Image Classification
Transformers
Safetensors
swinv2
LADI
Aerial Imagery
Disaster Response
Emergency Management
Instructions to use MITLL/LADI-v2-classifier-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MITLL/LADI-v2-classifier-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MITLL/LADI-v2-classifier-large") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("MITLL/LADI-v2-classifier-large") model = AutoModelForImageClassification.from_pretrained("MITLL/LADI-v2-classifier-large") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -105,10 +105,16 @@ print(labels)
|
|
| 105 |
**BibTeX:**
|
| 106 |
|
| 107 |
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 108 |
```
|
| 109 |
|
| 110 |
-
Paper forthcoming - watch this space for details
|
| 111 |
-
|
| 112 |
---
|
| 113 |
|
| 114 |
- **Developed by:** Jeff Liu, Sam Scheele
|
|
|
|
| 105 |
**BibTeX:**
|
| 106 |
|
| 107 |
```
|
| 108 |
+
@misc{ladi_v2,
|
| 109 |
+
title={LADI v2: Multi-label Dataset and Classifiers for Low-Altitude Disaster Imagery},
|
| 110 |
+
author={Samuel Scheele and Katherine Picchione and Jeffrey Liu},
|
| 111 |
+
year={2024},
|
| 112 |
+
eprint={2406.02780},
|
| 113 |
+
archivePrefix={arXiv},
|
| 114 |
+
primaryClass={cs.CV}
|
| 115 |
+
}
|
| 116 |
```
|
| 117 |
|
|
|
|
|
|
|
| 118 |
---
|
| 119 |
|
| 120 |
- **Developed by:** Jeff Liu, Sam Scheele
|