.ipynb
 notebooks/music-generation/music-generation.ipynb
 notebooks/named-entity-recognition/named-entity-recognition.ipynb
 notebooks/nano-llava-multimodal-chatbot/nano-llava-multimodal-chatbot.ipynb
 notebooks/nuextract-structure-extraction/nuextract-structure-extraction.ipynb
 notebooks/object-detection-webcam/object-detection.ipynb
+notebooks/omnigen/omnigen.ipynb
 notebooks/omniparser/omniparser.ipynb
 notebooks/oneformer-segmentation/oneformer-segmentation.ipynb
 notebooks/openvino-api/openvino-api.ipynb
@@ -114,6 +120,7 @@ notebooks/rmbg-background-removal/rmbg-background-removal.ipynb
 notebooks/s3d-mil-nce-text-to-video-retrieval/s3d-mil-nce-text-to-video-retrieval.ipynb
 notebooks/sam2-image-segmentation/segment-anything-2-image.ipynb
 notebooks/sam2-video-segmentation/segment-anything-2-video.ipynb
+notebooks/sana-image-generation/sana-image-generation.ipynb
 notebooks/sdxl-turbo/sdxl-turbo.ipynb
 notebooks/segment-anything/segment-anything.ipynb
 notebooks/siglip-zero-shot-image-classification/siglip-zero-shot-image-classification.ipynb