Universe

P3rs0n-23 Computer Vision Model

byTIP PsonTask:
Object Detection
License:CC BY 4.034 views4 downloads

How to use the P3rs0n-23 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="p3rs0n-23/1")
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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": "person, \, b"
  },
  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 
See all 9.8k imagesP3rs0n-23 pson sample showing personP3rs0n-23 pson sampleP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing personP3rs0n-23 pson sample showing person

About P3rs0n-23 Model

Here are a few use cases for this project:

  1. Social Media Content Moderation: The "P3rs0n-23" model could be used to automatically filter and categorize images on social media platforms. For instance, it could identify images with persons or bicycles, easing the process of content moderation and targeted advertisement.

  2. Surveillance Systems: This model could be applied to enhance security systems. For example, it could alert authorities when a person or a bicycle is detected in specific areas (like no-pedestrian zones or bicycle-free zones), improving overall safety.

  3. Smart City Planning: City planners could use this model to monitor the usage of public spaces, parks, or bike lanes. Tracking the movement of people and bicycles could provide rich data for city planning and development.

  4. Advanced Driver-Assistance Systems (ADAS): The model could help in recognizing pedestrians and bicycles on the road, thereby aiding in collision avoidance and ensuring safety in semi-autonomous and autonomous vehicles.

  5. Animal Care and Protection: Given its apparent ability to distinguish between different entities, including dogs, the model could be used in pet detection and tracking, thereby aiding animal rescue operations and population studies.

Cite This Project

LicenseCC BY 4.0

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

@misc{ p3rs0n-23_dataset,
  title = { P3rs0n-23 Dataset },
  type = { Open Source Dataset },
  author = { TIP Pson },
  howpublished = { \url{ https://universe.roboflow.com/tip-pson/p3rs0n-23 } },
  url = { https://universe.roboflow.com/tip-pson/p3rs0n-23 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { apr },
  note = { visited on 2026-07-29 },
}

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