--- 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/yolov8s-pokemon-classification results: - task: type: image-classification dataset: type: keremberke/pokemon-classification name: pokemon-classification split: validation metrics: - type: accuracy value: 0.02459 # min: 0.0 - max: 1.0 name: top1 accuracy - type: accuracy value: 0.0806 # min: 0.0 - max: 1.0 name: top5 accuracy ---
keremberke/yolov8s-pokemon-classification
### 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/yolov8s-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} ```