Identify if peas are moldy
using AI
Below is a free classifier to identify if peas are moldy. Just upload your image, and our AI will predict if peas are moldy - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-peas-are-moldy", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/if-peas-are-moldy/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/if-peas-are-moldy/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if peas are moldy.
This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Peas Are Fresh and Peas Are Moldy.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if peas are moldy).
Whether you're just curious or building if peas are moldy detection into your application, we hope our classifier proves helpful.
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Need to identify if peas are moldy at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Quality Control in Food Processing: Implementing the 'if peas are moldy' identifier can enhance quality control processes in food processing plants. By automating the detection of moldy peas, companies can reduce waste, ensure product safety, and maintain high standards for consumer products.
- Retail Inventory Management: Retailers can use this function to assess the freshness of their pea inventory. By identifying and removing moldy peas from shelves, stores can improve the customer experience, reduce returns, and increase overall sales of fresh produce.
- Supply Chain Monitoring: Implementing this identifier in supply chain logistics can help monitor the condition of peas during transportation. Early detection of mold can prompt immediate action, preventing compromised products from reaching consumers and minimizing losses for distributors.
- Consumer Health and Safety: Food delivery services can integrate this function to ensure that only fresh, uncontaminated peas are delivered to customers. By using this technology, services can enhance food safety, build trust with consumers, and reduce health risks associated with moldy produce.
- Agricultural Research and Development: Researchers in agriculture can apply this classification function to study mold growth patterns in peas under varying conditions. This data can inform breeding programs focused on developing mold-resistant pea varieties, thereby improving crop yield and quality.
- Smart Farming Solutions: Farmers can utilize this identifier with IoT devices in the field to monitor the health of their crops in real-time. By identifying moldy peas early, farmers can take prompt action to manage crop health, optimizing their yield and reducing pesticide usage.
- Environmental Impact Assessment: Food waste generated by moldy produce has a significant environmental impact. By implementing this function in various stages of the food supply chain, stakeholders can better assess and mitigate the environmental costs associated with food spoilage, leading to more sustainable practices.