
This is a fine-tunned object detection model for fashion.

For more details of the implementation you can check the source code [here](https://github.com/valntinaf/fine_tunning_YOLOS_for_fashion)

the dataset used for its training is available [here](https://huggingface.co/datasets/detection-datasets/fashionpedia)

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']


![image](https://miro.medium.com/v2/resize:fit:1400/format:webp/1*q8TTgxX_gf6vRe5AJN2r4g.png)

{"language": ["en"], "tags": ["YOLOS", "Object detection"], "datasets": ["detection-datasets/fashionpedia"], "pipeline_tag": "object-detection"}
transformers pytorch yolos object-detection YOLOS Object detection en dataset:detection-datasets/fashionpedia endpoints_compatible region:us