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import io
import time
import requests
import streamlit as st
from openfoodfacts.images import generate_image_url
from PIL import Image
@st.cache_data
def send_prediction_request(image_url: str, model_name: str, server_base_url: str):
return requests.get(
f"{server_base_url}/api/v1/images/predict",
params={"image_url": image_url, "models": model_name, "output_image": 1},
)
def get_product(barcode: str):
r = requests.get(f"https://world.openfoodfacts.org/api/v2/product/{barcode}")
if r.status_code == 404:
return None
return r.json()["product"]
def run(barcode: str, model_names: list[str], server_base_url: str):
product = get_product(barcode)
st.markdown(f"[Product page](https://world.openfoodfacts.org/product/{barcode})")
if not product:
st.error(f"Product {barcode} not found")
return
images = product.get("images", [])
if not images:
st.error(f"No images found for product {barcode}")
return
for image_id, _ in images.items():
if not image_id.isdigit():
continue
image_url = generate_image_url(barcode, f"{image_id}")
for model_name in model_names:
start = time.monotonic()
response = send_prediction_request(image_url, model_name, server_base_url)
elapsed = time.monotonic() - start
if response.headers["Content-Type"] != "image/jpeg":
st.error(f"Error: {response.text}")
continue
image = Image.open(io.BytesIO(response.content))
st.write(f"Image {image_id}")
st.image(image, caption=f"Model: {model_name} ({elapsed:.2f}s)")
st.divider()
st.title("Object detection demo")
st.markdown(
"This Streamlit is useful to test object detection models running in production at Open Food Facts."
)
default_barcode = st.query_params["barcode"] if "barcode" in st.query_params else ""
model_names = st.multiselect(
"Models",
options=[
"nutrition-table-yolo",
"nutrition-table",
"nutriscore",
"nutriscore-yolo",
"universal-logo-detector",
],
help="Select the model(s) to use",
default=["nutrition-table-yolo", "nutrition-table"],
)
barcode = st.text_input(
"barcode", help="Barcode of the product", value=default_barcode
).strip()
st.query_params["barcode"] = barcode
# Default server is staging
server_base_url = "https://robotoff.openfoodfacts.net"
if "env" in st.query_params:
if st.query_params["env"] == "prod":
server_base_url = "https://robotoff.openfoodfacts.net"
elif st.query_params["env"] == "dev":
server_base_url = "http://localhost:5000"
if barcode:
run(barcode, model_names, server_base_url)
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