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Update app.py
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app.py
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@@ -9,12 +9,20 @@ import torch
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from PIL import Image
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from transformers import ViTForImageClassification, ViTImageProcessor
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# Load the model
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model_name = "trpakov/vit-face-expression"
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model = ViTForImageClassification.from_pretrained(model_name)
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image_processor = ViTImageProcessor.from_pretrained(model_name)
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# Streamlit app
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st.title("Emotion Recognition with vit-face-expression")
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@@ -43,6 +51,6 @@ if uploaded_image:
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# Display scores for each category
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st.write("Emotion Scores:")
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for label, score in zip(emotion_labels, outputs.logits[0]):
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from PIL import Image
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#from transformers import ViTForImageClassification, ViTImageProcessor
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from transformers import AutoImageProcessor, AutoModelForImageClassification
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# Load the model
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model_name = "trpakov/vit-face-expression"
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processor = AutoImageProcessor.from_pretrained(model_name)
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model = AutoModelForImageClassification.from_pretrained(model_name)
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# Load the model
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model_name = "trpakov/vit-face-expression"
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#model = ViTForImageClassification.from_pretrained(model_name)
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#image_processor = ViTImageProcessor.from_pretrained(model_name)
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# Streamlit app
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st.title("Emotion Recognition with vit-face-expression")
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# Display scores for each category
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#st.write("Emotion Scores:")
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#for label, score in zip(emotion_labels, outputs.logits[0]):
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# st.write(f"{label}: {score:.4f}")
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