COCO 128 Computer Vision Model

bybandraiTask:
Object Detection
License:CC BY 4.0

How to use the COCO 128 Detection API

Try This Model

Drop an image here or click to upload

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="coco-128-nxvyz/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": "car, truck, bus, dog, cat"
  },
  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 COCO 128 Model

COCO 128 is a subset of 128 images of the larger COCO dataset. It reuses the training set for both validation and testing, with the purpose of proving that your training pipeline is working properly and can overfit this small dataset.

COCO 128 is a great dataset to use the first time you are testing out a new model.

Cite This Project

LicenseCC BY 4.0

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

@misc{ coco-128-nxvyz_dataset,
  title = { COCO 128 Dataset },
  type = { Open Source Dataset },
  author = { bandrai },
  howpublished = { \url{ https://universe.roboflow.com/bandrai/coco-128-nxvyz } },
  url = { https://universe.roboflow.com/bandrai/coco-128-nxvyz },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { jul },
  note = { visited on 2026-07-29 },
}

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