Epic Rabbit
Core detection engine for Armanid — by Epic Rabbit
Epic Rabbit is the high-performance engine that powers the Armanid object detection library. It provides a complete, standalone computer vision backend with no external detection framework dependencies.
Installation
pip install epic-rabbit
pip install armanid
Quick Start
from armanid import Armanid
model = Armanid("armanid-nano")
results = model.detect("image.jpg")
results[0].show()
Webcam Detection
from armanid import Armanid
from armanid.utils import run_webcam
model = Armanid("armanid-nano")
run_webcam(model, cam_index=0, conf=0.25)
Available Models
| Model | Size | Speed |
|---|---|---|
| armanid-nano | ~6MB | Fastest |
| armanid-small | ~22MB | Fast |
| armanid-medium | ~50MB | Balanced |
| armanid-large | ~84MB | Accurate |
| armanid-xlarge | ~131MB | Most Accurate |
Features
- Object Detection
- Instance Segmentation
- Pose Estimation
- Object Tracking
- Train on custom datasets
- Export to ONNX, TFLite, CoreML
License
MIT License — Epic Rabbit
Metadata
Release files for epic-rabbit 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| epic_rabbit-1.0.1.tar.gz | 627.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| epic_rabbit-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.4 MB
Release files / epic_rabbit-1.0.1.tar.gz
| Download URL | epic_rabbit-1.0.1.tar.gz |
|---|---|
| Size | 627.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/6.2.0 CPython/3.11.8
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Release files / epic_rabbit-1.0.1-py3-none-any.whl
| Download URL | epic_rabbit-1.0.1-py3-none-any.whl |
|---|---|
| Size | 758.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.8
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