[DOCS] Updating Interactive Tutorials (#26947)

Updating the notebooks section in docs.

Author: sgolebiewski-intel

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/20240923220849/dist/rst_files/"
+artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20241007220823/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="

docs/notebooks/3D-pose-estimation-with-output.rst

@@ -227,7 +227,7 @@ chair for example.
 
 .. parsed-literal::
 
-    /tmp/ipykernel_60730/2434168836.py:12: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
+    /tmp/ipykernel_59833/2434168836.py:12: 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")
 
 
@@ -321,7 +321,7 @@ select device from dropdown list for running inference using OpenVINO
 
 .. parsed-literal::
 
-    /tmp/ipykernel_60730/2804603389.py:23: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
+    /tmp/ipykernel_59833/2804603389.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])
 
 

docs/notebooks/3D-segmentation-point-clouds-with-output.rst

@@ -68,6 +68,7 @@ notebooks/llm-rag-llamaindex/llm-rag-llamaindex.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
+notebooks/mllama-3.2/mllama-3.2.ipynb
 notebooks/mms-massively-multilingual-speech/mms-massively-multilingual-speech.ipynb
 notebooks/mobileclip-video-search/mobileclip-video-search.ipynb
 notebooks/mobilevlm-language-assistant/mobilevlm-language-assistant.ipynb
@@ -93,6 +94,7 @@ notebooks/phi-3-vision/phi-3-vision.ipynb
 notebooks/photo-maker/photo-maker.ipynb
 notebooks/pix2struct-docvqa/pix2struct-docvqa.ipynb
 notebooks/pixart/pixart.ipynb
+notebooks/pixtral/pixtral.ipynb
 notebooks/pose-estimation-webcam/pose-estimation.ipynb
 notebooks/pytorch-post-training-quantization-nncf/pytorch-post-training-quantization-nncf.ipynb
 notebooks/pytorch-quantization-aware-training/pytorch-quantization-aware-training.ipynb
@@ -107,6 +109,8 @@ notebooks/qwen2-vl/qwen2-vl.ipynb
 notebooks/riffusion-text-to-music/riffusion-text-to-music.ipynb
 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/sdxl-turbo/sdxl-turbo.ipynb
 notebooks/segment-anything/segment-anything.ipynb
 notebooks/siglip-zero-shot-image-classification/siglip-zero-shot-image-classification.ipynb
@@ -149,9 +153,14 @@ notebooks/typo-detector/typo-detector.ipynb
 notebooks/vehicle-detection-and-recognition/vehicle-detection-and-recognition.ipynb
 notebooks/vision-background-removal/vision-background-removal.ipynb
 notebooks/vision-monodepth/vision-monodepth.ipynb
+notebooks/wav2lip/wav2lip.ipynb
+notebooks/whisper-asr-genai/whisper-asr-genai.ipynb
 notebooks/whisper-subtitles-generation/whisper-subtitles-generation.ipynb
 notebooks/wuerstchen-image-generation/wuerstchen-image-generation.ipynb
 notebooks/yolov10-optimization/yolov10-optimization.ipynb
+notebooks/yolov11-optimization/yolov11-instance-segmentation.ipynb
+notebooks/yolov11-optimization/yolov11-keypoint-detection.ipynb
+notebooks/yolov11-optimization/yolov11-object-detection.ipynb
 notebooks/yolov8-optimization/yolov8-instance-segmentation.ipynb
 notebooks/yolov8-optimization/yolov8-keypoint-detection.ipynb
 notebooks/yolov8-optimization/yolov8-obb.ipynb

docs/notebooks/action-recognition-webcam-with-output_files/action-recognition-webcam-with-output_22_0.png

@@ -355,7 +355,7 @@ Test performance in Sync Mode
 .. parsed-literal::
 
     Source ended
-    average throuput in sync mode: 62.96 fps
+    average throuput in sync mode: 63.95 fps
 
 
 Async Mode
@@ -494,7 +494,7 @@ Test the performance in Async Mode
 .. parsed-literal::
 
     Source ended
-    average throuput in async mode: 105.40 fps
+    average throuput in async mode: 108.46 fps
 
