Image Classification
ultralytics
TensorBoard
PyTorch
v8
ultralyticsplus
yolov8
yolo
vision
awesome-yolov8-models
Eval Results (legacy)
Instructions to use keremberke/yolov8n-pokemon-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use keremberke/yolov8n-pokemon-classification with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("keremberke/yolov8n-pokemon-classification") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - ultralyticsplus | |
| - yolov8 | |
| - ultralytics | |
| - yolo | |
| - vision | |
| - image-classification | |
| - pytorch | |
| - awesome-yolov8-models | |
| library_name: ultralytics | |
| library_version: 8.0.21 | |
| inference: false | |
| datasets: | |
| - keremberke/pokemon-classification | |
| model-index: | |
| - name: keremberke/yolov8n-pokemon-classification | |
| results: | |
| - task: | |
| type: image-classification | |
| dataset: | |
| type: keremberke/pokemon-classification | |
| name: pokemon-classification | |
| split: validation | |
| metrics: | |
| - type: accuracy | |
| value: 0.02322 # min: 0.0 - max: 1.0 | |
| name: top1 accuracy | |
| - type: accuracy | |
| value: 0.09016 # min: 0.0 - max: 1.0 | |
| name: top5 accuracy | |
| <div align="center"> | |
| <img width="640" alt="keremberke/yolov8n-pokemon-classification" src="https://huggingface.co/keremberke/yolov8n-pokemon-classification/resolve/main/thumbnail.jpg"> | |
| </div> | |
| ### Supported Labels | |
| ``` | |
| ['Abra', 'Aerodactyl', 'Alakazam', 'Alolan Sandslash', 'Arbok', 'Arcanine', 'Articuno', 'Beedrill', 'Bellsprout', 'Blastoise', 'Bulbasaur', 'Butterfree', 'Caterpie', 'Chansey', 'Charizard', 'Charmander', 'Charmeleon', 'Clefable', 'Clefairy', 'Cloyster', 'Cubone', 'Dewgong', 'Diglett', 'Ditto', 'Dodrio', 'Doduo', 'Dragonair', 'Dragonite', 'Dratini', 'Drowzee', 'Dugtrio', 'Eevee', 'Ekans', 'Electabuzz', 'Electrode', 'Exeggcute', 'Exeggutor', 'Farfetchd', 'Fearow', 'Flareon', 'Gastly', 'Gengar', 'Geodude', 'Gloom', 'Golbat', 'Goldeen', 'Golduck', 'Golem', 'Graveler', 'Grimer', 'Growlithe', 'Gyarados', 'Haunter', 'Hitmonchan', 'Hitmonlee', 'Horsea', 'Hypno', 'Ivysaur', 'Jigglypuff', 'Jolteon', 'Jynx', 'Kabuto', 'Kabutops', 'Kadabra', 'Kakuna', 'Kangaskhan', 'Kingler', 'Koffing', 'Krabby', 'Lapras', 'Lickitung', 'Machamp', 'Machoke', 'Machop', 'Magikarp', 'Magmar', 'Magnemite', 'Magneton', 'Mankey', 'Marowak', 'Meowth', 'Metapod', 'Mew', 'Mewtwo', 'Moltres', 'MrMime', 'Muk', 'Nidoking', 'Nidoqueen', 'Nidorina', 'Nidorino', 'Ninetales', 'Oddish', 'Omanyte', 'Omastar', 'Onix', 'Paras', 'Parasect', 'Persian', 'Pidgeot', 'Pidgeotto', 'Pidgey', 'Pikachu', 'Pinsir', 'Poliwag', 'Poliwhirl', 'Poliwrath', 'Wigglytuff', 'Zapdos', 'Zubat'] | |
| ``` | |
| ### How to use | |
| - Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus): | |
| ```bash | |
| pip install ultralyticsplus==0.0.23 ultralytics==8.0.21 | |
| ``` | |
| - Load model and perform prediction: | |
| ```python | |
| from ultralyticsplus import YOLO, postprocess_classify_output | |
| # load model | |
| model = YOLO('keremberke/yolov8n-pokemon-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)** |