Identify MLB teams
using AI
Below is a free classifier to identify MLB teams. Just upload your image, and our AI will predict which Major League Baseball team a player belongs to - 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("mlb-teams", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/mlb-teams/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/mlb-teams/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict which Major League Baseball team a player belongs to.
This pretrained image model uses a Nyckel-created dataset and has 28 labels, including Angels, Astros, Athletics, Blue Jays, Braves, Brewers, Cardinals, Cubs, Diamondbacks and Dodgers.
We'll also show a confidence score (the higher the number, the more confident the AI model is around which Major League Baseball team a player belongs to).
Whether you're just curious or building MLB teams detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify MLB teams at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Fan Engagement Analysis: This use case involves utilizing the false image classification function to analyze fan-generated content on social media, identifying images tagged with MLB teams that might contain misleading or altered content. By understanding misrepresentation of teams in visual content, organizations can enhance engagement strategies and ensure accurate branding in their promotional efforts.
- Merchandise Authenticity Verification: Retailers can use the function to classify images of merchandise associated with MLB teams, helping to identify counterfeit products. By filtering out false representations, businesses can protect their brand integrity and improve consumer trust in official merchandise.
- Content Moderation for Social Media: Social media platforms can integrate this classification function to automatically filter out misleading images related to MLB teams. This helps maintain a healthy online environment, ensuring that users are exposed to authentic content that accurately represents teams and their activities.
- Marketing Campaign Optimization: By using the false image classification function, marketing teams can analyze visual content related to MLB teams in their campaigns to identify inaccuracies or misleading representations. This enables them to refine their messaging, ensuring that promotional materials accurately reflect the teams and resonate with fans.
- Sponsorship and Partnership Evaluation: Companies looking to sponsor MLB teams can use this function to analyze the visual content associated with potential partners. By identifying false or misleading imagery, businesses can make informed decisions about their sponsorship investments and ensure they align with authentic representations of the team.
- Data Enrichment for Fan Analytics: Sports analytics platforms can leverage this classification function to enrich their datasets by identifying and removing misleading images related to MLB teams. This enhances the quality of insights generated from fan data, allowing for more accurate market segmentation and targeting.
- Compliance Monitoring for Advertisements: Regulatory bodies and organizations can employ the false image classification function to monitor advertisements featuring MLB teams for compliance with industry standards. By detecting and addressing misleading visuals, they can help protect fans and consumers from deceptive marketing practices.