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Project Type
Object Detection
Classification
Instance Segmentation
+3

Model Type
RF-DETR
YOLO26
YOLOv11
YOLOv8
YOLO-NAS
+4

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r1t1r1t10r1t11r1t12r1t13

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Try R1t3 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": "r1t3"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Top R1t3 Datasets and Models

The datasets below can be used to train fine-tuned models for r1t3 detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.

Related Objects of Interest:
r1t1r1t10r1t11r1t12r1t13
custard_apple project thumbnail
Object Detection

custard_apple

by kapil

232 images
treer1t1r1t10r1t11r1t12r1t13r1t14r1t15r1t16r1t17r1t18r1t19r1t2r1t20r1t21r1t22r1t23r1t24r1t25r1t3
tree identication using CNN project thumbnail
Object Detection

tree identication using CNN

by sreeja

588 images
01R11T25R1T1R1T10R1T11R1T12R1T13R1T14R1T15R1T16R1T17R1T18R1T19R1T2R1T20R1T21R1T22R1T23R1T24
object detection using CNN project thumbnail
Object Detection

object detection using CNN

by Cheruvu Sirisha

601 images
01R1T1R1T10R1T11R1T12R1T13R1T14R1T15R1T16R1T17R1T18R1T19R1T2R1T20R1T21R1T22R1T23R1T24R1T25
kesari-evg project thumbnail
Object Detection

kesari-evg

by mango segmentation

290 images
10-1111-1212-1313-1414-1515-1616-1717-1818-1919-202-33-44-55-66-77-88-99-10R1 T2R1T1
Kesari_18th_aprl_fullbox project thumbnail
Object Detection

Kesari_18th_aprl_fullbox

by kapil

301 images
treer1t1r1t10r1t11r1t12r1t13r1t14r1t15r1t16r1t17r1t18r1t19r1t2r1t20r1t21r1t22r1t23r1t24r1t25r1t3
Showing 1 - 5 of 5
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