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Project Type

Object Detection

Classification

Instance Segmentation

+3

Model Type

RF-DETR

YOLO26

YOLOv11

YOLOv8

YOLO-NAS

+4

Classes

Related Objects of Interest:

apiaceae fabaceae lamiaceae rosaceae asparagaceae

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Try Brassicaceae Detection API

Run on custom image

Drop or click to upload

# 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": "brassicaceae"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Top Brassicaceae Datasets and Models

The datasets below can be used to train fine-tuned models for brassicaceae detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.

Related Objects of Interest:

apiaceae fabaceae lamiaceae rosaceae asparagaceae

weed_detect project thumbnail

Object Detection

weed_detect

by Mattia Bradley

3.01k images1 model10

wheat barley: tillering weed: brassicaceae weed: monocot weed: poaceae weed:dicot weed_dicot weed_monocot wheat: elong wheat: heading wheat: tillering

Roboweeds 2022 project thumbnail

Object Detection

Roboweeds 2022

1.15k images3

weed: brassicaceae weed: poaceae

pollenidentification project thumbnail

Object Detection

pollenidentification

by Pollen identification

4.53k images1 model

Acacia Fabaceae Amaranthaceae Brassicaceae D1 Brassicaceae D2 Brassicaceae D3 Brassicaceae D4 Pinaceae-formally called Gramineae-grass B3 Ziziphus SP Rhamnaceae E1 Ziziphus SP Rhamnaceae E2 Ziziphus SP Rhamnaceae E3 Ziziphus SP Rhamnaceae E4 Ziziphus SP Rhamnaceae F4 Ziziphus SP Rhamnaceae F5

Brassicaceae Diseases project thumbnail

Object Detection

Brassicaceae Diseases

by SurentharRajamohan

3.33k images3

* 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping)* Random rotation of between -15 and +15 degrees * Random shear of between -4° to +4° horizontally and -4° to +4° vertically * Resize to 420x420 (Stretch)* annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time ==============================Alternaria-Spot Brassicaceae Diseases - v1 2024-11-26 12:42pm Brassicaceae Diseases - v2 2024-11-26 12:49pm Brassicaceae Diseases - v3 2024-11-26 12:56pm Club Root Diseases-wbZv-T77K are annotated in YOLOv8 format.Downy-Mildew

Roboweed-v1 project thumbnail

Object Detection

Roboweed-v1

by RoboweedMapsTeimouriEtal22

1.15k images2

weed: brassicaceae weed: poaceae

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