DrGM-ConvNeXt-V2L-Facial-Emotion-Recognition

from transformers import AutoImageProcessor, AutoModelForImageClassification
import torch
from PIL import Image

# Load Model
repo_name = "DrGM/DrGM-ConvNeXt-V2L-Facial-Emotion-Recognition" 
processor = AutoImageProcessor.from_pretrained(repo_name)
model = AutoModelForImageClassification.from_pretrained(repo_name)

# Predict
image = Image.open("path/to/your/image.jpg").convert("RGB")
inputs = processor(image, return_tensors="pt")

with torch.no_grad():
    logits = model(**inputs).logits
    predicted_label = logits.argmax(-1).item()
    print(model.config.id2label[predicted_label])