Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
English
vit
huggingpics
Eval Results (legacy)
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("IrshadG/Clothes_Pattern_Classification_v2")
model = AutoModelForImageClassification.from_pretrained("IrshadG/Clothes_Pattern_Classification_v2")Quick Links
Clothes_Pattern_Classification_v2
Classification to recognize pattern types in clothes. Best results if used after cropping the image Options:
'Solid', 'Stripe', 'All over pattern', 'Melange', 'Metallic', 'Denim', 'Colour blocking', 'Dot', 'Contrast', 'Check', 'Chambray', 'Front print', 'Glittering/Metallic', 'Placement print', 'Neps', 'Embroidery', 'Lace', 'Argyle', 'Slub', 'Mesh', 'Hologram']
Example Images
- Downloads last month
- 65
Evaluation results
- Accuracyself-reported0.918
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="IrshadG/Clothes_Pattern_Classification_v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")