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import gradio as gr
from fastai.vision.all import load_learner
# Custom CSS for the app (remove background color from examples)
custom_css = """
body { background-color: #1E1E1E; color: #F5F5F5; }
.gradio-container { max-width: 800px; margin: auto; }
.input-panel, .output-panel {
background-color: #2E2E2E;
border: 2px solid #00BFFF;
border-radius: 10px;
box-shadow: 0 0 10px #00BFFF;
padding: 20px;
margin: 10px;
}
button {
background: linear-gradient(90deg, #00BFFF, #FF6B6B);
border: none;
color: #F5F5F5;
padding: 2px 5px;
border-radius: 2px;
cursor: pointer;
}
button:hover {
box-shadow: 0 0 10px #00BFFF;
}
"""
def classify_img(img) -> dict:
"""helper function to generate predictions"""
lbls = ['Cat', 'Dog']
preds, idx, probs = model.predict(img)
return dict(zip(lbls, map(float, probs)))
# load model
model = load_learner('model_2_ep_new_data.pkl')
# build app
image = gr.Image()
label = gr.Label()
examples = './inf_cs/'
app = gr.Interface(fn = classify_img, inputs = image, outputs = label, examples = examples, theme = 'earneleh/paris', css = custom_css,
examples_per_page = 7, flagging_mode = 'never', clear_btn = None)
app.launch()
# app.close() |