Guava Computer Vision Model
How to use the Guava Detection API
Try This Model
Drop an image here or click to upload
Or try a test image
Model type: Roboflow 3.0 Object Detection (Fast)
Dataset: guava-7slni/1 (840 images)
Checkpoint: COCO
Jan 13, 2025
Code Snippets
from inference_sdk import InferenceHTTPClient
CLIENT = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="guava-7slni/1")Give your agent everything it needs
Or, Use Free Intact_guava, Intact_guava-rotten_guava and Rotten_guava 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": "intact_guava, intact_guava-rotten_guava, rotten_guava"
},
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
About Guava Model
A description for this project has not been published yet.
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{ guava-7slni_dataset,
title = { Guava Dataset },
type = { Open Source Dataset },
author = { Guavatrain },
howpublished = { \url{ https://universe.roboflow.com/guavatrain/guava-7slni } },
url = { https://universe.roboflow.com/guavatrain/guava-7slni },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { jan },
note = { visited on 2026-07-29 },
}