NeuroModFlowNet.ONNX Prepared Models
Prepared ONNX model artifacts for NeuroModFlowNet.ONNX.
These files are generated artifacts. They are not covered by the Apache-2.0 license of the NeuroModFlowNet.ONNX source code repository unless explicitly stated.
See models.manifest.json for file paths, sizes and SHA256 hashes.
Model Licenses
This repository contains prepared artifacts from different model families. The Hugging Face metadata uses license: other because a single repository-level license value would be misleading.
YOLO-Derived Models
YOLO weights and YOLO-derived prepared artifacts are provided under AGPL-3.0, consistent with the Ultralytics YOLO licensing terms.
This applies to YOLO-family folders such as:
yolo26n/;yolo26n-cls/;yolo26n-obb/;yolo26n-pose/;yolo26n-seg/;- other artifacts exported from or derived from Ultralytics YOLO models.
Users are responsible for ensuring that their YOLO model use complies with the licenses of:
- Ultralytics YOLO;
- the base/pretrained model, if any;
- the training dataset;
- any deployment/runtime libraries.
PaddleOCR Models
PaddleOCR / PP-OCR artifacts are provided under Apache-2.0, consistent with the PaddleOCR project license.
The PaddleOCR artifacts in this repository are prepared ONNX files for NeuroModFlowNet.ONNX demos. The clean detection models are sourced from the ONNX exports in monkt/paddleocr-onnx, which describe the original models as PaddleOCR / PP-OCR models from the PaddlePaddle team and mark the ONNX exports as Apache-2.0.
Current PaddleOCR paths include:
paddleocr/detection/v3/det.onnx;paddleocr/detection/v3/det_bytebgr.onnx;paddleocr/detection/v5/det.onnx;paddleocr/detection/v5/det_bytebgr.onnx.
Source references:
- PaddleOCR project: https://github.com/PaddlePaddle/PaddleOCR
- PaddleOCR / PP-OCR ONNX source used by the preparation scripts: https://huggingface.co/monkt/paddleocr-onnx
Prepared Variants
Files with embedded preprocessing heads, for example *_bytebgr.onnx, are modified variants prepared for lower-overhead NeuroModFlowNet.ONNX input pipelines. They keep the license obligations of the source model family they were derived from.
Warranty
The author provides these artifacts "as is", without warranty. Users are responsible for checking that their use complies with all applicable model, dataset, export, and deployment/runtime licenses.