ML Node Catalog

Load Trained ML Model from Path

2 in2 outSecurity 3/10

Load Model (Binary)

Load Trained ML Model from Path using fast binary format (Fory)

2 in2 outSecurity 3/10

Predict

Predict with Machine Learning Model

4 in1 outSecurity 4/10

Prediction Class/Label

Extract class_idx and label from predictions.

1 in2 outSecurity 10/10

Save Model

Save Trained ML Model to Path

3 in1 outSecurity 3/10

Save Model (Binary)

Save Trained ML Model to Path using fast binary format (Fory)

3 in1 outSecurity 3/10

Teachable Machine

Image classification using Teachable Machine models.

6 in2 outSecurity 10/10

Train Classifier (Decision Tree)

AI/ML/Classification

Fit/Train a Decision Tree classifier. Native multi-class support with interpretable rules.

4 in2 outSecurity 4/10

Train Classifier (Naive Bayes)

AI/ML/Classification

Fit/Train a Gaussian Naive Bayes classifier. Native multi-class support - no need for One-vs-All.

2 in2 outSecurity 4/10

Train Classifier (SVM)

AI/ML/Classification

Fit/Train Support Vector Machines (SVM) for Multi-Class Classification

2 in2 outSecurity 4/10

Train Clustering (DBSCAN)

AI/ML/Clustering

Fit/Train DBSCAN Density-Based Clustering

4 in3 outSecurity 4/10

Train Clustering (KMeans)

AI/ML/Clustering

Fit/Train KMeans Clustering

3 in2 outSecurity 4/10

K-Fold Split

Generate K train/test splits for cross-validation. Each fold uses (K-1)/K data for training and 1/K for validation.

6 in4 outSecurity 4/10

Sample Dataset

Random sample N records or a ratio from a dataset

5 in2 outSecurity 4/10

Shuffle Dataset

Shuffle dataset rows randomly

3 in1 outSecurity 4/10

Split Dataset

Split a dataset into training and testing subsets

5 in1 outSecurity 4/10

Stratified Split

Split a dataset into training and testing subsets while maintaining class distribution

6 in1 outSecurity 4/10

Accuracy

AI/ML/Metrics

Calculate classification accuracy by comparing predictions to actual values

4 in2 outSecurity 2/10

Confusion Matrix

AI/ML/Metrics

Build confusion matrix and calculate precision, recall, and F1 score

4 in2 outSecurity 2/10

Regression Metrics

AI/ML/Metrics

Calculate MSE, RMSE, MAE, and R² for regression predictions

4 in2 outSecurity 2/10

Get Centroids

AI/ML/Model Info

Extract cluster centroids from a trained KMeans model

2 in2 outSecurity 0/10

Get Coefficients

AI/ML/Model Info

Extract coefficients and intercept from a trained Linear Regression model

2 in2 outSecurity 0/10

Model Info

AI/ML/Model Info

Get general information about any ML model

2 in3 outSecurity 10/10

Extract Keypoint

Extract a specific keypoint from a pose by index or name

2 in5 outSecurity 10/10

Feature Extraction

Extract feature vectors from images using ONNX models

4 in3 outSecurity 10/10

Feature Similarity

Compare two feature vectors using cosine similarity or L2 distance

2 in2 outSecurity 10/10

Image Classification

Image Classification with ONNX-Models. Download models from: MobileNetV2 (https://github.com/onnx/models/tree/main/validated/vision/classification/mobilenet), SqueezeNet (https://github.com/onnx/models/tree/main/validated/vision/classification/squeezenet), ResNet (https://github.com/onnx/models/tree/main/validated/vision/classification/resnet), EfficientNet (https://github.com/onnx/models/tree/main/validated/vision/classification/efficientnet-lite4)

7 in2 outSecurity 10/10

Load ONNX

Load ONNX Model from Path

2 in4 outSecurity 10/10

Model Info

Get ONNX model metadata (inputs, outputs, shapes)

