Identify food delivery by logo
using AI
Below is a free classifier to identify food delivery by logo. Just upload your image, and our AI will predict what food delivery service the logo represents - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("food-delivery-by-logo", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/food-delivery-by-logo/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/food-delivery-by-logo/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict what food delivery service the logo represents.
This pretrained image model uses a Nyckel-created dataset and has 20 labels, including Berkich, Caviar, Chownow, Deliveroo, Delivery.Com, Doorbell, Doordash, Eatstreet, Foodpanda and Freshly.
We'll also show a confidence score (the higher the number, the more confident the AI model is around what food delivery service the logo represents).
Whether you're just curious or building food delivery by logo detection into your application, we hope our classifier proves helpful.
Need to identify food delivery by logo at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Logo-Based Delivery Validation: This function can be utilized by food delivery services to verify that the correct restaurant logo is present on the delivered packaging. This helps ensure brand integrity and prevent mix-ups that can lead to customer dissatisfaction.
- Fraud Prevention in Deliveries: By identifying the logos on food packages, this function can help detect fraudulent activities where incorrect or counterfeit logos are used. This will enhance security measures for delivery companies and maintain their reputation.
- Quality Control for Restaurant Partners: Restaurants can employ this logo identifier to conduct quality checks on delivery packaging. This ensures that the correct branding and logos are used consistently to promote a professional image across all deliveries.
- Enhanced Marketing Insights: Food delivery platforms can analyze logo identification data to understand customer preferences and restaurant performance. This information can drive targeted marketing strategies and promotional campaigns based on brand engagement metrics.
- Customer Feedback Mechanism: The function can facilitate a feedback loop whereby customers can report issues related to incorrect packaging or logos via an app. This will improve service reliability and customer experience by ensuring that brands are presented accurately.
- Training AI for Visual Recognition: The logo identification function can be utilized to enhance machine learning models in visual recognition. This training can improve the accuracy of automated systems in recognizing food packaging, logos, and associated branding over time.
- Integration with Smart Assistants: By incorporating the logo identification capability into smart home devices, customers could use voice commands to verify the logos of their food deliveries. This adds a layer of convenience and assurance for users regarding their meal orders.