Universe

new_yaotian Computer Vision Dataset

by杜昊晨Task:
Object Detection
License:CC BY 4.014 views1 download
See all 739 imagesnew_yaotian defection sample showing aokengnew_yaotian defection sample showing zhuangqinew_yaotian defection sample showing zhuangqinew_yaotian defection sample showing aokeng, yinhuasunshang, zhuangqinew_yaotian defection sample showing aokengnew_yaotian defection sample showing zhuangqinew_yaotian defection sample showing aokengnew_yaotian defection sample showing zhuangqinew_yaotian defection sample showing diaoqi, xiaotousunshang, zhuangqinew_yaotian defection sample showing zhuangqinew_yaotian defection sample showing aokengnew_yaotian defection sample showing diaoqi, zhuangqi

About new_yaotian Dataset

Here are a few use cases for this project:

  1. Industrial Quality Control: The new_yaotian model can be used in various industries such as manufacturing, textiles, and automotive, where it can help in identifying different types of defects in the production process. This would lead to improved product quality and less wastage.

  2. Archaeology and Art restoration: This model can assist archaeologists or art restorers in the identification of deteriorations and damages on artifacts or paintings such as "zhuangqi" or "diaoqi", facilitating in the restoration process.

  3. Agriculture: The new_yaotian model can be used in agriculture for identifying diseases or defects in crops, thus helping take corrective actions early, resulting in improved crop health and yield.

  4. Photo Restoration: In the field of photography and film, this model could be instrumental in identifying and categorizing various types of damages in vintage or old photographs/films, which can further aid in their restoration.

  5. Healthcare: This model can contribute to performing examination of medical images such as X-Rays or CT scans, helping in the identification of certain defect classes, thus assisting doctors with diagnosis. It's important to notice that this would require an extremely high level of accuracy and reliability.

Use Free Aokeng, Diaoqi and Xianxinglashang 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": "aokeng, diaoqi, xianxinglashang, xiaotousunshang, yinhuasunshang"
  },
  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{ new_yaotian_dataset,
  title = { new_yaotian Dataset },
  type = { Open Source Dataset },
  author = { 杜昊晨 },
  howpublished = { \url{ https://universe.roboflow.com/-yttj2/new_yaotian } },
  url = { https://universe.roboflow.com/-yttj2/new_yaotian },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { apr },
  note = { visited on 2026-07-29 },
}

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