Instructions to use lknjbvhgjhibkhvj/keklol123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lknjbvhgjhibkhvj/keklol123 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="lknjbvhgjhibkhvj/keklol123")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("lknjbvhgjhibkhvj/keklol123") model = AutoModelForObjectDetection.from_pretrained("lknjbvhgjhibkhvj/keklol123") - Notebooks
- Google Colab
- Kaggle
This is a fine-tunned object detection model for fashion.
For more details of the implementation you can check the source code here
the dataset used for its training is available here
this model supports the following categories:
CATS = ['shirt, blouse', 'top, t-shirt, sweatshirt', 'sweater', 'cardigan', 'jacket', 'vest', 'pants', 'shorts', 'skirt', 'coat', 'dress', 'jumpsuit', 'cape', 'glasses', 'hat', 'headband, head covering, hair accessory', 'tie', 'glove', 'watch', 'belt', 'leg warmer', 'tights, stockings', 'sock', 'shoe', 'bag, wallet', 'scarf', 'umbrella', 'hood', 'collar', 'lapel', 'epaulette', 'sleeve', 'pocket', 'neckline', 'buckle', 'zipper', 'applique', 'bead', 'bow', 'flower', 'fringe', 'ribbon', 'rivet', 'ruffle', 'sequin', 'tassel']
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