Isarsoft Model Export Toolkit - Export models for Perception
Project description
Isarsoft Model Utility
A command-line utility for exporting object detection models to ONNX format for Isarsoft Perception, complete with metadata generation and optional packaging.
Features
- Convert PyTorch
.ptmodels from RFDETR to ONNX - Embed metadata: class labels, model description, company attribution
- Options to anonymize or georeference specific classes
- Support for custom input image sizes
- Generate a thumbnail for frontend display (optional)
- Package outputs into a ZIP archive (optional)
- Verbose logging for debugging and audit trails
Requirements
- Python 3.10 or later
Installation
# Create a conda environment (recommended)
conda create -n isarsoft-export python=3.10 -y
conda activate isarsoft-export
# Install the package
pip install isarsoft-model-utility
Usage
isarsoft-export --model <MODEL_PATH> \
--output <OUTPUT_DIR> \
--classes <CLASS_LIST>
--model-name <MODEL>
All flags and options are described below.
Required Arguments
| Flag | Shortcut | Description |
|---|---|---|
--model |
-m |
Path to model file (.pt) or use default for pretrained |
--output |
-o |
Directory where exported files will be saved |
--classes |
-c |
Comma-separated list of class names (e.g., person,car,bike) |
Optional Arguments
| Flag | Shortcut | Type | Default | Description |
|---|---|---|---|---|
--model-name |
-n |
String | rfdetr |
Model Name for the Frontend |
--description |
-d |
String | Object detection model |
Model description for metadata |
--company |
String | Generated |
Company name for metadata | |
--anonymize-classes |
String | None | Comma-separated class indices to anonymize (e.g., 0,1) |
|
--georeference-classes |
String | None | Comma-separated class indices to georeference (e.g., 2,3) |
|
--imgsz |
Integer | 560 |
Input image size for export | |
--thumbnail |
String | None | Location of thumbnail for Frontend | |
--no-zip |
Flag | Disabled | Skip creating zip package | |
--verbose |
-v |
Flag | Disabled | Enable verbose logging |
Examples
Basic export with class names:
isarsoft-export \
--model model.pt \
--output ./exported \
--classes person,car,bike
--model-name custom
Export with custom metadata and class options:
isarsoft-export \
--model model.pt \
--output ./exported \
--classes person,vehicle,animal \
--description "Multi-class detector" \
--company "MyCompany" \
--anonymize-classes 0 \
--georeference-classes 1,2 \
--model-name custom
Export with custom image size and thumbnail:
isarsoft-export \
--model model.pt \
--output ./exported \
--classes person \
--imgsz 728 \
--thumbnail ./thumbnail.svg \
--model-name custom
Exit Codes
0on successful export1on failure (errors are printed; use--verbosefor traceback)
Logging
Verbose mode (--verbose) outputs detailed logs to the console, including validation steps and stack traces on error.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file isarsoft_model_utility-0.1.0.tar.gz.
File metadata
- Download URL: isarsoft_model_utility-0.1.0.tar.gz
- Upload date:
- Size: 1.0 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.10.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
354dfa4e73bbe5626def5fd8ecf95827ea3213db49b6ef0e6184da5b7b2a2226
|
|
| MD5 |
b81eae0d3d131aaa571d4de1af721744
|
|
| BLAKE2b-256 |
fdb0023aa5c47b0aff2dac1c9ec21d64fcd53223d91af22f1070490d0cbf4eb9
|
File details
Details for the file isarsoft_model_utility-0.1.0-py3-none-any.whl.
File metadata
- Download URL: isarsoft_model_utility-0.1.0-py3-none-any.whl
- Upload date:
- Size: 1.0 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.10.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5b3679222738d3f71c372a33ea0edf473a0cd43de96dfa0f6e33f3dd6be0a72d
|
|
| MD5 |
a00580f04b1719d4a6297d886136c171
|
|
| BLAKE2b-256 |
86e200d3517e52ddc60c2ea6966c9f2f9b17a116883e8d18ed82403cc46c2414
|