Image Classification
LiteRT
LiteRT
ONNX
English
vision
botany
western-australia
dinov3
mixture-of-experts
adaround
fp8
int8
android
biodiversity
flora
Instructions to use thenukegun10x/PLantDetect-WA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use thenukegun10x/PLantDetect-WA with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Add CLI guide and quickstart instructions to Model Card
Browse files
README.md
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## 3.
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```python
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import torch
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import numpy as np
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---
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## 3. 🖥️ Official Plant CLI Guide
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### 1. Installation
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```bash
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git clone https://huggingface.co/thenukegun10x/wa-plant-identifier
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cd wa-plant-identifier
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pip install -r requirements.txt
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```
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### 2. Identify a Plant from a Single Photo
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```bash
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python plant_cli.py identify wild_flower.jpg --topk 5
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```
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### 3. Multi-View Botanical Identification (Flower + Leaf + Habit)
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Achieves **97%–99% certainty** by averaging logits across complementary plant angles:
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```bash
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python plant_cli.py identify flower.jpg leaf.jpg habit.jpg fruit.jpg
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```
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### 4. Batch Directory Identification
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Recursively process an entire field folder and export results to CSV:
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```bash
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python plant_cli.py batch --dir field_photos/ --pattern "*.jpg" --recursive --out results.csv
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```
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---
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## 4. Python Quickstart Examples
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### Multi-View Inference with PyTorch / Safetensors
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```python
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import torch
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import numpy as np
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