 
 Compare the performance
@@ -637,5 +637,5 @@ Test the performance with ``AsyncInferQueue``
 
 .. parsed-literal::
 
-    average throughput in async mode with async infer queue: 140.92 fps
+    average throughput in async mode with async infer queue: 144.01 fps
 

docs/notebooks/all_notebooks_paths.txt

@@ -200,16 +200,16 @@ By default, ``compile_model`` API will select **AUTO** as
 
 .. parsed-literal::
 
-    [23:33:07.3079]I[plugin.cpp:421][AUTO] device:CPU, config:LOG_LEVEL=LOG_INFO
-    [23:33:07.3079]I[plugin.cpp:421][AUTO] device:CPU, config:PERFORMANCE_HINT=LATENCY
-    [23:33:07.3079]I[plugin.cpp:421][AUTO] device:CPU, config:PERFORMANCE_HINT_NUM_REQUESTS=0
-    [23:33:07.3079]I[plugin.cpp:421][AUTO] device:CPU, config:PERF_COUNT=NO
-    [23:33:07.3079]I[plugin.cpp:426][AUTO] device:CPU, priority:0
-    [23:33:07.3079]I[schedule.cpp:17][AUTO] scheduler starting
-    [23:33:07.3080]I[auto_schedule.cpp:181][AUTO] select device:CPU
-    [23:33:07.4176]I[auto_schedule.cpp:346][AUTO] Device: [CPU]: Compile model took 109.630635 ms
-    [23:33:07.4178]I[auto_schedule.cpp:112][AUTO] device:CPU compiling model finished
-    [23:33:07.4178]I[plugin.cpp:454][AUTO] underlying hardware does not support hardware context
+    [23:32:04.6480]I[plugin.cpp:421][AUTO] device:CPU, config:LOG_LEVEL=LOG_INFO
+    [23:32:04.6480]I[plugin.cpp:421][AUTO] device:CPU, config:PERFORMANCE_HINT=LATENCY
+    [23:32:04.6480]I[plugin.cpp:421][AUTO] device:CPU, config:PERFORMANCE_HINT_NUM_REQUESTS=0
+    [23:32:04.6480]I[plugin.cpp:421][AUTO] device:CPU, config:PERF_COUNT=NO
+    [23:32:04.6480]I[plugin.cpp:426][AUTO] device:CPU, priority:0
+    [23:32:04.6481]I[schedule.cpp:17][AUTO] scheduler starting
+    [23:32:04.6481]I[auto_schedule.cpp:181][AUTO] select device:CPU
+    [23:32:04.7787]I[auto_schedule.cpp:346][AUTO] Device: [CPU]: Compile model took 130.622171 ms
+    [23:32:04.7789]I[auto_schedule.cpp:112][AUTO] device:CPU compiling model finished
+    [23:32:04.7790]I[plugin.cpp:454][AUTO] underlying hardware does not support hardware context
     Successfully compiled model without a device_name.
 
 
@@ -222,8 +222,8 @@ By default, ``compile_model`` API will select **AUTO** as
 
 .. parsed-literal::
 
-    [23:33:07.4229]I[schedule.cpp:308][AUTO] scheduler ending
     Deleted compiled_model
+    [23:32:04.7847]I[schedule.cpp:308][AUTO] scheduler ending
 
 
 Explicitly pass AUTO as device_name to Core::compile_model API
@@ -556,12 +556,12 @@ Loop for inference and update the FPS/Latency every
 
     Compiling Model for AUTO device with THROUGHPUT hint
     Start inference,  6 groups of FPS/latency will be measured over  10s intervals
-    throughput:  184.55fps, latency:  31.14ms, time interval: 10.00s
-    throughput:  183.88fps, latency:  31.86ms, time interval: 10.01s
-    throughput:  182.58fps, latency:  32.11ms, time interval: 10.00s
-    throughput:  183.39fps, latency:  31.91ms, time interval: 10.00s
-    throughput:  183.80fps, latency:  31.85ms, time interval: 10.01s
-    throughput:  183.74fps, latency:  31.86ms, time interval: 10.00s
+    throughput:  183.87fps, latency:  31.26ms, time interval: 10.01s
+    throughput:  184.60fps, latency:  31.70ms, time interval: 10.00s
+    throughput:  183.24fps, latency:  31.93ms, time interval: 10.01s
+    throughput:  184.05fps, latency:  31.75ms, time interval: 10.00s
+    throughput:  184.40fps, latency:  31.77ms, time interval: 10.00s
+    throughput:  178.41fps, latency:  32.83ms, time interval: 10.02s
     Done
 
