Universe

field_crop_20221104 Computer Vision Dataset

bysensorTask:
Object Detection
License:CC BY 4.033 views1 download
See all 423 imagesfield_crop_20221104 crop sample showing Cabbagefield_crop_20221104 crop sample showing Cabbage, radish_1field_crop_20221104 crop sample showing Cabbage, radish_1field_crop_20221104 crop sample showing radish_2field_crop_20221104 crop sample showing Cabbagefield_crop_20221104 crop sample showing Cabbagefield_crop_20221104 crop sample showing radish_2field_crop_20221104 crop sample showing radish_1, radish_2field_crop_20221104 crop sample showing radish_2field_crop_20221104 crop sample showing Cabbage, radish_1field_crop_20221104 crop sample showing Cabbagefield_crop_20221104 crop sample showing Cabbage

About field_crop_20221104 Dataset

Here are a few use cases for this project:

  1. Precision Agriculture: The "field_crop_20221104" model can be used in precision farming by helping farmers identify different crop types on their land to optimize field management. The accurate identification of Cabbage, radish_2, and radish_1 can aid in prescribing appropriate treatments, timings, and locations for intervention.

  2. Crop Health Management: The model can be combined with other plant health indicators to predict disease outbreaks or pest infestations specific to these crops. Early identification can help prevent spread and potentially major losses.

  3. Crop Rotation Planning: Farmers can use this model to detect the current crops and use the information to plan successful crop rotations, improving soil health and crop production in the process.

  4. Agro-climatic Research: Climate researchers and botanists could use this model to study the impact of changing climate conditions on the distribution and health of specific crops over time.

  5. Grocery Supply Chain Management: The model can be implemented into the supply chain by helping grocery stores and distributors estimate the quantity and predict the availability of these crops from their network of growers.

Use Free Cabbage, Radish_1 and Radish_2 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": "Cabbage, radish_1, radish_2"
  },
  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{ field_crop_20221104_dataset,
  title = { field_crop_20221104 Dataset },
  type = { Open Source Dataset },
  author = { sensor },
  howpublished = { \url{ https://universe.roboflow.com/sensor-hq923/field_crop_20221104 } },
  url = { https://universe.roboflow.com/sensor-hq923/field_crop_20221104 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { nov },
  note = { visited on 2026-07-29 },
}

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