CV_2 Computer Vision Dataset
About CV_2 Dataset
A description for this project has not been published yet.
Use Free * 50% probability of horizontal flip, * Auto-orientation of pixel data (with EXIF-orientation stripping) and * Random rotation of between -1 and +1 degrees 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": "* 50% probability of horizontal flip, * Auto-orientation of pixel data (with EXIF-orientation stripping), * Random rotation of between -1 and +1 degrees, * Random shear of between -2° to +2° horizontally and -2° to +2° vertically, * Randomly crop between 0 and 5 percent of the image"
},
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
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{ cv_2-5u3vo_dataset,
title = { CV_2 Dataset },
type = { Open Source Dataset },
author = { Computer Vision PrJ },
howpublished = { \url{ https://universe.roboflow.com/computer-vision-prj/cv_2-5u3vo } },
url = { https://universe.roboflow.com/computer-vision-prj/cv_2-5u3vo },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { jul },
note = { visited on 2026-07-29 },
}