| import subprocess |
| import sys |
|
|
| def install(package): |
| subprocess.check_call([sys.executable, "-m", "pip", "install", package]) |
|
|
| install('fastai') |
| install('torch') |
|
|
| import streamlit as st |
| from fastai.vision.all import * |
| from PIL import Image |
|
|
| |
| @st.cache(allow_output_mutation=True) |
| def load_model(): |
| |
| model = load_learner('model6.pkl') |
| return model |
|
|
| |
| model = load_model() |
|
|
| |
| st.title("Image Classification with fastai") |
|
|
| |
| uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"]) |
|
|
| if uploaded_file: |
| |
| image = Image.open(uploaded_file).convert("RGB") |
| st.image(image, caption="Uploaded Image", use_column_width=True) |
| |
| |
| img = PILImage.create(uploaded_file) |
| |
| |
| pred, pred_idx, probs = model.predict(img) |
| |
| |
| st.write(f"Prediction: {pred}") |
| st.write(f"Probability: {probs[pred_idx]:.4f}") |
|
|
| |
| st.bar_chart(probs.numpy()) |
|
|
