dp-cnic-detector Computer Vision Model
How to use the dp-cnic-detector Segmentation API
Try This Model
Drop an image here or click to upload
Or try a test image
Model type: YOLOv11 Instance Segmentation (Medium)
Dataset: dp-cnic-detector-yp1hr/3 (543 images)
Checkpoint: COCOm-seg
Sep 23, 2025
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="dp-cnic-detector-yp1hr/3")Give your agent everything it needs
Or, Use Free CNIC-Card-Address Detection API
Powered by general detection model
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": "CNIC-Card-Address"
},
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 dp-cnic-detector Model
A description for this project has not been published yet.
Roboflow Agent
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ dp-cnic-detector-yp1hr_dataset,
title = { dp-cnic-detector Dataset },
type = { Open Source Dataset },
author = { data pilot },
howpublished = { \url{ https://universe.roboflow.com/data-pilot/dp-cnic-detector-yp1hr } },
url = { https://universe.roboflow.com/data-pilot/dp-cnic-detector-yp1hr },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { sep },
note = { visited on 2026-07-29 },
}