Instructions to use JustFadjrin/batik-vit-model-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JustFadjrin/batik-vit-model-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JustFadjrin/batik-vit-model-classification") 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("JustFadjrin/batik-vit-model-classification") model = AutoModelForImageClassification.from_pretrained("JustFadjrin/batik-vit-model-classification") - Notebooks
- Google Colab
- Kaggle
| license: cc0-1.0 | |
| library_name: transformers | |
| pipeline_tag: image-classification | |
| tags: | |
| - image-classification | |
| - vision-transformer | |
| - vit | |
| - batik | |
| - indonesia | |
| # Batik ViT Model Confident | |
| Model ini adalah model klasifikasi jenis batik berbasis Vision Transformer (ViT). | |
| Model digunakan pada project **Batik ViT Classifier** untuk mengklasifikasikan gambar batik Indonesia. | |
| ## Dataset | |
| Dataset berasal dari Kaggle: | |
| **Batik Nusantara (Batik Indonesia) Dataset** | |
| Author: HendryHB | |
| Link: https://www.kaggle.com/datasets/hendryhb/batik-nusantara-batik-indonesia-dataset | |
| ## Jenis Batik yang Dapat Dideteksi | |
| Model ini dilatih untuk mengenali 20 jenis batik: | |
| 1. Aceh Pintu Aceh | |
| 2. Bali Barong | |
| 3. Bali Merak | |
| 4. DKI Ondel Ondel | |
| 5. Jawa Barat Megamendung | |
| 6. Jawa Timur Pring | |
| 7. Kalimantan Dayak | |
| 8. Lampung Gajah | |
| 9. Madura Mataketeran | |
| 10. Maluku Pala | |
| 11. NTB Lumbung | |
| 12. Papua Asmat | |
| 13. Papua Cendrawasih | |
| 14. Papua Tifa | |
| 15. Solo Parang | |
| 16. Sulawesi Selatan Lontara | |
| 17. Sumatera Barat Rumah Minang | |
| 18. Sumatera Utara Boraspati | |
| 19. Yogyakarta Kawung | |
| 20. Yogyakarta Parang | |
| ## Catatan | |
| Model ini tidak 100% akurat karena dataset masih terbatas dan jenis batik di Indonesia sangat banyak. | |
| Hasil prediksi dipengaruhi oleh kualitas gambar, pencahayaan, sudut pengambilan foto, background, dan kemiripan motif antar kelas. |