soccerfinal Computer Vision Model

byclassTask:
Object Detection
License:CC BY 4.0252 views7 downloads

How to use the soccerfinal Detection API

Try This Model

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Or try a test image 

Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="soccerfinal/1")
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Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "ball, player, person, Referee, center_high"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 

About soccerfinal Model

Here are a few use cases for this project:

  1. Sports Analytics: The "soccerfinal" computer vision model could be used to analyze matches by automatically tracking player movements, ball interactions, and referee calls. This information could help coaches develop new strategies, evaluate player performance, and identify patterns in the opposing team's gameplay.

  2. Live Game Highlight Creation: The model can be used to automatically detect key moments in a soccer match, such as goals, penalties, and corner kicks. This information can be used to create real-time highlights for viewers, improving fan engagement and media coverage.

  3. Soccer Training App: A mobile app can incorporate the "soccerfinal" model to provide personalized training for amateur and professional players. The app could analyze user-recorded soccer practice videos, providing feedback and tips to help players improve their skills and moves.

  4. Virtual and Augmented Reality Sports Experiences: The "soccerfinal" model can be integrated into VR/AR applications, allowing users to immerse themselves in a realistic soccer environment. Users could learn about specific game situations, analyze tactics, or practice their skills in a virtual setting.

  5. Security and Crowd Management: By identifying and tracking different elements and people (such as referees, players, and unauthorized persons) in a soccer match, the model can help ensure security and effective crowd management in stadiums, deterring trespassing, and reducing the likelihood of incidents during games.

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ soccerfinal_dataset,
  title = { soccerfinal Dataset },
  type = { Open Source Dataset },
  author = { class },
  howpublished = { \url{ https://universe.roboflow.com/class-fok1e/soccerfinal } },
  url = { https://universe.roboflow.com/class-fok1e/soccerfinal },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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