s

app.py

@@ -1,14 +1,6 @@
-from transformers import ViTForImageClassification, ViTFeatureExtractor
-from PIL import Image
-import torch
+import gradio as gr
+from transformers import pipeline
 
-# Loading in Model
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model = ViTForImageClassification.from_pretrained( "imjeffhi/pokemon_classifier").to(device)
-feature_extractor = ViTFeatureExtractor.from_pretrained('imjeffhi/pokemon_classifier')
+pipe = pipeline(task="image-classification", model="microsoft/beit-base-patch16-224-pt22k-ft22k")
 
-# Caling the model on a test image
-img = Image.open('test.jpg')
-extracted = feature_extractor(images=img, return_tensors='pt').to(device)
-predicted_id = model(**extracted).logits.argmax(-1).item()
-predicted_pokemon = model.config.id2label[predicted_id]
+gr.Interface.from_pipeline(pipe, title="22k Image Classification", description="Object Recognition using Microsoft BEIT", examples = ['wonder_cat.jpg', 'aki_dog.jpg',], allow_flagging="never").launch(inbrowser=True)