Universe

KP_2 Computer Vision Model

bydimgo1979gmailcomTask:
Object Detection
License:MIT290 views11 downloads

How to use the KP_2 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="kp_2/30")
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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": "Label, BPB, GB, GB_FULL, KP"
  },
  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 790 imagesKP_2 KP sample showing GB, KP_NS, NS, PBKP_2 KP sample showing GB, KP_NS, NS, PBKP_2 KP sample showing GB, GB_FULL, KP_NS, NS, PB, PB_FULLKP_2 KP sample showing GB, KP, TKP_2 KP sample showing GB, GB_FULL, KP_NS, NS, PBKP_2 KP sample showing GB, GB_FULL, KP_NS, NS, PBKP_2 KP sample showing GB, GB_FULL, KP_NS, NSKP_2 KP sample showing GB, KP_NS, NS, PB_FULLKP_2 KP sample showing GB, GB_FULL, KP_NS, NS, PBKP_2 KP sample showing BPB, GB, KP_NS, NS, PBKP_2 KP sample showing GB, GB_FULL, NSKP_2 KP sample showing KP, KP_NS, NS, PB, PB_FULL

About KP_2 Model

Here are a few use cases for this project:

  1. Medical Imaging: KP_2 can be applied in medical imaging for the identification and classification of different diseases represented by 'NS', 'GB', 'PB', etc. For instance, these could represent different types of brain anomalies, and the 'FULL' designation could denote a severe stage of the disease. Its use can help doctors and medical personnel in making more accurate diagnosis and treatment plans.

  2. Quality Control in Manufacturing: This model can be used to identify and classify different components or parts in a manufacturing assembly line represented by 'KP', 'PB', 'NTB', etc., detecting any faulty pieces. The 'FULL' subcategory could represent the completed product. KP_2 could greatly enhance the production efficiency and quality control.

  3. Astronomy and Space Research: If these abbreviations refer to different celestial bodies or phenomena like 'NS' for neutron star, 'GB' for globular cluster, 'PB' for pulsar binary etc., this model can be used to classify images of space, helping in more efficient astronomical research and discovery.

  4. Document Classification: In cases where 'KP', 'NPB', 'NTB' etc. represent different categories of documents or textual data, KP_2 can assist in sorting and categorizing documents for better information management.

  5. Ecological Conservation: If these classes represent different species or groups of animals ('T' for tigers, 'GB' for grizzly bears, 'PB' for polar bears, etc.), KP_2 could be used in wildlife monitoring programs to identify and track various animal populations, contributing to their conservation.

Cite This Project

LicenseMIT

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

@misc{ kp_2_dataset,
  title = { KP_2 Dataset },
  type = { Open Source Dataset },
  author = { dimgo1979gmailcom },
  howpublished = { \url{ https://universe.roboflow.com/dimgo1979gmailcom/kp_2 } },
  url = { https://universe.roboflow.com/dimgo1979gmailcom/kp_2 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { apr },
  note = { visited on 2026-07-29 },
}

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