# Load model directly
from transformers import AutoImageProcessor, AutoModelForObjectDetection
processor = AutoImageProcessor.from_pretrained("valentinafevu/yolos-fashionpedia")
model = AutoModelForObjectDetection.from_pretrained("valentinafevu/yolos-fashionpedia", device_map="auto")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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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="valentinafevu/yolos-fashionpedia")