Universe

4class Computer Vision Dataset

byJack LiTask:
Object Detection
License:CC BY 4.0103 views2 downloads
See all 246 images4class Cells sample4class Cells sample showing Cancer, RBC4class Cells sample showing Cancer, RBC, WBC4class Cells sample showing Normal, RBC4class Cells sample showing Cancer, RBC, WBC4class Cells sample4class Cells sample showing Cancer, RBC, WBC4class Cells sample4class Cells sample4class Cells sample showing Cancer, RBC4class Cells sample showing Cancer, RBC4class Cells sample showing WBC

About 4class Dataset

Here are a few use cases for this project:

  1. Medical Diagnosis: The "4class" model can be employed by pathologists to accurately identify and quantify the different cell types in blood and tissue samples, assisting in the diagnosis of various blood disorders and diseases, including anemia, leukemia, and infections.

  2. Research and Drug Development: Researchers can use the "4class" model to analyze cellular response to experimental treatments, providing essential data for drug discovery, evaluating the efficacy of novel compounds, and understanding cell behavior under various conditions.

  3. Education and Training: The "4class" computer vision model can serve as an educational tool for medical students and professionals, facilitating their understanding of different cell types, their characteristics, and functions, while promoting accurate identification in laboratory settings.

  4. Automated Screening: Integration of the "4class" computer vision model into medical laboratory equipment can automate the process of cell classification during screenings or biopsies. This can help save time and reduce the risk of human errors during the evaluation of samples.

  5. Telemedicine and Remote Analysis: The "4class" model can support telemedicine platforms, making it possible for healthcare professionals to remotely access and evaluate blood and tissue samples. This would be particularly useful in underserved areas, where access to pathologists might be limited.

Use Free Can, Normal and Cance 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": "Can, Normal, Cance, Cancer, RBC"
  },
  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 

Cite This Project

LicenseCC BY 4.0

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

@misc{ 4class-k3rgo_dataset,
  title = { 4class Dataset },
  type = { Open Source Dataset },
  author = { Jack Li },
  howpublished = { \url{ https://universe.roboflow.com/jack-li/4class-k3rgo } },
  url = { https://universe.roboflow.com/jack-li/4class-k3rgo },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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