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Age-and-Emotion-Classifier / app.py

dennisjooo

Removed `torch.cuda.isavailable()` from `app.py`

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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)]}

	# Add some text comment to it lol
	comment = text_comment(list(age_result.keys())[0])

	# Returning the classification result
	return age_result, comment, emotion_result

	# Snarky 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 "Oof, watch out for those wrinkles!"
	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 "Hey Siri, play 'My Way' by Frank Sinatra"


	if __name__ == "__main__":
	# Definining the title of the interface
	title_text = """
	# I will guess your age and mood based on your picture!
	---
	Totally not creepy, I promise :)
	<br>Made by [Dennis Jonathan](dennisjooo.github.io). A project for REA Mastering AI course.
	Age guessing model from [nateraw/vit-age-classifier](https://huggingface.co/nateraw/vit-age-classifier)
	<br>Mood-guessing model is a [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k)
	trained on [FastJobs/Visual_Emotional_Analysis](https://huggingface.co/datasets/FastJobs/Visual_Emotional_Analysis)
	"""

	# 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=[
	"./images/andrew.jpg",
	"./images/feifei.jpg",
	"./images/geoff.jpg",
	"./images/ilya.jpg",
	"./images/karpathy.jpg",
	"./images/lex.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("Beep boop, guess my age and emotion!")
	btn.click(classify_image, inputs=[image, top_k], outputs=[age_label, comment, emotion_label])

	# Clear button
	clear = gr.Button("Poof begone!")
	clear.click(lambda: [None, None, None, None], inputs=[], outputs=[image, age_label, comment, emotion_label])

	# Launching the interface
	demo.launch(share=True, debug=True)