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06bf0a6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | 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
# Load the model (ensure model file is in the same directory or provide correct path)
@st.cache(allow_output_mutation=True)
def load_model():
# Replace 'model.pkl' with your model file
model = load_learner('modelmarvel.pkl')
return model
# Load the model
model = load_model()
# Streamlit application
st.title("Image Classification with fastai")
# Image upload
uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
if uploaded_file:
# Open and display the image
image = Image.open(uploaded_file).convert("RGB")
st.image(image, caption="Uploaded Image", use_column_width=True)
# Prepare image for the model
img = PILImage.create(uploaded_file)
# Predict
pred, pred_idx, probs = model.predict(img)
# Display results
st.write(f"Prediction: {pred}")
st.write(f"Probability: {probs[pred_idx]:.4f}")
# Optionally, display confidence as a bar chart
st.bar_chart(probs.numpy()) |