Add initial application files and model

app.py

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+___all___ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
+from fastai.vision.all import *
+import gradio as gr
+
+# Load the trained model
+learn = load_learner('human_race_model.pkl')
+
+# Define the categories based on your model's output
+categories = learn.dls.vocab
+
+# Define the function to classify images
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# Define the Gradio components
+image = gr.Image(type='pil', label='Input Image')
+label = gr.Label()
+examples = ['example1.jpeg', 'example2.jpeg', 'example3.jpeg']  # Replace with your example images
+
+# Create and launch the Gradio interface
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, title="Image Classifier", examples=examples)
+intf.launch(inline=False)

human_race_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:515f3f10533d6b5510db7126eb5dd81936ced0ecedf535f036f35a84958da0b4
+size 47110142

requirements.txt

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+fastai
+fastapi
+uvicorn
+aiofiles