Trash_Detection Computer Vision Model
How to use the Trash_Detection 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: trash_detection-zoike/3 (6152 images)
Checkpoint: trash_detection-zoike/1
Mar 21, 2026
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="trash_detection-zoike/3")Give your agent everything it needs
Or, Use Free Can, Organic and Plastic_bottle 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": "can, organic, plastic_bottle"
},
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 Trash_Detection Model
This is for a project, it detects garbages. So far, it can only detects bottles for now.
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{ trash_detection-zoike_dataset,
title = { Trash_Detection Dataset },
type = { Open Source Dataset },
author = { Carlas Workspace },
howpublished = { \url{ https://universe.roboflow.com/carlas-workspace-srubh/trash_detection-zoike } },
url = { https://universe.roboflow.com/carlas-workspace-srubh/trash_detection-zoike },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { mar },
note = { visited on 2026-07-29 },
}