Identify happy or sad
using AI
Below is a free classifier to identify happy or sad. Just upload your image, and our AI will predict if you're happy or sad - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("happy or sad-identifier", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/happy or sad-identifier/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/happy or sad-identifier/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if you're happy or sad.
This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Happy and Sad.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if you're happy or sad).
Whether you're just curious or building happy or sad detection into your application, we hope our classifier proves helpful.
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Need to identify happy or sad at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Marketing Campaigns Assessment: This function can be used by marketing departments to analyze the audience's reaction to different advertising content. It can identify whether the audience looks happy or sad, providing feedback on the efficacy of the campaign.
- Customer Service Improvement: Customer service representatives could use this function to better read and respond to customer emotions during a video call. It can help lead to better understanding of customer sentiment and improved service delivery.
- Employee Wellness Programs: HR departments can use the function to assess the emotional well-being of employees during internal meetings or video conferences. This can help in identifying potential issues and proactive measures to improve employee's mental health.
- E-Learning Platforms: The function can be used to gauge the effectiveness of teaching methods or materials, by analyzing the learners' emotional responses during the online learning process.
- User Experience Testing: It can be used to assess users' emotional response to a new product or technology. This can provide valuable insights for the design and improvement of the user interface or overall user experience.
- Market Research: The function can be used during focus group discussions or other market research activities. Observing whether participants appear happy or sad can provide additional data about their reaction to the product or concept being discussed.
- Social Media Analytics: Companies could use this function to analyze user reactions to their posts, updates, or ads on social media platforms. It can help in understanding audience sentiment and engagement, thus informing future marketing strategies.