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import torch | |
import gradio as gr | |
from model import EmotiClassifier | |
predictor = EmotiClassifier() | |
labels = ['angry', 'disgust', 'fear', 'happy', 'neutral', 'sad', 'surprise'] | |
predictor.load_state_dict(torch.load('emoticlassifier-64acc-1_250loss.pth')) | |
def classify(image): | |
torch_image = torch.Tensor(image) | |
torch_image = torch_image.view(1, 1, torch_image.shape[0], torch_image.shape[1]) | |
pred = predictor(torch_image) | |
label = torch.argmax(pred) | |
pred_class = label.item() | |
return labels[pred_class] | |
webcam = gr.Image(source='webcam', streaming=True, shape=(48, 48), image_mode='L', interactive=True, tool="editor") | |
interface = gr.Interface(fn=classify, inputs=webcam, outputs='text') | |
interface.launch(); | |