2 in4 outSecurity 10/10

Object Detection

Object Detection in Images with ONNX-Models. Download models from: TinyYOLOv2 (https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/tiny-yolov2), YOLO (https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation), SSD-MobileNet (https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/ssd-mobilenetv1)

6 in2 outSecurity 10/10

Pose Estimation

Detect human poses and keypoints using ONNX models. Download models from: YOLOv8-Pose (https://docs.ultralytics.com/models/yolov8/), MoveNet (https://tfhub.dev/google/movenet/), HRNet (https://github.com/OAID/TengineKit)

5 in2 outSecurity 10/10

Semantic Segmentation

Segment images into semantic classes using ONNX models. Download models from: DeepLabV3 (https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/duc), FCN (https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/fcn)

Session Info

Get information about a loaded ONNX session

1 in4 outSecurity 10/10

Unload ONNX

Release ONNX model from cache to free memory

2 in2 outSecurity 10/10

Audio to Mel Spectrogram

Convert audio to mel spectrogram for speech models

Load Audio

Load audio file for processing

2 in4 outSecurity 10/10

Resample Audio

Resample audio to target sample rate

Trim Audio

Trim audio to speech segments from VAD

Voice Activity Detection

Detect speech segments in audio. Download Silero VAD model from: https://github.com/snakers4/silero-vad/raw/master/src/silero_vad/data/silero_vad.onnx

6 in3 outSecurity 10/10

Batch Image Inference

AI/ML/ONNX/Batch

Run ONNX inference on multiple images in batches

6 in3 outSecurity 10/10

Compare Faces

Compare two face embeddings for similarity

4 in4 outSecurity 10/10

Crop Faces

Crop detected faces from image

Face Detection

Detect faces in images. Download models from: UltraFace (https://github.com/onnx/models/tree/main/validated/vision/body_analysis/ultraface), RetinaFace (https://huggingface.co/arnabdhar/retinaface-onnx), SCRFD (https://huggingface.co/onnx-community/scrfd_10g_bnkps)

6 in3 outSecurity 10/10

Face Embedding

Extract face embedding for recognition. Download models from: ArcFace (https://huggingface.co/onnx-community/arcface_torch/tree/main), FaceNet (https://huggingface.co/rocca/facenet-onnx)

Named Entity Recognition

AI/ML/ONNX/NLP

Extract named entities (persons, organizations, locations, dates, etc.) from text using ONNX models. Supports BERT, RoBERTa, and other transformer-based NER models with automatic tokenization. Download models from: BERT-base-NER (https://huggingface.co/dslim/bert-base-NER), Multilingual NER (https://huggingface.co/Davlan/bert-base-multilingual-cased-ner-hrl), spaCy NER (https://huggingface.co/spacy). Download tokenizer.json from the same model repository.

8 in4 outSecurity 10/10

Crop Text Regions

AI/ML/ONNX/OCR

Crop detected text regions from image for recognition

Text Detection

AI/ML/ONNX/OCR

Detect text regions in images. Download models from: CRAFT (https://huggingface.co/quocanh34/craft_text_detection_onnx), DBNet (https://huggingface.co/Xenova/dbnet_resnet50_onnx), EAST (https://www.dropbox.com/s/r2ingd0l3zt8hxs/frozen_east_text_detection.tar.gz)

Text Recognition

AI/ML/ONNX/OCR

Recognize text from cropped text regions. Download models from: CRNN (https://huggingface.co/Xenova/crnn_onnx), TrOCR (https://huggingface.co/microsoft/trocr-base-printed), PaddleOCR (https://huggingface.co/aapot/paddleocr-onnx)

Colorize Depth

AI/ML/ONNX/Vision

Convert depth map to rainbow-colored visualization

2 in2 outSecurity 10/10

Depth Estimation

AI/ML/ONNX/Vision

Estimate depth from a single image using ONNX models. Download models from: MiDaS (https://github.com/isl-org/MiDaS/releases), DPT (https://huggingface.co/Intel/dpt-large/tree/main), Depth Anything (https://huggingface.co/depth-anything/Depth-Anything-V2-Small/tree/main)