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File size: 2,431 Bytes
44bf352 | 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 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | import streamlit as st
import requests
from PIL import Image
import io
import time
API_BASE_URL = "http://localhost:7860"
st.set_page_config(page_title="AgroVisor AI System", page_icon="🌱", layout="wide")
st.title("🌱 AgroVisor AI System")
st.markdown("Efficient, modular backend with queuing and resource management.")
# Sidebar
st.sidebar.title("Navigation")
page = st.sidebar.radio("Choose task", [
"Unified Classification",
"Plant Disease Detection",
"Paddy Disease Classification",
"Pest Identification"
])
# Helper to handle API requests and queue status
def predict(endpoint, file):
files = {"file": (file.name, file.getvalue(), file.type)}
try:
response = requests.post(f"{API_BASE_URL}/predict/{endpoint}", files=files, timeout=60)
if response.status_code == 200:
return response.json(), None
elif response.status_code == 429:
return None, "Server busy or queue full. Please wait and try again."
else:
return None, f"Error: {response.status_code} - {response.text}"
except requests.exceptions.RequestException as e:
return None, f"Request failed: {e}"
# Main UI logic
def show_predict_ui(endpoint, label):
st.header(label)
uploaded_file = st.file_uploader(f"Upload an image for {label.lower()}", type=["jpg", "jpeg", "png"])
if uploaded_file:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
if st.button(f"Predict {label}"):
with st.spinner("Processing and waiting in queue if needed..."):
result, error = predict(endpoint, uploaded_file)
if error:
st.error(error)
elif result:
st.success("Prediction complete!")
st.json(result)
if page == "Unified Classification":
show_predict_ui("unified", "Unified Classification")
elif page == "Plant Disease Detection":
show_predict_ui("plant-disease", "Plant Disease Detection")
elif page == "Paddy Disease Classification":
show_predict_ui("paddy-disease", "Paddy Disease Classification")
elif page == "Pest Identification":
show_predict_ui("pest", "Pest Identification")
st.sidebar.markdown("---")
st.sidebar.info("Backend: FastAPI (modular, lazy loading, LRU cache, queuing)")
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