Image Classification
timm
Safetensors
PyTorch
Turkish
English
timm-image-classification
efficientnetv2
vehicle-classification
car-body-type
Eval Results (legacy)
Instructions to use ryan12345441/car-body-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use ryan12345441/car-body-classifier with timm:
import timm model = timm.create_model("hf_hub:ryan12345441/car-body-classifier", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Update model card title
Browse files
README.md
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@@ -20,7 +20,7 @@ metrics:
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base_model: timm/tf_efficientnetv2_s.in21k_ft_in1k
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base_model_relation: finetune
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model-index:
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- name:
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results:
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type: image-classification
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name: Test Weighted F1
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---
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#
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This repository contains a PyTorch/timm EfficientNetV2-S image classifier for 8 vehicle body types. The model predicts one of `SUV`, `VAN`, `STATION_WAGON`, `MICRO`, `ACIK_TEKERLEKLI_F1_ARACLARI`, `SEDAN`, `HATCHBACK`, or `PICK_UP` from a single RGB vehicle image.
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base_model: timm/tf_efficientnetv2_s.in21k_ft_in1k
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base_model_relation: finetune
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model-index:
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- name: EfficientNetV2-S Car Body Classifier
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results:
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- task:
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type: image-classification
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name: Test Weighted F1
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---
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# EfficientNetV2-S Car Body Classifier
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This repository contains a PyTorch/timm EfficientNetV2-S image classifier for 8 vehicle body types. The model predicts one of `SUV`, `VAN`, `STATION_WAGON`, `MICRO`, `ACIK_TEKERLEKLI_F1_ARACLARI`, `SEDAN`, `HATCHBACK`, or `PICK_UP` from a single RGB vehicle image.
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