 
@@ -607,12 +607,12 @@ Loop for inference and update the FPS/Latency for each
 
     Compiling Model for AUTO Device with LATENCY hint
     Start inference,  6 groups fps/latency will be out with  10s interval
-    throughput:  139.69fps, latency:  6.62ms, time interval: 10.00s
-    throughput:  141.89fps, latency:  6.61ms, time interval: 10.00s
-    throughput:  142.44fps, latency:  6.64ms, time interval: 10.00s
-    throughput:  142.12fps, latency:  6.61ms, time interval: 10.01s
-    throughput:  142.13fps, latency:  6.60ms, time interval: 10.00s
-    throughput:  141.86fps, latency:  6.66ms, time interval: 10.00s
+    throughput:  140.52fps, latency:  6.62ms, time interval: 10.01s
+    throughput:  142.84fps, latency:  6.60ms, time interval: 10.00s
+    throughput:  142.14fps, latency:  6.60ms, time interval: 10.00s
+    throughput:  142.63fps, latency:  6.60ms, time interval: 10.00s
+    throughput:  143.11fps, latency:  6.61ms, time interval: 10.01s
+    throughput:  132.99fps, latency:  7.13ms, time interval: 10.01s
     Done
 
 

docs/notebooks/amused-lightweight-text-to-image-with-output.rst

@@ -736,7 +736,6 @@ up of the dynamic quantized models.
 Interactive demo
 ----------------
 
-
 Now, it is your turn! You can provide your own image and comma-separated
 list of labels for zero-shot classification.
 

docs/notebooks/animate-anyone-with-output.rst

@@ -46,7 +46,7 @@ Guide <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.
 
 .. parsed-literal::
 
-    Requirement already satisfied: pip in /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-780/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (24.2)
+    Requirement already satisfied: pip in /opt/home/k8sworker/ci-ai/cibuilds/jobs/ov-notebook/jobs/OVNotebookOps/builds/790/archive/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages (24.2)
     Note: you may need to restart the kernel to use updated packages.
     Note: you may need to restart the kernel to use updated packages.
 
@@ -192,13 +192,11 @@ NLP model from Hugging Face and export it in ONNX format:
 
 .. parsed-literal::
 
-    2024-09-23 23:53:52.285454: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
-    2024-09-23 23:53:52.319037: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+    2024-10-07 23:35:08.862114: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
+    2024-10-07 23:35:08.907564: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
     To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-    2024-09-23 23:53:52.844892: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-780/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
-      warnings.warn(
-    /opt/home/k8sworker/ci-ai/cibuilds/ov-notebook/OVNotebookOps-780/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:215: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
+    2024-10-07 23:35:09.444317: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+    /opt/home/k8sworker/ci-ai/cibuilds/jobs/ov-notebook/jobs/OVNotebookOps/builds/790/archive/.workspace/scm/ov-notebook/.venv/lib/python3.8/site-packages/transformers/models/distilbert/modeling_distilbert.py:215: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
       mask, torch.tensor(torch.finfo(scores.dtype).min)
 
 
@@ -675,7 +673,7 @@ frameworks conversion guides.
 
 .. parsed-literal::
 
-    2024-09-23 23:54:09.260359: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1956] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
+    2024-10-07 23:35:26.468759: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1956] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
     Skipping registering GPU devices...
 
 

docs/notebooks/async-api-with-output.rst

@@ -192,7 +192,7 @@ And print results
 
     Predicted Class: 281
     Predicted Label: n02123045 tabby, tabby cat
-    Predicted Probability: 0.5351971983909607
+    Predicted Probability: 0.4793865978717804
 
 
 Convert the model to OpenVINO Intermediate representation format