|
|
|
--- |
|
tags: |
|
- ultralyticsplus |
|
- yolov8 |
|
- ultralytics |
|
- yolo |
|
- vision |
|
- image-classification |
|
- pytorch |
|
- awesome-yolov8-models |
|
library_name: ultralytics |
|
library_version: 8.0.23 |
|
inference: false |
|
|
|
datasets: |
|
- keremberke/painting-style-classification |
|
|
|
model-index: |
|
- name: keremberke/yolov8m-painting-classification |
|
results: |
|
- task: |
|
type: image-classification |
|
|
|
dataset: |
|
type: keremberke/painting-style-classification |
|
name: painting-style-classification |
|
split: validation |
|
|
|
metrics: |
|
- type: accuracy |
|
value: 0.05723 |
|
name: top1 accuracy |
|
- type: accuracy |
|
value: 0.21463 |
|
name: top5 accuracy |
|
--- |
|
|
|
<div align="center"> |
|
<img width="640" alt="keremberke/yolov8m-painting-classification" src="https://huggingface.co/keremberke/yolov8m-painting-classification/resolve/main/thumbnail.jpg"> |
|
</div> |
|
|
|
### Supported Labels |
|
|
|
``` |
|
['Abstract_Expressionism', 'Action_painting', 'Analytical_Cubism', 'Art_Nouveau_Modern', 'Baroque', 'Color_Field_Painting', 'Contemporary_Realism', 'Cubism', 'Early_Renaissance', 'Expressionism', 'Fauvism', 'High_Renaissance', 'Impressionism', 'Mannerism_Late_Renaissance', 'Minimalism', 'Naive_Art_Primitivism', 'New_Realism', 'Northern_Renaissance', 'Pointillism', 'Pop_Art', 'Post_Impressionism', 'Realism', 'Rococo', 'Romanticism', 'Symbolism', 'Synthetic_Cubism', 'Ukiyo_e'] |
|
``` |
|
|
|
### How to use |
|
|
|
- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus): |
|
|
|
```bash |
|
pip install ultralyticsplus==0.0.24 ultralytics==8.0.23 |
|
``` |
|
|
|
- Load model and perform prediction: |
|
|
|
```python |
|
from ultralyticsplus import YOLO, postprocess_classify_output |
|
|
|
# load model |
|
model = YOLO('keremberke/yolov8m-painting-classification') |
|
|
|
# set model parameters |
|
model.overrides['conf'] = 0.25 # model confidence threshold |
|
|
|
# set image |
|
image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg' |
|
|
|
# perform inference |
|
results = model.predict(image) |
|
|
|
# observe results |
|
print(results[0].probs) # [0.1, 0.2, 0.3, 0.4] |
|
processed_result = postprocess_classify_output(model, result=results[0]) |
|
print(processed_result) # {"cat": 0.4, "dog": 0.6} |
|
``` |
|
|
|
**More models available at: [awesome-yolov8-models](https://yolov8.xyz)** |
