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| # Importing some modules | |
| import gradio as gr | |
| from transformers import pipeline | |
| # Loading in the model | |
| MODEL_AGE = pipeline('image-classification', model='nateraw/vit-age-classifier', device=-1) | |
| MODEL_EMOTION = pipeline('image-classification', model='dennisjooo/emotion_classification', device=-1) | |
| def classify_image(image, top_k): | |
| # Getting the classification result | |
| age_result = MODEL_AGE(image) | |
| emotion_result = MODEL_EMOTION(image) | |
| # Reformating the classification result into a dictionary | |
| age_result = {result['label']: result['score'] for result in age_result[:min(int(top_k), 8)]} | |
| emotion_result = {result['label']: result['score'] for result in emotion_result[:min(int(top_k), 7)]} | |
| comment = text_comment(list(age_result.keys())[0]) | |
| # Returning the classification result | |
| return age_result, comment, emotion_result | |
| # comment based on age | |
| def text_comment(pred_class): | |
| match pred_class: | |
| case "3-9": | |
| return "Lost your way to the playground?" | |
| case "10-19": | |
| return "But Mom, I'm not a kid anymore!" | |
| case "20-29": | |
| return "You're in your prime!" | |
| case "30-39": | |
| return "Maturity comes with experience not age!" | |
| case "40-49": | |
| return "You're still young at heart!" | |
| case "50-59": | |
| return "Retirement is just around the corner!" | |
| case "60-69": | |
| return "You're a senior citizen now!" | |
| case "more than 70": | |
| return "Bye Bye" | |
| if __name__ == "__main__": | |
| # Definining the title of the interface | |
| title_text = """ | |
| # I will guess your age and mood based on your picture! | |
| --- | |
| Sajid Hussain | |
| """ | |
| # Creating the Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown(title_text) | |
| with gr.Row(equal_height=True): | |
| with gr.Column(): | |
| # Creating the input block | |
| image = gr.Image(label="Upload a picture of yourself", type="pil", scale=2) | |
| # Creating the example block | |
| gr.Examples(examples=[ | |
| "/content/Jony-Dep.jfif", | |
| "/content/Sami.jfif", | |
| "/content/imrankhan.jpg", | |
| ], inputs=[image], label="Or choose an example") | |
| with gr.Column(): | |
| # Getting the top k hyperparameter | |
| top_k = gr.Number(label="How many guesses do I get?", value=1) | |
| # Creating the output block | |
| age_label = gr.Label(label="Hey it's me, your age!") | |
| comment = gr.Textbox(label="Based on your age, I think you are...", | |
| placeholder="I'm still learning, so I might be wrong!") | |
| emotion_label = gr.Label(label="Hey it's me, your emotion!") | |
| with gr.Row(): | |
| # Submit button | |
| btn = gr.Button("Guess my age and emotion!") | |
| btn.click(classify_image, inputs=[image, top_k], outputs=[age_label, comment, emotion_label]) | |
| # Clear button | |
| clear = gr.Button("Refresh!") | |
| clear.click(lambda: [None, None, None, None], inputs=[], outputs=[image, age_label, comment, emotion_label]) | |
| # Launching the interface | |
| demo.launch(share=True, debug=True) |